Handoff Security Using Artificial Neural Networks in Cognitive Radio Networks / G. Ratkhor, N. Dzhaglan, S. Garg [et al.]

Уровень набора: IEEE Internet of Things MagazineАльтернативный автор-лицо: Ratkhor, G., Gitandzhali;Dzhaglan, N., Navin;Garg, S., Sakhil;Chzhun Choy Bong;Dzhayakodi (Jayakody) Arachshiladzh, D. N. K., specialist in the field of electronics, Professor of Tomsk Polytechnic University, 1983-, Dushanta Nalin KumaraКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет, Инженерная школа информационных технологий и робототехники, Научно-образовательный центр "Автоматизация и информационные технологии"Язык: английский.Страна: .Резюме или реферат: The dynamic and highly open nature of cognitive radio (CR) makes cognitive communication extremely vulnerable to various malicious activities resulting from several security threats. Although extensive efforts have been devoted to the research and development of spectrum sharing systems, security issues are not well addressed for the cognitive radio network (CRN). The sensing and dynamic access mechanism invites a number of security threats at the physical layer in the CRN. In particular, during the handoff of cognitive users (CUs), a malicious user (MU) may perform new types of attacks specific to handoff CU (HCU). In this article, we present a new type of security threat, called a cognitive user emulation attack (CUEA), which occurs during the spectrum handoff in a CRN. In CUEA, an attacker aims to block the legitimate users (i.e., HCUs) from accessing the new and unused channels by mimicking them. The problem comes from the fact that during the delay in the spectrum handoff process, when users vacate to occupy an unused channel, the MU can behave as a legitimate HCU to block the user from occupying the unused channel.; Consequently, the MU can affect the data transmission process and degrade the network performance. To address this problem, we first present a detailed investigation of the security threats specific to CUs that occur during their mobility. Also, we discuss the problems for different communication networks (i.e., centralized and decentralized), where CUEA takes place with different attacking strategies. Further, we examine the challenges of CUEA in different networks by classifying them into a range of open issues. Moreover, we illustrate the need for artificial intelligence techniques for making efficient autonomous decisions to improve the network performance in terms of throughput, energy consumption, and delivery delay. We also discuss the prospective challenges of the primary user emulation attack and future research directions..Примечания о наличии в документе библиографии/указателя: [References: 15 tit.].Аудитория: .Тематика: труды учёных ТПУ | электронный ресурс | emulation | blockchain | delays | security | cognitive radio | artificial intelligence | блокчейн | безопасность | искусственный интеллект | искусственные нейронные сети | радиосети Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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[References: 15 tit.]

The dynamic and highly open nature of cognitive radio (CR) makes cognitive communication extremely vulnerable to various malicious activities resulting from several security threats. Although extensive efforts have been devoted to the research and development of spectrum sharing systems, security issues are not well addressed for the cognitive radio network (CRN). The sensing and dynamic access mechanism invites a number of security threats at the physical layer in the CRN. In particular, during the handoff of cognitive users (CUs), a malicious user (MU) may perform new types of attacks specific to handoff CU (HCU). In this article, we present a new type of security threat, called a cognitive user emulation attack (CUEA), which occurs during the spectrum handoff in a CRN. In CUEA, an attacker aims to block the legitimate users (i.e., HCUs) from accessing the new and unused channels by mimicking them. The problem comes from the fact that during the delay in the spectrum handoff process, when users vacate to occupy an unused channel, the MU can behave as a legitimate HCU to block the user from occupying the unused channel.

Consequently, the MU can affect the data transmission process and degrade the network performance. To address this problem, we first present a detailed investigation of the security threats specific to CUs that occur during their mobility. Also, we discuss the problems for different communication networks (i.e., centralized and decentralized), where CUEA takes place with different attacking strategies. Further, we examine the challenges of CUEA in different networks by classifying them into a range of open issues. Moreover, we illustrate the need for artificial intelligence techniques for making efficient autonomous decisions to improve the network performance in terms of throughput, energy consumption, and delivery delay. We also discuss the prospective challenges of the primary user emulation attack and future research directions.

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