Journal of Political Philosophy, EarlyView.

Malware is a sophisticated, malicious, and sometimes unidentifiable application on the network. The classifying network traffic method using machine learning shows to perform well in detecting malware. In the literature, it is reported that this good performance can depend on a reduced set of network features. This study presents an empirical evaluation of two statistical methods of reduction and selection of features in an Android network traffic dataset using six supervised algorithms: Naïve Bayes, support vector machine, multilayer perceptron neural network, (...) decision tree, random forest, and K-nearest neighbors. The principal component analysis and logistic regression methods with p value were applied to select the most representative features related to the time properties of flows and features of bidirectional packets. The selected features were used to train the algorithms using binary and multiclass classification. For performance evaluation and comparison metrics, precision, recall, F-measure, accuracy, and area under the curve were used. The empirical results show that random forest obtains an average accuracy of 96% and an AUC-ROC of 0.98 in binary classification. For the case of multiclass classification, again random forest achieves an average accuracy of 87% and an AUC-ROC over 95%, exhibiting better performance than the other machine learning algorithms. In both experiments, the 13 most representative features of a mixed set of flow time properties and bidirectional network packets selected by LR were used. In the case of the other five classifiers, their results in terms of precision, recall, and accuracy, are competitive with those obtained in related works, which used a greater number of input features. Therefore, it is empirically evidenced that the proposed method for the selection of features, based on statistical techniques of reduction and extraction of attributes, allows improving the identification performance of malware traffic, discriminating it from the benign traffic of Android applications. (shrink)

In orthodox quantum mechanics, it has virtually become the custom to identify properties of a physical system with operationally testable propositions about the system. The causes and consequences of this practice are explored mathematically in this paper. Among other things, it is found that such an identification imposes severe constraints on the admissible states of the physical system.

The discussion of the construction with usus est is conventionally bound up with that of opus est, and comparatively little attention has been given to the problem presented by the use of the ablative case with the former phrase. The tendency to pass lightly over this matter is due doubtless to the manifest etymological connexion between usus and utor, which leads to the assumption that the verbal noun would naturally follow the syntax of the verb.

Recent scholarship, focusing on the rapid decline of microscopy after the late 1680's, has shown that the limitations of microscopy and the ambivalent meaning of its findings led to a wide-spread sense of frustration with the new instrument. The present article tries to connect this fall from favor with the microscope's equally surprising but hitherto little noticed late rise to prominence. The crucial point is that when the microscope, more than a decade after the telescope, finally managed to arouse the (...) interest of natural philosophers, it did so as a corpuscularian tool, and as such it came to share the difficult fate of seventeenth-century corpuscularianism. The essay ends with the claim that the fall of microscopy was not only due to the failure of microscopy to corroborate corpuscularianism, but also to the changing definition of natural philosophy in the late seventeenth and early eighteenth centuries and to the separation of the domains of living matter from a physica whose recent mathematical framework excluded the organic world. (shrink)

There is an argument, well known in the history of philosophy, which makes all knowledge ultimately depend on some kind of intuitive or sensory immediacy. According to this argument, either the proposition itself is self–evident; 2 or else it can be shown to follow, with the help of a chain of intermediate links, from other propositions which are self–evident. Moreover, it is this self–evidence of immediate knowledge and only this which, again speaking traditionally, sufficiently guarantees the truth of the affirmations (...) of a science as opposed to those of various and fluctuating opinions. (shrink)