The never ending growth of digital information and the availability of low-cost storage facilities and networks capacity is leading users towards moving their data to remote storage resources. Since users’ data often holds identity-related information, several privacy issues arise when data can be stored in untrusted domains. In addition digital identity management is becoming extremely complicated due to the identity replicas proliferation necessary to get authentication in different domains. GMail and Amazon Web Services, for instance, (...) are two examples of online services adopted by million of users throughout the world which hold huge amounts of sensitive users data. State-of-the-art encryption tools for large-scale distributed infrastructures allow users to encrypt content locally before storing it on a remote untrusted repository. This approach can experience performance drawbacks, when very large data-sets must be encrypted/decrypted on a single machine. The proposed approach extends the existing solutions by providing two additional features: (1) the encryption can also be delegated to a pool of remote trusted computing resources, and (2) the definition of the encryption context which drives the tool to select the best strategy to process the data. The performance benchmarks are based on the results of tests carried out both on a local workstation and on the Grid INFN Laboratory for Dissemination Activities (GILDA) testbed. (shrink)

—Industrial networks are increasingly based on open protocols and platforms that are also employed in the IT industry and Internet background. Most of the industries use wireless networks for communicating information and data, due to high cable cost. Since, the wireless networks are insecure, it is essential to secure the critical information and data during transmission. The data that transmitted is intercepted by eavesdropper can be predicted by secrecy capacity. The secrecy capacity is the difference between channel (...) capacity of main link and wiretap link of wireless transmission. When the secrecy capacity gets fades, then it is known that transmitted data is intercepted. In the event, of applying optimal sensor scheduling scheme a sensor with highest secrecy capacity is chosen and data is transmitted. It is followed with cooperative localization algorithm to enhance nodes, predict and maintain power of each sensor nodes. Through localization algorithm best sensor nodes are get predicted for transmission. Moreover, RC4 encryption and decryption algorithm is enhanced for data while transmission. This will enable protection to data to an extent. Also, an asymptotic intercept probability analysis is performed to provide an imminent into the impact of the sensor scheduling on the wireless security. (shrink)

Personal data is highly vulnerable to security exploits, spurring moves to lock it down through encryption, to cryptographically ‘cloud’ it. But personal data is also highly valuable to corporations and states, triggering moves to unlock its insights by relocating it in the cloud. We characterise this twinned condition as ‘clouded data’. Clouded data constructs a political and technological notion of privacy that operates through the intersection of corporate power, computational resources and the ability to (...) obfuscate, gain insights from and valorise a dependency between public and private. First, we survey prominent clouded data approaches, suggesting their particular affordances produce distinctive versions of privacy. Next, we perform two notional code-based experiments using synthetic datasets. In the field of health, we submit a patient’s blood pressure to a notional cloud-based diagnostics service; in education, we construct a student survey that enables aggregate reporting without individual identification. We argue that these technical affordances legitimate new political claims to capture and commodify personal data. The final section broadens the discussion to consider the political force of clouded data and its reconstitution of traditional notions such as the public and the private. (shrink)

Due to the complexity and versatility of network security alarm data, a cloud-based network security data extraction method is proposed to address the inability to effectively understand the network security situation. The information properties of the situation are generated by creating a set of spatial characteristics classification of network security knowledge, which is then used to analyze and optimize the processing of hybrid network security situation information using cloud computing technology and (...) co-filtering technology. Knowledge and information about the security situation of a hybrid network has been analyzed using cloud computing strategy. The simulation results show that a cyber security crash occurs in window 20, after which the protection index drops to window 500. The increase in the security index of 500 windows is consistent with the effectiveness of the concept of this document method, indicating that this document method can sense changes in the network security situation. Starting from the first attacked window, the defense index began to decrease. In order to simulate the added network defense, the network security events in the 295th time window were reduced in the original data, and the defense index increased significantly in the corresponding time period, which is consistent with the method perception results, which further verifies the effectiveness and reliability of this method on the network security event perception. This method provides high-precision knowledge of network security situations and improves the security and stability of cloud-based networks. (shrink)

This paper addresses the always online behavior of the data owner in proxy re- encryption schemes for re-encryption keys issuing. We extend and adapt multi-authority ciphertext policy attribute based encryption techniques to type-based proxy re-encryption to build our solution. As a result, user authentication and user authorization are moved to the cloud server which does not require further interaction with the data owner, data owner and data users identities are hidden from the cloud server, (...) and re-encryption keys are only issued to legitimate users. An in depth analysis shows that our scheme is secure, flexible and efficient for mobile cloud computing. (shrink)

In recent years, the network has become more complex, and the attacker’s ability to attack is gradually increasing. How to properly understand the network security situation and improve network security has become a very important issue. In order to study the method of extracting information about the security situation of the network based on cloud computing, we recommend the technology of knowledge of the network security situation based on the data extraction technology. It (...) converts each received cyber security event into a standard format that can be defined as multiple brochures, creating a general framework for the cyber security situation. According to the large nature of network security situation data, the Hadoop platform is used to extract aggregation rules, and perform model extraction, pattern analysis, and learning on a network security event dataset to complete network security situation rule mining, and establish a framework for assessing the state of network security. According to the results of the federal rule extraction, the level of network node security risk is obtained in combination with signal reliability, signal severity, resource impact, node protection level, and signal recovery factor. A simulation test is performed to obtain the intrusion index according to the source address of the network security alarm. Through the relevant experiments and analysis of the results, the attack characteristics obtained in this study were obtained after manually reducing the network security event in the 295 h window. The results show that after the security event is canceled, the corresponding window attack index decreases to 0, indicating that this method can effectively implement a network security situation awareness. The proposed technique allows you to accurately sense changes in network security conditions. (shrink)

Guided by the theories of system theory, synergetic theory, and other disciplines and based on fuzzy data mining algorithm, this article constructs a three-tier social security fund cloud audit platform. Firstly, the article systematically expounds the current situation of social security fund and social security fund audit, such as the technical basis of cloud computing and data mining. Combined with the actual work, the necessity and feasibility of building a cloud audit platform for social security (...) funds are analyzed. This article focuses on the construction of the cloud audit platform for social security funds. The general idea of using fuzzy data mining algorithm to build the social security fund audit cloud platform is to compress the knowledge contained in a large number of data into the weights between nodes and optimize the weights through the learning of the neural network system. Through the optimization function, the information contained in the neural network is stored in a few weights as far as possible. The main information is further highlighted by network clipping and removing weights that have little impact on the output. (shrink)

This paper examines one particular problem of values in cloud computing: how individuals can take advantage of the cloud to store data without compromising their privacy and autonomy. Through the creation of Lockbox, an encrypted cloud storage application, we explore how designers can use reflection in designing for human values to maintain both privacy and usability in the cloud.

The evolution of wireless communications, from the first to the fifth generation, has driven Internet of Things (IoT) advancements. IoT is transforming sectors like agriculture, healthcare, and transportation, but also presents challenges like spectrum bandwidth demand, speed requirements, and security issues. IoT environments, with embedded sensors and actuators, connect to other devices to transmit and receive data over the internet. These data are processed locally or in the cloud, enabling decision-making and automation. Various wireless technologies, including Bluetooth, (...) Zigbee, LoRa, and WiFi, cater to specific IoT applications. 5G, with its high speeds, low latency, and efficient bandwidth sharing, is ideal for high-speed data transmission, and thus it provides robust infrastructure for low-latency and bandwidth-sensitive applications. This latest mobile network technology is being rapidly implemented worldwide, providing unprecedented throughput and low latency, which are crucial for the IoT. This paper presents a comprehensive systematic review on 5G security features, vulnerabilities, threats to mobile devices, security in IoT devices, common attacks to IoT devices and protection of data in this environment. Despite enhanced security, 5G faces challenges like Distributed Denial of Service (DDoS), Man In The Middle (MITM), cross-slice disruptions, and side-channel attacks. (shrink)

An intelligent climate and watering agriculture system is presented that is controlled with Android application for smart water consumption considering small and medium ruler agricultural fields. Data privacy and security as a big challenge in current Internet of Things (IoT) applications, as with the increase in number of connecting devices, these devices are now more vulnerable to security threats. An intelligent fuzzy logic and blockchain technology is implemented for timely analysis and securing the network. The proposed design consists (...) of various sensors that collect real-time data from environment and field such as temperature, soil moisture, light intensity, and humidity. The sensed field information is stored in IoT cloud platform, and after the analysis of entries, watering is scheduled by implementing the intelligent fuzzy logic and blockchain. The intelligent fuzzy logic based on different set of rules for making smart decisions to meet the watering requirements of plant and blockchain technology provides necessary security to the IoT-enabled system. The implementation of blockchain technology allows access only to the trusted devices and manages the network. From the experimentation, it is observed that the proposed system is highly scalable and secure. Multiple users at the same time can monitor and interact with the system remotely by using the proposed intelligent agricultural system. The decisions are taken by applying intelligent fuzzy logic based on input variables, and an alert is transmitted about watering requirements of a field to the user. The proposed system is capable of notifying users for turning water motor on and off. The experimental outcomes of the proposed system also reveal that it is an efficient and highly secure application, which is capable of handling the process of watering the plants. (shrink)

This article starts with the analysis of the existing electronic commerce system, summarizes its characteristics, and analyzes and solves its existing problems. Firstly, the characteristics of the relational database My Structured Query Language and the distributed database HBase are analyzed, their respective advantages and disadvantages are summarized, and the advantages and disadvantages of each are taken into account when storing data. My SQL is used to store structured business data in the system, while HBase is used to store (...) unstructured data such as pictures. These two storage mechanisms together constitute a data storage subsystem. Secondly, considering the large amount of data in the e-commerce system and the complex calculation of the data mining algorithm, this paper uses MapReduce to realize the parallelization of the data mining algorithm and builds a Hadoop-based commodity recommendation subsystem on this basis. We use JavaEE technology to design a full-featured web mall system. Finally, based on the impact of cloud computing, mobile e-commerce is analyzed, including relevant theories, service mode, architecture, core technology, and the application in e-commerce, which can realize e-commerce precision marketing, find the optimal path of logistics, and take effective security measures to avoid transaction risks. This method can avoid the disadvantages of the traditional e-commerce, where large-scale data cannot be processed in a timely manner, realize the value of mining data behind, and realize the precision marketing of e-commerce enterprises. (shrink)

Big data technologies are entering the world of ageing computer systems running critical infrastructures. These innovations promise to afford rapid Internet connectivity, remote operations or predictive maintenance. As legacy critical infrastructures were traditionally disconnected from the Internet, the prospect of their modernisation necessitates an inquiry into cyber security and how it intersects with traditional engineering requirements like safety, reliability or resilience. Looking at how the adoption of big data technologies in critical infrastructures shapes understandings of risk management, we (...) focus on a specific case study from the cyber security governance: the EU Network and Information Systems Security Directive. We argue that the implementation of Network and Information Systems Security Directive is the first step in the integration of safety and security through novel risk management practices. Therefore, it is the move towards legitimising the modernisation of critical infrastructures. But we also show that security risk management practices cannot be directly transplanted from the safety realm, as cyber security is grounded in anticipation of the future adversarial behaviours rather than the history of equipment failure rates. Our analysis offers several postulates for the emerging research agenda on big data in complex engineering systems. Building on the conceptualisations of safety and security grounded in the materialist literature across Science and Technology Studies and Organisational Sociology, we call for a better understanding of the ‘making of’ technologies, standardisation processes and engineering knowledge in a quest to build safe and secure critical infrastructures. (shrink)

Smart grids are designed to revolutionize the energy sector by creating a smarter, more efficient and reliable power supply network. The rise of smart grids is a response to the need for a more comprehensive and sophisticated energy system that caters to the needs of homes and businesses. Key features of smart grids include the integration of renewable energy sources, decentralized generation and advanced distribution networks. At the heart of smart grids is a sophisticated metering system, consisting of intelligent (...) electronic devices that measure energy consumption and enable two-way communication between the utility company and the consumer. The information exchanged via these devices is critical, as it includes sensitive data such as energy consumption patterns and billing information. With the rise of the Internet of Things (IoT) and Industry 4.0, the security of this information is of utmost importance. This paper delves into the security challenges faced by advanced metering infrastructure (AMI) and highlights the crucial role played by cryptography in ensuring the secure exchange of sensitive information. Cryptographic protocols such as encryption, authentication and digital signatures are essential components of a secure smart grid infrastructure. These protocols work together to ensure the confidentiality, integrity and authenticity of the information exchanged between the utility company and the consumer. (shrink)

This essay explores the implications of a commonly held ancient and medieval belief that human memory and invention are, if not exactly the same, the closest thing to it. In order to create, in order to think at all, human beings require both a well-provisioned stock of memory-held knowledge and some mental tool or machine, an engine which lives in the intricate networks of their own memories. In the verbal arts of the trivium students learned the basic principles of memory (...) training: the need for divisio, the need to make a clear, distinct location for each piece of memorized content, and the need to mark items uniquely for secure recollection. Frequently these mental structures took the form of images. Evidence for such memorial and compositional images is common: I focus on a few representative types, including the sermon-related “Cherub” figure of the later Middle Ages, and accounts by Cassiodorus and others of scholars, even when blind, using their highly structured memories to compose new work. (shrink)

Over the past 30 years, computer engineering has developed a lot. Currently, computer and software applications have a central role in business, medicine, security, communications, industry, education, and everyday life. Software developers, peoples who manage computer networks, data security analysts can do well, but they also have the potential to cause suffering and harm to the clients or ordinary peoples, willingly or not. For this reason, IT activities must be regulated by specific laws. From the beginning, we argue that (...) the law is not the same thing as ethics, even if both promote the good. Certain ethical principles can be strengthened by law. In the field of computer science and technology, can exists theft, privacy violations, violence and harassment. To combat and punish such actions and behaviors, law is needed. But is software engineering a profession? If so, are there codes of professional ethics whereby specialists in the field can regulate their professional activity, as is the case, for example, in areas such as justice or medicine? In relation with that, Gibbs and Ford have identified 8 components of a professional infrastructure. Some of that is: initial vocational training, professional accreditation, licensing, continuous vocational training, the existence of code of ethics.. With the fact that software engineering is a profession, in this article we present the main principles of behavior. The principles are not legally binding. This are grouped by interest categories depending on who or what is involved in the interaction with software engineering. (shrink)

As an advanced network calculation mode, cloud computing is becoming more and more popular. However, with the proliferation of large data centers hosting cloud applications, the growth of energy consumption has been explosive. Surveys show that a remarkable part of the large energy consumed in data center results from over-provisioning of the network resource to meet requests during peak demand times. In this paper, we propose a solution to this problem by constructing a dynamic (...) energy-efficient resource management scheme. As a way of saving energy as well as maintaining cloud user’s quality of experience, the scheme presents a multitier cloud architecture by configuring physical machines into two pools: a hot pool and a warm pool. Each PM is configured with a resource search engine that finds an available virtual machine for the request, and a synchronous sleep mechanism is introduced to the warm pool. To analyze the end-to-end performance of the cloud system’s service with the proposed scheme, we establish a hybrid queueing system composed of three stochastic submodels by using a matrix-geometric solution. Accordingly, the average latency of requests and the energy-saving rate of the system are derived. Through numerical results, we show the influence of the synchronous sleep mechanism on the system performance. Moreover, from the perspective of economics, we build a system cost function to study the trade-off between different performance measures. An improved Salp Swarm Algorithm is presented to minimize the system cost and optimize the sleep parameter. (shrink)

IntroductionInformation and communication technologies are becoming an integral part of medical practice, research and administration and their use will grow as telemedicine and electronic medical record use become part of routine practice. Security in maintaining patient data is important and there is a statuary obligation to do so, but few health professionals have been trained on how to achieve this. There is no information on the use of computers and email by doctors and nurses in South Africa in the (...) workplace and at home, and whether their current computer practices meets legal and ethical requirements. The aims of this study were to determine the use of computers by healthcare practitioners in the workplace and home; the use and approach to data storage, encryption and security of patient data and patient email; and the use of informed consent to transmit data by email.MethodsA self-administered questionnaire was administered to 400 health care providers from the state and private health care sectors. The questionnaire covered computer use in the workplace and at home, sharing of computers, data encryption and storage, email use, encryption of emails and storage, and the use of informed consent for email communication.Results193 doctors and 207 nurses in the private and public sectors completed the questionnaire. Forty (10%) of participants do not use a computer. A third of health professionals were the only users of computers at work or at home. One hundred and ninety-eight respondents (55%) did not know if the data on the computers were encrypted, 132 (36.7%) knew that the data were not encrypted and 30 (8.3%) individuals knew that the data on the computers they were using were encrypted. Few doctors, 58 (16%), received emails from patients, with doctors more likely to receive emails from patients than nurses (p = 0.0025). Thirty-one percent of individuals did not respond to the emails. Emails were saved by 40 (69%) recipients but only 5 (12.5%) doctors encrypted the messages, 19 (47.5%) individuals knowingly did not encrypt and 16 (40.0%) did not know if they encrypted the data. While 20% of health professionals have emailed patient data, but only 41.7% gained consent to do so.ConclusionsMost health professionals as sampled in South Africa are not compliant with the National Health Act or the Electronic Communications Transactions Act of South Africa or guidelines from regulatory bodies when managing patient data on computers. Many appear ignorant or lack the ability to comply with simple data security procedures. (shrink)

In cloud security, intrusion detection system (IDS) is one of the challenging research areas. In a cloud environment, security incidents such as denial of service, scanning, malware code injection, virus, worm, and password cracking are getting usual. These attacks surely affect the company and may develop a financial loss if not distinguished in time. Therefore, securing the cloud from these types of attack is very much needed. To discover the problem, this paper suggests a novel IDS established (...) on a combination of a leader-based k-means clustering (LKM), optimal fuzzy logic system. Here, at first, the input dataset is grouped into clusters with the use of LKM. Then, cluster data are afforded to the fuzzy logic system (FLS). Here, normal and abnormal data are inquired by the FLS, while FLS training is done by the grey wolf optimization algorithm through maximizing the rules. The clouds simulator and NSL-Knowledge Discovery and DataBase (KDD) Cup 99 dataset are applied to inquire about the suggested method. Precision, recall, and F-measure are conceived as evaluation criteria. The obtained results have denoted the superiority of the suggested method in comparison with other methods. (shrink)

With the rapid growth of informatics systems’ technology in this modern age, the Internet of Things (IoT) has become more valuable and vital to everyday life in many ways. IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. However, the insecure nature of IoT devices has led to several difficulties, one of which is distributed denial-of-service (DDoS) attacks. IoT (...) systems have several security limitations due to their disreputability characteristics, like dynamic communication between IoT devices. The dynamic communications resulted from the limited resources of these devices, such as their data storage and processing units. Recently, many attempts have been made to develop intelligent models to protect IoT networks against DDoS attacks. The main ongoing research issue is developing a model capable of protecting the network from DDoS attacks that is sensitive to various classes of DDoS and can recognize legitimate traffic to avoid false alarms. Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. The RNN, CNN, LSTM, and CNN-BiLSTM are implemented and tested to determine the most effective model against DDoS attacks that can accurately detect and distinguish DDoS from legitimate traffic. The intrusion detection evaluation dataset (CICIDS2017) is used to provide more realistic detection. The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. The four models are tested and assessed using Confusion Metrix against four commonly used criteria: accuracy, precision, recall, and F-measure. The performance of the models is quite effective as they obtain an accuracy rate of around 99.00%, except for the CNN model, which achieves an accuracy of 98.82%. The CNN-BiLSTM achieves the best accuracy of 99.76% and precision of 98.90%. (shrink)

Informational self-determination refers to the right or ability of individuals to exercise personal control over the collection, use and disclosure of their personal data by others. The basis of modern privacy laws and practices around the world, informational privacy has become a challenging concept to protect and promote in a world of ubiquitous and unlimited data sharing and storage among organizations. The paper advocates a “user-centric” approach to managing personal data online. However, user-centricity can be problematic (...) when the user—the data subject—is not directly involved in transactions involving the disclosure, collection, processing, and storage of their personal data. Identity data is increasingly being generated, used and stored entirely in the networked “Cloud”, where it is under control of third parties. The paper explores possible technology solutions to ensure that individuals will be able to exercise informational self-determination in an era of network grid computing, exponential data creation, ubiquitous surveillance and rampant online fraud. The paper describes typical “Web 2.0” use scenarios, suggests some technology building blocks to protect and promote informational privacy online, and concludes with a call to develop a privacy-respective information technology ecosystem for identity management. Specifically, the paper outlines four fundamental technological approaches to help assure widespread and enduring online participation, confidence and trust in the information society. (shrink)

The commentary raises political questions about the ways in which data has been constituted as an object vested with certain powers, influence, and rationalities. We place the emergence and transformation of professional practices such as ‘data science’, ‘data journalism’, ‘data brokerage’, ‘data mining’, ‘data storage’, and ‘data analysis’ as part of the reconfiguration of a series of fields of power and knowledge in the public and private accumulation of data. Data (...) politics asks questions about the ways in which data has become such an object of power and explores how to critically intervene in its deployment as an object of knowledge. It is concerned with the conditions of possibility of data that involve things, language, and people that together create new worlds. We define ‘data politics’ as both the articulation of political questions about these worlds and the ways in which they provoke subjects to govern themselves and others by making rights claims. We contend that without understanding these conditions of possibility – of worlds, subjects and rights – it would be difficult to intervene in or shape data politics if by that it is meant the transformation of data subjects into data citizens. (shrink)

As the world keeps advancing, the need for automated interconnected devices has started to gain significance; to cater to the condition, a new concept Internet of Things has been introduced that revolves around smart devicesʼ conception. These smart devices using IoT can communicate with each other through a network to attain particular objectives, i.e., automation and intelligent decision making. IoT has enabled the users to divide their household burden with machines as these complex machines look after the environment variables (...) and control their behavior accordingly. As evident, these machines use sensors to collect vital information, which is then the complexity analyzed at a computational node that then smartly controls these devicesʼ operational behaviors. Deep learning-based guessing attack protection algorithms have been enhancing IoT security; however, it still has a critical challenge for the complex industries’ IoT networks. One of the crucial aspects of such systems is the need to have a significant training time for processing a large dataset from the networkʼs previous flow of data. Traditional deep learning approaches include decision trees, logistic regression, and support vector machines. However, it is essential to note that this convenience comes with a price that involves security vulnerabilities as IoT networks are prone to be interfered with by hackers who can access the sensor/communication data and later utilize it for malicious purposes. This paper presents the experimental study of cryptographic algorithms to classify the types of encryption algorithms into the asymmetric and asymmetric encryption algorithm. It presents a deep analysis of AES, DES, 3DES, RSA, and Blowfish based on timing complexity, size, encryption, and decryption performances. It has been assessed in terms of the guessing attack in real-time deep learning complex IoT applications. The assessment has been done using the simulation approach and it has been tested the speed of encryption and decryption of the selected encryption algorithms. For each encryption and decryption, the tests executed the same encryption using the same plaintext for five separate times, and the average time is compared. The key size used for each encryption algorithm is the maximum bytes the cipher can allow. To the comparison, the average time required to compute the algorithm by the three devices is used. For the experimental test, a set of plaintexts is used in the simulation—password-sized text and paragraph-sized text—that achieves target fair results compared to the existing algorithms in real-time deep learning networks for IoT applications. (shrink)

Recent large-scale personal data loss incidents highlighted the need for public bodies to more securely handle confidential data. We surveyed trainees from all specialties in the Welsh Deanery for their knowledge and practice. All registered trainees were invited to participate in an online anonymised survey. There were 880 completed and non-duplicated responses (52.9% response rate). Responses were analysed using Microsoft Access. Over 40% (388/880 (44.1%)) did not use formal guidelines on storage or disposal of confidential data. (...) The majority appeared to dispose of confidential paper documents securely, that is, using shredders and white shredder bags. However, there were significant numbers of unmarked responses. Clinical documents, such as theatre lists, were taken home by 281/880 (31.9%) of trainees. The majority secured their computers (569/871 (65.3%)) by either not keeping patient identifiable data on them or using encryption. However, 302/871 (34.7%) did not adequately secure their computers. The surgical and anaesthetic specialties were least aware of formal confidentiality guidelines (95/178 (53.4%)) and 52/102 (51.0%) respectively) and least secured their computers (106/178 (59.6%) and 63/102 (61.8%) respectively). Education is needed to improve knowledge and practice of confidential data handling. This may be delivered through workshops during induction programmes or as part of European Computer Driving Licence (ECDL) modules. Training is especially indicated for the surgical and anaesthetic specialties. (shrink)

Abstract: Networking is one of the most important areas currently used for data transfer and enterprise management. It also includes the security aspect that enables us to protect our network to prevent hackers from accessing the organization's data. In this paper, we would like to learn what the network is and how it works. And what are the basics of the network since its emergence and know the mechanism of action components. After reading this paper (...) - even if you do not have a general background on networking - you will be able to manage your own network and be able to distribute and control your ip. (shrink)

As we move our social institutions from paper and ink based operations to the electronic medium, we invisibly create a type of surveillance society, a panopticon society. It is not the traditional surveillance society in which government officials follow citizens around because they are concerned about threats to the political order. Instead it is piecemeal surveillance by public and private organizations. Piecemeal though it is, It creates the potential for the old kind of surveillance on an even grander scale. The (...) panopticon is the prison environment described by Foucault in which prison cells are arranged in a large circle with the side facing the inside of the circle open to view. The guard tower is placed in the middle of the circle so that guards can see everything that goes on in every cell. When we contemplate all the electronic data that is now gathered about each of us as we move through our everyday lives --- intelligent highway systems, consumer transactions, traffic patterns on the internet, medical records, financial records, and so on --- there seems little doubt that we are moving into a panopticon. The social issues that arise from this are too numerous to detail here, but data retention is an important part of it. In the paper-and-ink world, documents are filed, files are boxed, boxes are put away or thrown away. The capacity for data retrieval and manipulation is, thereby, limited by the sheer difficulty and cost of storing, finding, searching, and manipulating large numbers of paper files. This inconvenience functions as a mechanism whereby the system forgets past information, not unlike the way we ourselves forget. However, the story is very different in the digital world; digital information is easy to store, easy to search and manipulate, and inexpensive to keep over extensive periods of time. Digitalized information systems tend, therefore, to collect extensive ancillary information and to retain this information indefinitely. Such lack of forgetfulness is likely to hamper the ability of individuals to shed their past, and start over with a clean slate. Concerns about data retention were expressed in the early literature on the social impact of computing, but for the most part the issue has dropped from sight. Rarely, has the social good of discarding accumulated personal data been addressed. In this paper, we want to make the case by examining diverse cases in which retention of information by either business or governmental institutions hinders the ability of individuals to start over or to act autonomously. We hope our argument for the good of forgetfulness will challenge the standard framework in which such issues have traditionally been debated. The privacy debate exemplifies the traditional framework insofar as it has been characterized as involving an inherent tension between, on the one hand, the needs of organizations and institutions for more accurate and efficient information systems so as to further their goals and, on the other hand, the desire of individuals to have information about them kept private. Regan argues against this framing of the privacy issue in favor of one that recognizes the social importance of personal privacy. We will examine the non-forgetfulness of information systems as a problem threatening not just individual interests but social good as well. Cryptography is often cited as the technology that will give us privacy and mediate against surveillance. One of the uses of cryptography, encryption, will allow us, some hope, to create confidentiality and relationships of trust that will facilitate many of the social arrangements we now have and perhaps make them even more secure than they are now. Electronic cash, for example, could be created in such a form that it would have the anonymity associated now with hard cash Others are less optimistic of the potential for cryptography to re-create relationships of trust in the new medium. One important point that already seems clear is that even if encryption technology will protect the confidentiality and integrity of electronic transactions and data, it will NOT stop the observation of traffic patterns on networks. This seems an important distinction to put on the table. Our patterns of communication will continue to be available, no matter what is encrypted, and an amazing amount of information can be gleaned from this data. In a sense, it means content integrity but no anonymity. This will indubitably impact how we interact and with whom we interact. (shrink)

Mobile applications and socio-sexual networking websites are used by outreach workers to respond synchronously to questions and provide information, resources, and referrals on sexual health and STI/HIV prevention, testing, and care to gay, bisexual and other men who have sex with men. This exploratory study examined ethical issues identified by online outreach workers who conduct online sexual health outreach for GB2M. Semi-structured individual interviews were conducted between November 2013 and April 2014 with online providers and managers to explore the benefits, (...) challenges, and ethical implications of delivering online outreach services in Ontario, Canada. Interviews were digitally recorded and transcribed verbatim. Thematic analyses were conducted, and member-checking, analyses by multiple coders, and peer debriefing supported validity and reliability. Four themes emerged on the ethical queries of providing online sexual health outreach for GB2M: managing personal and professional boundaries with clients; disclosing personal or identifiable information to clients; maintaining client confidentiality and anonymity; and security and data storage measures of online information. Participants illustrated familiarity with potential ethical challenges, and discussed ways in which they seek to mitigate and prevent ethical conflict. Implications of this analysis for outreach workers, researchers, bioethicists, and policy-makers are to: understand ethical complexities associated with online HIV prevention and outreach for GB2M; foster dialogue to recognize and address potential ethical conflict; and identify competencies and skills to mitigate risk and promote responsive and accessible online HIV outreach. (shrink)

Based on cloud computing and statistics theory, this paper proposes a reasonable analysis method for big data of film and television. The method selects Hadoop open source cloud platform as the basis, combines the MapReduce distributed programming model and HDFS distributed file storage system and other key cloud computing technologies. In order to cope with different data processing needs of film and television industry, association analysis, cluster analysis, factor analysis, and K-mean + association analysis (...) algorithm training model were applied to model, process, and analyze the full data of film and TV series. According to the film type, producer, production region, investment, box office, audience rating, network score, audience group, and other factors, the film and television data in recent years are analyzed and studied. Based on the study of the impact of each attribute of film and television drama on film box office and TV audience rating, it is committed to the prediction of film and television industry and constantly verifies and improves the algorithm model. (shrink)

Networks for the exchange and/or sharing of genetic data are developing in many countries. We focus here on the situations in the US and France. We highlight some recent and remarkable differences between these two countries concerning the mode of access to, and the storage and use of genetic data, particularly as concerns two-sided markets and dynamic consent or dynamic electronic informed consent. This brief overview suggests that, even though the organization and function of these two-sided markets (...) remain open to criticism, dynamic e-IC should be more widely used, especially in France, if only to determine its real effectiveness. (shrink)

The technical details of Internet architecture affect social debates about privacy and autonomy, intellectual property, cybersecurity, and the basic performance and reliability of Internet services. This paper explores one method for practicing anticipatory ethics in order to understand how a new infrastructure for the Internet might impact these social debates. This paper systematically examines values expressed by an Internet architecture engineering team—the Named Data Networking project—based on data gathered from publications and internal documents. Networking engineers making technical choices (...) also weigh non-technical values when working on Internet infrastructure. Analysis of the team’s documents reveals both values invoked in response to technical constraints and possibilities, such as efficiency and dynamism, as well as values, including privacy, security and anonymity, which stem from a concern for personal liberties. More peripheral communitarian values espoused by the engineers include democratization and trust. The paper considers the contextual and social origins of these values, and then uses them as a method of practicing anticipatory ethics: considering the impact such priorities may have on a future Internet. (shrink)

Online social networks have rapidly become a prominent and widely used service, offering a wealth of personal and sensitive information with significant security and privacy implications. Hence, OSNs are also an important—and popular—subject for research. To perform research based on real-life evidence, however, researchers may need to access OSN data, such as texts and files uploaded by users and connections among users. This raises significant ethical problems. Currently, there are no clear ethical guidelines, and researchers may end up performing (...) ethically questionable research, sometimes even when more ethical research alternatives exist. For example, several studies have employed “fake identities” to collect data from OSNs, but fake identities may be used for attacks and are considered a security issue. Is it legitimate to use fake identities for studying OSNs or for collecting OSN data for research? We present a taxonomy of the ethical challenges facing researchers of OSNs and compare different approaches. We demonstrate how ethical considerations have been taken into account in previous studies that used fake identities. In addition, several possible approaches are offered to reduce or avoid ethical misconducts. We hope this work will stimulate the development and use of ethical practices and methods in the research of online social networks. (shrink)

Meeting 5G high bandwidth rates, ultra-low latencies, and high reliabilities requires of network infrastructures that automatically increase/decrease the resources based on their customers’ demand. An autonomous and dynamic management of a 5G network infrastructure represents a challenge, as any solution must account for the radio access network, data plane traffic, wavelength allocation, network slicing, and network functions’ orchestration. Furthermore, federation among administrative domains (ADs) must be considered in the network management. Given the increased (...) dynamicity of 5G networks, artificial intelligence/machine learning (AI/ML) solutions are strong candidates able to learn, and take quick provisioning decisions upon fast changes in network conditions. Therefore, this chapter presents an analysis of the state-of-the-art solutions for 5G networks’ management, where AI/ML solutions are discussed and compared with traditional methods. Additionally, the chapter provides a technology overview of both standards, and existing solutions regarding the 5G network management, and directions toward the integration of AI/ML in 5G networks. (shrink)

The impact of Online Social Networks on human lives is foreseen to be very large with unprecedented amount of data and users. OSN users share their ideas, photos, daily life events, feelings and news. Since OSNs’ security and privacy challenges are more potential than ever before, it is necessary to enhance the protection and filtering approaches of OSNs contents. This paper explores OSNs’ threats and challenges, and categorize them into: account-based, URL-based and content-based threats. In addition, we analyze the (...) existing protection methods and highlight their limitations and weaknesses. Based on that, we propose a comprehensive, user-level, proactive and real-time OSNs’ protection system, called Hybrid Real-time Social Networks Protector. HRSP has three components; a user-level security protocol and two classification models. The protocol defines a structure for OSN’s cryptographic services, including encryption, access control and users’ authentication. The classification models employ machine learning, black lists, white lists and users’ feedback, in order to classify URLs into: Benign, Risk and Inappropriate classes, and contents into: Benign, Hate speech and Inappropriate classes. We constructed two data sets of 150,000 URLs and 22,000 tweets to build and test the two classification models. Results show an overall accuracy of 93.2% for the URL model and 84.4% for the content model, while the protocol implementation produces compatible size and time overhead. The components of HRSP are integrated and have compatible design with OSN platforms. (shrink)

This paper researches and analyzes the evaluation of the competitiveness of ice and snow tourism, uses the improved fuzzy neural network algorithm to process the system flow diagram of ice and snow tourism development through the function and characteristics of the power system of ice and snow tourism, and finally selects more than 40 indicators of the three subsystems of resources, economy, and culture. Based on the construction of cloud fuzzy neural network model, the above method is (...) used for experimental comparison analysis, and experiments are conducted through University of California Irvine dataset and engineering examples to compare with the traditional cloud model, fuzzy neural network, and BP neural network to analyze the operation efficiency, accuracy rate, and several rules of the algorithm. Through the experimental comparative analysis, the cloud fuzzy neural network can fully take into account the randomness and fuzziness of the data, optimize the generation of cloud rules, avoid multidimensional rule disasters, and ensure the operational efficiency of the algorithm; the accuracy rate of the algorithm is improved relative to that of the traditional technology, and it applies to a variety of datasets. And the software is used to test the ice and snow tourism industry system dynamics model to realize the correctness and robustness testing of the model. After the constructed model can reflect the real situation within the error range, the final policy simulation of the model is carried out. (shrink)

Coordination of a power system with the phasor measurement devices in real time on the load and generation sides is carried out within the context of smart grid studies. Power systems equipped with information systems in a smart grid pace with external security threats. Developing a smart grid which can resist against cyber threats is considered indispensable for the uninterrupted operation. In this study, a two-way secure communication methodology underpinned by a chaos-based encryption algorithm for PMU devices is proposed. The (...) proposed system uses the IEEE-14 busbar system on which the optimum PMU placement has been installed. The proposed hyperchaotic system-based encryption method is applied as a new security methodology among PMU devices. The success of results is evaluated by the completeness of data exchange, durations, the complexity of encryption-decryption processes, and strength of cryptography using a microcomputer-based implementation. The results show that the proposed microcomputer-based encryption algorithms can be directly embedded as encryption hardware units into PMU and PDC devices which have very fast signal processing capabilities taking into considerations the acceptable delay time for power system protection and measuring applications and quality metering applications which is 2 ms and 10 ms, respectively. While proposed algorithms can be used in TCP or UDP over IP-based IEEE C37.118, IEC 61850, and IEC 61850-90-5 communication frameworks, they can also be embedded into electronic cards, smartcards, or smart tokens which are utilized for authentication among smart grid components. (shrink)

This paper explores the history of a unique assemblage of researchers in the geodetic and allied sciences organised at Ohio State University (OSU) in 1947 at the beginning of the Cold War. From about 1950 to 1970, the OSU geodetic sciences group was the most significant group of geodetic researchers in the world. Funded almost entirely by military and intelligence agencies, they pioneered the technologies, organised the research initiatives, ordered the data sets, and trained the generation of geodesists who (...) eventually created the Cold War Figure of the Earth to both prosecute and prevent global nuclear war. They devised elaborate mechanisms to pursue in secrecy and isolation research that had hitherto been performed collaboratively and globally. They invented methods to maintain professional associations and protocols, both to distribute-and disguise-the fruits of their geodetic research. In accomplishing this, their work also undermined the basic hypothesis of isostasy that had been foundational to geodesy for the previous century.Fundamental progress in the geosciences and military and intelligence directives were inextricably linked during the Cold War, although the extent of their convergence has been masked by the security protocols organised to disguise it. With the declassification of key programmes underway, it is now both possible and necessary to substantially revise the history of Cold War-era geosciences and their associated technologies. (shrink)

This edited collection brings together a series of interdisciplinary contributions in the field of Information Technology Law. The topics addressed in this book cover a wide range of theoretical and practical legal issues that have been created by cutting-edge Internet technologies, primarily Big Data, the Internet of Things, and Cloud computing. Consideration is also given to more recent technological breakthroughs that are now used to assist, and - at times - substitute for, human work, such as automation, robots, (...) sensors, and algorithms. The chapters presented in this edition address these issues from the perspective of different legal backgrounds. The first part of the book discusses some of the shortcomings that have prompted legislators to carry out reforms with regard to privacy, data protection, and data security. Notably, some of the complexities and salient points with regard to the new European General Data Protection Regulation (EU GDPR) and the new amendments to the Japan's Personal Information Protection Act (PIPA) have been scrutinized. The second part looks at the vital role of Internet intermediaries (or brokers) for the proper functioning of the globalized electronic market and innovation technologies in general. The third part examines an electronic approach to evidence with an evaluation of how these technologies affect civil and criminal investigations. The authors also explore issues that have emerged in e-commerce, such as Bitcoin and its blockchain network effects. The book aims to explain, systemize and solve some of the lingering legal questions created by the disruptive technological change that characterizes the early twenty-first century. (shrink)

Scalability, efficiency, and security had been a persistent problem over the years in data mining, several techniques had been proposed and implemented but none had been able to solve the problem of scalability, efficiency and security from cloud computing. In this research, we solve the problem scalability, efficiency and security in data mining over cloud computing by using a restful web services and combination of different technologies and tools, our model was trained by using different machine (...) learning algorithm, and finally using different validation and cross-validation methods to compare and validate our results. We build, train, test and deploy our model by restful API services which can be called through an endpoint, and with very high accuracy and huge success. (shrink)

The rapidly advancing field of brain-computer (BCI) and brain-to-brain interfaces (BBI) is stimulating interest across various sectors including medicine, entertainment, research, and military. The developers of large-scale brain-computer networks, sometimes dubbed ‘Mindplexes’ or ‘Cloudminds’, aim to enhance cognitive functions by distributing them across expansive networks. A key technical challenge is the efficient transmission and storage of information. One proposed solution is employing blockchain technology over Web 3.0 to create decentralised cognitive entities. This paper explores the potential of a decentralised (...) web for coordinating large brain-computer constellations, and its associated benefits, focusing in particular on the conceptual and ethical challenges this innovation may pose pertaining to (1) Identity, (2) Sovereignty (encompassing Autonomy, Authenticity, and Ownership), (3) Responsibility and Accountability, and (4) Privacy, Safety, and Security. We suggest that while a decentralised web can address some concerns and mitigate certain risks, underlying ethical issues persist. Fundamental questions about entity definition within these networks, the distinctions between individuals and collectives, and responsibility distribution within and between networks, demand further exploration. (shrink)

There is a tendency in decision‐making research to treat uncertainty only as a problem to be overcome. But it is also a feature that can be leveraged, particularly in social interaction. Comparing the behavior of profitable and unprofitable poker players, we reveal a strategic use of information processing that keeps decision makers unpredictable. To win at poker, a player must exploit public signals from others. But using public inputs makes it easier for an observer to reconstruct that player's strategy and (...) predict his or her behavior. How should players trade off between exploiting profitable opportunities and remaining unexploitable themselves? Using a recent multivariate approach to information theoretic data analysis and 1.75 million hands of online two‐player No‐Limit Texas Hold'em, we find that the important difference between winning and losing players is not in the amount of information they process, but how they process it. In particular, winning players are better at integrative information processing—creating new information from the interaction between their cards and their opponents’ signals. We argue that integrative information processing does not just produce better decisions, it makes decision‐making harder for others to reverse engineer, as an expert poker player's cards act like the private key in public‐key cryptography. Poker players encrypt their reasoning with the way they process information. The encryption function of integrative information processing makes it possible for players to exploit others while remaining unexploitable. By recognizing the act of information processing as a strategic behavior in its own right, we offer a detailed account of how experts use endemic uncertainty to conceal their intentions in high‐stakes competitive environments, and we highlight new opportunities between cognitive science, information theory, and game theory. (shrink)

Purpose This study aims to ascertain the impact of data collecting awareness on perceived information security concerns and information-sharing behavior on social networking sites. Design/methodology/approach Based on communication privacy management theory, the study forecasted the relationship between information-sharing behavior and awareness of data collecting purposes, data collection tactics and perceived security risk using structural equation modeling analysis and one-way ANOVA. The sample size of 521 young social media users in Vietnam, ages 18 to 34, was made up (...) of 26.7% men and 73.3% women. When constructing the questionnaire survey method with lone source respondents, the individual’s unique awareness and experiences with using online social networks (OSNs) were taken into account. Findings The results of the investigation demonstrate a significant relationship between information-sharing and awareness of data collecting, perceptions of information security threats and behavior. Social media users have used OSN privacy settings and paid attention to the sharing restriction because they are concerned about data harvesting. Research limitations/implications This study was conducted among young Vietnamese social media users, reflecting specific characteristics prevalent in the Vietnamese environment, and hence may be invalid in other nations’ circumstances. Practical implications Social media platform providers should improve user connectivity by implementing transparent privacy policies that allow users to choose how their data are used; have clear privacy statements and specific policies governing the use of social media users’ data that respect users’ consent to use their data; and thoroughly communicate how they collect and use user data while promptly detecting any potential vulnerabilities within their systems. Originality/value The authors ascertain that the material presented in this manuscript will not infringe upon any statutory copyright and that the manuscript will not be submitted elsewhere while under Journal of Information, Communication and Ethics in Society review. (shrink)

An astonishingly diverse biomolecular circuitry orchestrates the functioning machinery underlying every living cell. These biomolecules and their circuits have been engineered not only for various industrial applications but also to perform other atypical functions that they were not evolved for—including computation. Various kinds of computational challenges, such as solving NP‐complete problems with many variables, logical computation, neural network operations, and cryptography, have all been attempted through this unconventional computing paradigm. In this review, we highlight key experiments across three different (...) ‘‘eras’’ of molecular computation, beginning with molecular solutions, transitioning to logic circuits and ultimately, more complex molecular networks. We also discuss a variety of applications of molecular computation, from solving NP‐hard problems to self‐assembled nanostructures for delivering molecules, and provide a glimpse into the exciting potential that molecular computing holds for the future. Also see the video abstract here: https://youtu.be/9Mw0K0vCSQw. (shrink)

PurposeThe purpose of this paper is to analyze written reflections of final year computing students taking a professionalism module that covered the social, legal, professional and ethical aspects of computing. Society's dependence on computers makes it essential that computing students, whose future work may involve the analysis, storage and security of private data, are capable of identifying ethical issues and of making reflective moral judgements. The capacity to make moral judgements has been linked to an ability to reflect, (...) so the aim of this research was twofold, to investigate students' familiarity with the concepts the module covered and their reflective ability.Design/methodology/approachThe research takes the form of an exploratory case study with qualitative data from written reflections examined using NVivo and word cloud analysis.FindingsThe students found it difficult to write reflectively and the majority of their reflections were either descriptive writing or descriptive reflection which considered events from one perspective. Awareness of the topics covered by the module appeared to be low prior to taking the module.Research limitations/implicationsThis research identifies the need to develop students' reflective skills and professional awareness in order to enhance their professional performance.Practical implicationsReflective writing and concepts such as profession and ethics need to be included throughout computing degrees, not just in a final year module. As students are strategic learners these topics also need to be covered in enough depth at each level so they are assessed and treated seriously by students.Social implicationsGiven the ubiquitous nature of computers and society's high level of dependence on them it is essential that students' moral reasoning skills are developed throughout their course, so on graduation they are capable of ethical thinking and can make reflective moral judgements.Originality/valueNo other qualitative research was found which covered this area and no research was found which raised these issues. (shrink)

Internet-of-Things (IoT) creates a significant impact in spectrum sensing, information retrieval, medical analysis, traffic management, etc. These applications require continuous information to perform a specific task. At the time, various intermediate attacks such as jamming, priority violation attacks, and spectrum poisoning attacks affect communication because of the open nature of wireless communication. These attacks create security and privacy issues while making data communication. Therefore, a new method autoencoder deep neural network (AENN) is developed by considering exploratory, evasion, causative, (...) and priority violation attack. The created method classifies the transmission outcomes used to predict the transmission state, whether it is jam data transmission or sensing data. After that, the sensing data is applied for network training that predicts the intermediate attacks. In addition to this, the channel access algorithm is used to validate the channel for every access that minimizes unauthorized access. After validating the channel according to the neural network, data have been transmitted over the network. The defined process is implemented, and the system minimizes different attacks on various levels of energy consumption. The effectiveness of the system is implemented using TensorFlow, and the system ensures the 99.02% of detection rate when compared with other techniques. (shrink)

The article deals with the algorithm of encrypting graphic information using transformation matrixes. It presents the actions that can be done with the image. The article also gives algorithms for forming matrixes that are created with the use of random processes. Examples of matrixes and encryption results are shown. Calculations of the analysis of combinations and conclusions to them are carried out. The article shows the possibilities and advantages of this image encryption algorithm. The proposed algorithm will allow to transmit (...) encrypted information through open communication channels. The algorithm uses all possible actions that can be done with the image, namely: image resizing, adding redundant elements to the image, changing the location of the pixels, changing the brightness of the image pixels, inverting the image pixels, changing the colours of the images pixels. A randomized approach to matrix formation will make it impossible to use neural systems. The algorithm of the implementation of writing encryption code is rather simple. It is not possible to decrypt the image without a key as the number of possible combinations is extremely large. This algorithm can be used in the military, intelligence, information security. Encryption does not require significant computing or RAM resources. This algorithm can be implemented in WEB-technology and in mobile applications, it has no recursive functions and loop in loop. The algorithm hides the image size, which in turn adds extra protection. Redundant elements will not allow neural networks to compare pixels. Changing colors, changing brightness, inversion by random processes will not allow neural networks to find the decryption function. The article considers an image encryption algorithm that will give a possibility to generate a key. The key will be a set of two-dimensional arrays formed in a randomized manner. A randomized approach to matrix formation will make it impossible to use neural systems. The algorithm uses all possible actions that can be done with the image, namely: Image resizing. Adding redundant elements to the image. Changing the location of the pixels. Changing the brightness of the image pixels. Inverting the image pixels. Changing the colours of the images pixels. The pixel positioning matrix gives us! combinations. The pixel brightness change matrix gives us 8 *! combinations. The pixel inversion matrix gives us 8 *! combinations. The pixel colour change matrix gives us 6 *! Combinations. The total number of combinations N is equal to: It is not possible to decrypt the image without a key as the number of possible combinations is extremely large. The algorithm of the implementation of writing encryption code is rather simple. This algorithm can be used in the military, intelligence, information security. The advantage of this algorithm is the fact that the encrypted image can be transmitted through open chann. (shrink)

This paper adopts Hadoop to build and test the storage and retrieval platform for painting resources. This paper adopts Hadoop as the platform and MapReduce as the computing framework and uses Hadoop Distributed Filesystem distributed file system to store massive log data, which solves the storage problem of massive data. According to the business requirements of the system, this paper designs the system according to the process of web text mining, mainly divided into log data (...) preprocessing module, log data storage module, log data analysis module, and log data visualization module. The core part of the system is the log data analysis module. The analysis of search keywords ranking, Uniform Resource Locator, and user click relationship, URL ranking, and other dimensions are realized through data statistical analysis, and Canopy coarse clustering is performed first according to search keywords, and then K-means clustering is used for the results after Canopy clustering, and the calculation of cosine similarity is adopted to realize the grouping of users and build user portrait. The Hadoop development environment is installed and deployed, and functional and performance tests are conducted on the contents implemented in this system. The constructed private cloud platform for remote sensing image data can realize online retrieval of remote sensing image metadata and fast download of remote sensing image data and solve the problems in storage, data sharing, and management of remote sensing image data to a certain extent. (shrink)

The last decade has seen rise in technologies that allow humans to send and receive intimate touch across long distances. Drawing together platform studies, digital intimacy studies, phenomenology of touch, and ethics of technology, we argue that these new haptic communication devices require specific ethical consideration of consent. The paper describes several technologies, including Kiiroo teledildonics, the Kissenger, the Apple Watch, and Hey Bracelet, highlighting how the sense of touch is used in marketing to evoke a feeling of connection within (...) the digital sphere. We then discuss the ambiguity of skin-to-skin touch and how it is further complicated in digital touch by remediation through platforms, companies, developers, manufacturers, cloud storage sites, the collection and use of data, research, satellites, and the internet. Lastly, we raise concerns about how consent of data collection and physical consent between users will be determined, draw on examples in virtual reality and sex-robotics, and ultimately arguing for further interdisciplinary research into this area. (shrink)

In order to correct the deficiencies of intrusion detection technology, the entire computer and network security system are needed to be more perfect. This work proposes an improved k-means algorithm and an improved Apriori algorithm applied in data mining technology to detect network intrusion and security maintenance. The classical KDDCUP99 dataset has been utilized in this work for performing the experimentation with the improved algorithms. The algorithm’s detection rate and false alarm rate are compared with the experimental (...) data before the improvement. The outcomes of proposed algorithms are analyzed in terms of various simulation parameters like average time, false alarm rate, absolute error as well as accuracy value. The results show that the improved algorithm advances the detection efficiency and accuracy using the designed detection model. The improved and tested detection model is then applied to a new intrusion detection system. After intrusion detection experiments, the experimental results show that the proposed system improves detection accuracy and reduces the false alarm rate. A significant improvement of 90.57% can be seen in detecting new attack type intrusion detection using the proposed algorithm. (shrink)

With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy-preserving cryptosystem is necessary. Such a solution relies on chaos encryption algorithms over standard cryptographic methods that possess multistage encryption levels, including high speed, high security, low compute overheads, and procedural power, among other characteristics. In this work, a secure image encryption scheme (...) is proposed using linear feedback shift register and chaos-based quantum chaotic map. The focus of the scheme is mainly dependent on the secret keys from the input of the algorithm. The threat landscape, the statistical test analysis, along critical comparisons with other schemes indicate that the presented algorithm is significantly secure and is resistant to a wide range of different attacks such as differential and statistical attacks. The proposed method has sufficiently higher sensitivity and security when compared to existing encryption algorithms. Several security parameters validated the security of proposed work such as correlation coefficient analyses among the neighboring pixels, entropy, the number of pixels change rate, unified average change intensity, mean square error, brute force, key sensitivity, and peak signal to noise ratio analyses. The randomness of the ciphers produced by the proposed technique is also passed through NIST-800-22. The results of NIST indicate that the ciphers are highly random and do not produce any type of periodicity or pattern. (shrink)

Moving away from simple data sharing within the science community towards cross-organizational collaboration scenarios significantly increased challenges related to security and privacy. They need to be addressed in order to make cross-organizational applications such as collaborative working environments a business proposition within communities such as eHealth, construction or manufacturing. Increasingly distributed scenarios where many different types of services need to be combined in order to implement semantically enriched business processes demand new approaches to security within such dynamic Virtual Organizations. (...) The allocation of access rights need to be possible in an easy and controlled way in order to allow inexperienced users to maintain the information and ensure compliance e.g. with legal and privacy related regulations. In this paper the focus is how security concepts originating from the Grid domain have been applied for collaborative working environments. The chosen scenarios are a Virtual Laboratory for Infectious Diseases (ViroLab) and different collaborative environments from the engineering domain as defined within the CoSpaces project. The requirements from these scenarios are analyzed and a security model enabling such dynamic, secure and trustworthy collaborations is presented. (shrink)

For a better detection in Network information security monitoring system, the author proposes a method based on adaptive depth detection. A deep belief network was designed and implemented, and the intrusion detection system model was combined with a support vector machine. The data set adopts the NSL-KDD network communication data set, and this data set is authoritative in the security field. Redundant cleaning, data type conversion, normalization, and other processing operations are performed on (...) the data set. Using the data conversion method based on the probability mass function probability mass function coding, a standard data set with low redundancy and low dimensionality can be obtained. Research indicates that when the batch size reaches 64, the accuracy of the test set reaches its maximum value. As the batch size increases, the accuracy first increases and then decreases. When the batch size continues to increase, the model will inevitably fall into the local optimal state, resulting in the degradation of the detection performance of the system. In terms of the false alarm rate, the DBN-SVM model is also the highest; however, it is only 10.73%. Under the premise of increasing the detection rate, the false alarm rate is improved; for the overall detection performance of the model, it is within an acceptable range. In terms of accuracy, the DBN-SVM model also scored the highest. The accuracy rate is the ratio of normal and correct classification for intrusion detection. It can explain the detection ability of the model. In summary, the overall detection ability of the DBN-SVM model is the best. The good classification ability to use SVM is proved, and the classification of low-dimensional features is expected to increase the detection rate of the system. (shrink)