AUTOMATIC CONTROL AND COMPUTER SCIENCES最新文献

One approach to obtain a cryptographically strong encryption gamma is to use linear-feedback shift registers defined by primitive polynomials. The ability to quickly select the appropriate polynomial can provide the required degree of security of the stream cipher. Currently, primitive polynomials for sufficiently large degrees are known, but usually these are so-called sparse polynomials. To increase the correlational stability, it is necessary to be able to quickly generate new primitive polynomials of the given degrees, which is the focus of this study.

The security of recommendation systems with collaborative filtering from manipulation attacks is considered. The most common types of attacks are analyzed and identified. A modified method for detecting manipulation attacks on recommendation systems with collaborative filtering is proposed. Experimental testing and a comparison of the effectiveness of the modified method with other current methods are carried out.

This article discusses the security of implementing encryption for the Bitcoin Core cryptocurrency wallet. Particular attention is paid to aspects of the practical use of cryptographic algorithms when encrypting the wallet.dat file with a password. Practical resistance to brute-force attacks using parallel computing on GPUs is also considered. It is discovered that Bitcoin Core does not implement changing the encryption key for the user’s private keys. This implementation makes it possible to carry out a second attack on the wallet without knowing the new password, if it has already been compromised previously. Changes to encryption algorithms are also been proposed to make brute-force attacks more difficult on the GPU.

This article presents graph theory-based approaches to self-regulation of networks with adaptive network topology. These approaches are limited to networks with no node mobility—peer-to-peer and heterogeneous sensor networks, as well as industrial networks on the example of Smart Grid smart energy consumption networks. For each network type, a generalized target function is described, conditions for self-regulation are formulated, and a formal description of the process of self-regulation is provided.

This paper presents a study of the possibility of using machine learning methods to detect malicious installation files related to the type of Trojan installers and downloaders. A comparative analysis of machine learning algorithms applicable for the solution of this problem is provided: the naive Bayes classifier (NBC), random forest, and C4.5 algorithm. Machine learning models are developed using the Weka software. The most significant attributes of installation files of legitimate and Trojan programs are highlighted.

This paper discusses problems of improving network infrastructure security. A network infrastructure is developed; an access control method based on severing superfluous network connectivity between subjects and objects is proposed and assessed; and potential directions of its development are outlined. This method can be used for network segmentation.

The extraction threat to machine learning models is considered. Most contemporary methods of defense against the extraction of computational machine learning models are based on the use of a protective noise mechanism. The main disadvantage inherent in the noise mechanism is that it reduces the precision of the model’s output. The requirements for the efficient methods of protecting the machine learning models from extraction are formulated, and a new method of defense against this threat, supplementing the noise with a distillation mechanism, is presented. It is experimentally shown that the developed method provides the resistance of machine learning models to extraction threat while maintaining the quality their operating results due to the transformation of protected models into the other simplified models equivalent to the original ones.

The results of an architecture stability analysis of messaging systems with a decentralized node structure Briar and Bridgefy are presented. Mathematical models of target systems are developed and protocols for generating keys, establishing connections, and transferring data between the systems’ users are described. The key features of the architecture of messaging systems with a decentralized nodal structure are highlighted. The main classes of threats to target systems are given.

Increasing the quality indicators for identifying the information security (IS) state of individual segments of cyber-physical systems is related to processing large information arrays. A method for improving quality indicators when solving problems of identifying the IS state is proposed. Its implementation is based on the formation of individual sample segments. Analysis of the properties of these segments makes it possible to select and assign algorithms that have the best quality indicators in the current segment. Segmentation of a data sample is considered. Using real dataset data as an example, experimental values of the quality indicator for the proposed method are given for various classifiers on individual segments and the entire sample.

The isogeny graphs of supersingular curves are one of the promising mathematical structures in postquantum cryptography algorithms. However, the recently reported attack on the SIDH protocol [1] demonstrates that the isogeny graphs require a more detailed investigation when applied to real protocols. In this study, we analyze the structure of the graphs of isogenies of degree (ell > 2) and consider the set of vertices of a special type to which an attack on reconstruction of the path in the graph is applicable [7].