This paper concerns several important topics of the Symmetry journal, namely, pattern recognition, computer-aided design, diversity and similarity. We also take advantage of the symmetric and asymmetric structure of a transfer function, which is responsible to map a continuous search space to a binary search space. A new method for design of a fuzzy-rule-based classifier using metaheuristics called Gravitational Search Algorithm (GSA) is discussed. The paper identifies three basic stages of the classifier construction: feature selection, creating of a fuzzy rule base and optimization of the antecedent parameters of rules. At the first stage, several feature subsets are obtained by using the wrapper scheme on the basis of the binary GSA. Creating fuzzy rules is a serious challenge in designing the fuzzy-rule-based classifier in the presence of high-dimensional data. The classifier structure is formed by the rule base generation algorithm by using minimum and maximum feature values. The optimal fuzzy-rule-based parameters are extracted from the training data using the continuous GSA. The classifier performance is tested on real-world KEEL (Knowledge Extraction based on Evolutionary Learning) datasets. The results demonstrate that highly accurate classifiers could be constructed with relatively few fuzzy rules and features.

No abstract

No abstract

In Tomsk University of Control Systems and Radioelectronics (TUSUR) one of the main areas of research is information security. The work is carried out by a scientific group under the guidance of Professor Shelupanov. One of the directions is the development of a comprehensive approach to assessing the security of the information systems. This direction includes the construction of an information security threats model and a protection system model, which allow to compile a complete list of threats and methods of protection against them. The main directions of information security tools development are dynamic methods of biometrics, methods for generating prime numbers for data encryption, steganography, methods and means of data protection in Internet of Things (IoT) systems. The article presents the main results of research in the listed areas of information security. The resultant properties in symmetric cryptography are based on the properties of the power of the generating functions. The authors have obtained symmetric principles for the development of primality testing algorithms, as discussed in the Appendix.Symmetry 2018, 10, x FOR PEER REVIEW 3 of 33 Ported to AMR system devices, IPsec ensures mutual authentication of network devices using the IKEv2 protocol. Optionally, the network can be configured based on the EAP-PSK protocol. During configuration, the devices receive network addresses and authentication keys, at which point the execution of EAP-PSK is stopped and data is transferred via IPsec. Another option is to use pre-installed certificates on the devices. In this case, the initial configuration is done manually, but the network does not require EAP-PSK to be used.Data integrity control and encryption during transmission are provided by ESP, which is the protocol used in IPsec at the transport level. This protocol ensures the security of both the data transmitted and packet headers at the network level.This approach makes it possible to ensure reliable authentication of the AMR system devices and the security of the data to be transmitted and opens a wide range of options for the configuration of network operation; however, it cannot be used in networks with heterogeneous communication channels. The EAP-PSK-based approach offers less flexibility but is suitable for networks with heterogeneous communication channels. For an AMR system, a list of threats was proposed based on the developed methodology. Threats to the confidentiality of the system are threats related to the collection of information about the system. This can be a list of devices, software versions, authentication data, access control policies, network addresses, interaction protocols, etc. Threats to the integrity of the automated system for commercial accounting are: substitution of an object, substitution of a communication channel, deletion of an object, destruction of a communication channel, addition of an unauthorized object, creation of an unauthorized communication channel; change of communication channel or object settings...

Almost all industrial internet of things (IIoT) attacks happen at the data transmission layer according to a majority of the sources. In IIoT, different machine learning (ML) and deep learning (DL) techniques are used for building the intrusion detection system (IDS) and models to detect the attacks in any layer of its architecture. In this regard, minimizing the attacks could be the major objective of cybersecurity, while knowing that they cannot be fully avoided. The number of people resisting the attacks and protection system is less than those who prepare the attacks. Well-reasoned and learning-backed problems must be addressed by the cyber machine, using appropriate methods alongside quality datasets. The purpose of this paper is to describe the development of the cybersecurity datasets used to train the algorithms which are used for building IDS detection models, as well as analyzing and summarizing the different and famous internet of things (IoT) attacks. This is carried out by assessing the outlines of various studies presented in the literature and the many problems with IoT threat detection. Hybrid frameworks have shown good performance and high detection rates compared to standalone machine learning methods in a few experiments. It is the researchers’ recommendation to employ hybrid frameworks to identify IoT attacks for the foreseeable future.