Network layer attacks and countermeasures in cognitive radio networks: A survey

Bouabdellah, Mounia; Kaabouch, Naima; Bouanani, Faïssal El; Ben-Azza, Hussain

doi:10.1016/j.jisa.2017.11.010

Cited by 37 publications

(16 citation statements)

References 28 publications

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“…The cognitive radio network is subject to several attacks that can create a denial of service [36][37][38]. For instance, if a channel is jammed, the communication is interrupted.…”

Section: Discussionmentioning

confidence: 99%

Multi-Attributes, Utility-Based, Channel Quality Ranking Mechanism for Cognitive Radio Networks

2018

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Abstract:Cognitive radio is an intelligent wireless solution that aims to enhance the access to the radio spectrum. In this technology, secondary users sense the radio spectrum, select the best channel among a pool of free channels, and determine the optimal transmission parameters to meet their quality-of-service requirements while maximizing the spectral efficiency. Over the past decade, several channel-ranking mechanisms have been proposed. However, these mechanisms consider only the remaining idle time of the channel and exclude some crucial parameters. This convincingly demonstrates a strong need for a new channel quality-ranking model that jointly considers several parameters to select the best communication channel for transmission. This paper proposes a utility model that integrates several important parameters for ranking channels. First, we underline the importance of the process of the channel quality ranking. Then, we describe a multi-attributes, utility-based, channel quality-ranking model. Finally, we describe a series of experiments and their results, which show that our model effectively ranks the best communication channels first.

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“…The cognitive radio network is subject to several attacks that can create a denial of service [36][37][38]. For instance, if a channel is jammed, the communication is interrupted.…”

Section: Discussionmentioning

confidence: 99%

Multi-Attributes, Utility-Based, Channel Quality Ranking Mechanism for Cognitive Radio Networks

2018

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“…For instance, authors in [30], listed several common security attacks/threats to CR physical layer and proposed some countermeasures that can be utilized to protect CR users. In [31], the authors presented a list of current network layer attacks and their countermeasures. Authors in [32], have presented a secured transmission approach that can be used in a CR-based network.…”

Section: A Related Workmentioning

confidence: 99%

A Secure and Energy-Aware Approach For Cognitive Radio Communications

Khaled

Ahmad

Habibi

et al. 2020

IEEE Open J. Commun. Soc.

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The cognitive radio (CR) technique has revealed a novel way of utilizing the precious radio spectrum via allowing unlicensed users to opportunistically access unutilized licensed bands. Using such a technique enables agile and flexible access to the radio spectrum and can resolve the spectrum-scarcity problem and maximize spectrum efficiency. However, two major impediments have been limiting the widespread adoption of cognitive radio technology. The software-defined radio technology, which is the enabling technology for the CR technique, is power-hungry and this raises a major concern for battery-constrained devices such as smart phones and laptops. Secondly, the opportunistic and open nature of the CR can lead to major security concerns about the data being sent and how safe it is. In this paper, we introduce an energy-and-security-aware CR-based communication approach that alleviates the power consumption of the CR technique and enhances its security measures according to the confidentiality level of the data being sent. Furthermore, the proposed approach takes into account user-related factors, such as the users battery level and users data type, and network-related factors, such as the number of unutilized bands and vulnerability level and then models the research question as a constrained optimization problem. Considering the time complexity of the optimum solution, we also propose a heuristic solution. We examine the proposed solution against existing solutions, and our obtained results show that the proposed approach can save energy consumption up to 18%, increase user throughput up to 20%, and achieve better spectrum utilization, up to 98%. Our proposed admission approach has the potential to open a new research direction towards safer and greener cognitive radio techniques. Index Terms-Cognitive radio, next generation wireless networks, green communications, cognitive radio security issues, software defined radio.

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“…Several malicious activities or attacks can target CRN, including selfish access (SA) one to the idle spectrum, namely, an entire deny of service (DoS). Nowadays, various techniques have been investigated to detect such attack activities.…”

Section: Introductionmentioning

confidence: 99%

A decision‐making approach for detecting the primary user emulation attack in cognitive radio networks

Fihri

Ghazi

Majd

et al. 2019

Int J Communication

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Summary Cognitive radio network (CRN) is a promising technology, which enables secondary users to use the free spectrum channels without causing detrimental interference with the primary user (PU). Nevertheless, CRN is subject to numerous cyber attacks that have a negative impact on its performance. Among the CRN attacks, the primary user emulation (PUE) attack is known to be one of the malicious attacks threatening CRN security. Several attacks detection techniques, based on attacker localization, have been investigated in the literature. These techniques include the trilateration, received signal strength indication (RSSI), and network coding approach as well. However, most of these techniques do not consider the uncertainty related to CRN, which can be modeled by a cost function defined as a weighted sum of conditional probabilities. In this paper, a localization technique, relied on a trilateration computation and a Bayesian model, is proposed for PUE position detection purpose under uncertainty conditions assumption. Particularly, the estimation of PUE position is performed through trilateration method based on RSSI at the anchor nodes for the signal coming from either PU or PUE, whereas, the Bayesian decision model, based on a cost function, is involved to check the PU legitimacy. The simulation results show that the decision‐making approach "Security, productivity, Balancing" influences directly the zone of the PUE attack detection.

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Network layer attacks and countermeasures in cognitive radio networks: A survey

Cited by 37 publications

References 28 publications

Multi-Attributes, Utility-Based, Channel Quality Ranking Mechanism for Cognitive Radio Networks

Multi-Attributes, Utility-Based, Channel Quality Ranking Mechanism for Cognitive Radio Networks

A Secure and Energy-Aware Approach For Cognitive Radio Communications

A decision‐making approach for detecting the primary user emulation attack in cognitive radio networks

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