Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

Zhang, Linyuan; Ding, Guoru; Wu, Qihui; Zou, Yulong; Han, Zhu; Wang, Jinlong

doi:10.1109/comst.2015.2422735

Cited by 206 publications

(86 citation statements)

References 106 publications

(206 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some studies have recently considered an attack model known as SSDF [32][33][34], which is a fatal threat to CSS. There are several typical attack patterns under the SSDF model, which are known as always opposite (AO), always busy (AB), always free (AF), and random disguising.…”

Section: Problem Formulationmentioning

confidence: 99%

Robust and Low‐Complexity Cooperative Spectrum Sensing via Low‐Rank Matrix Recovery in Cognitive Vehicular Networks

Liu

Zeng

Guo

2018

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

In cognitive vehicular networks (CVNs), many envisioned applications related to safety require highly reliable connectivity. This paper investigates the issue of robust and efficient cooperative spectrum sensing in CVNs. We propose robust cooperative spectrum sensing via low-rank matrix recovery (LRMR-RCSS) in cognitive vehicular networks to address the uncertainty of the quality of potentially corrupted sensing data by utilizing the real spectrum occupancy matrix and corrupted data matrix, which have a simultaneously low-rank and joint-sparse structure. Considering that the sensing data from crowd cognitive vehicles would be vast, we extend our robust cooperative spectrum sensing algorithm to dense cognitive vehicular networks via weighted low-rank matrix recovery (WLRMR-RCSS) to reduce the complexity of cooperative spectrum sensing. In the WLRMR-RCSS algorithm, we propose a correlation-aware selection and weight assignment scheme to take advantage of secondary user (SU) diversity and reduce the cooperation overhead. Extensive simulation results demonstrate that the proposed LRMR-RCSS and WLRMR-RCSS algorithms have good performance in resisting malicious SU behavior. Moreover, the simulations demonstrate that the proposed WLRMR-RCSS algorithm could be successfully applied to a dense traffic environment.

show abstract

Section: Problem Formulationmentioning

confidence: 99%

Robust and Low‐Complexity Cooperative Spectrum Sensing via Low‐Rank Matrix Recovery in Cognitive Vehicular Networks

Liu

Zeng

Guo

2018

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…For a constant β (i.e., fraction of compromised SNs) the attacker plans the optimum C i in (5) such that the FC becomes inefficient (i.e., useless). Adopting again the MDC (14), the optimisation problem can be expressed as:…”

Section: B Attacker Performance Optimisationmentioning

confidence: 99%

“…However, security issues in centralized detection using WSNs remain an open issue, see [14]- [19] and references therein. While there are many types of security threats, in this paper we focus on a single type of attack, which is the test statistic falsification (TSF) attack part of the Byzantine attacks family originally proposed by [20] and later widely used in the context of distributed detection (e.g., [19], [21], [22]).…”

Section: Introductionmentioning

confidence: 99%

Distributed Binary Event Detection Under Data-Falsification and Energy-Bandwidth Limitation

Nurellari¹,

McLernon²,

Ghogho³

et al. 2016

IEEE Sensors J.

View full text Add to dashboard Cite

Abstract-We address the problem of centralized detection of a binary event in the presence of falsifiable sensor nodes (SNs) (i.e., controlled by an attacker) for a bandwidth-constrained under−attack spatially uncorrelated distributed wireless sensor network (WSN). The SNs send their quantized test statistics over orthogonal channels to the fusion center (FC), which linearly combines them to reach a final decision. First (considering that the FC and the attacker do not act strategically), we derive (i) the FC optimal weight combining; (ii) the optimal SN to FC transmit power, and (iii) the test statistic quantization bits that maximize the probability of detection (P d ). We also derive an expression for the attacker strategy that causes the maximum possible FC degradation. But in these expressions, both the optimum FC strategy and the attacker strategy require a − priori knowledge that cannot be obtained in practice. The performance analysis of sub-optimum FC strategies is then characterized, and based on the (compromised) SNs willingness to collaborate, we also derive analytically the sub-optimum attacker strategies. Then, considering that the FC and the attacker now act strategically, we re-cast the problem as a minimax game between the FC and the attacker and prove that the Nash Equilibrium (NE) exists. Finally, we find this NE numerically in the simulation results and this gives insight into the detection performance of the proposed strategies.

show abstract

“…Like all other networks [3], WSNs are also vulnerable to various security issues. Furthermore, the local SNs decision process (i.e., local detection performance) itself is subject to various security threats.…”

Section: Introductionmentioning

confidence: 99%

A Secure Optimum Distributed Detection Scheme in Under-Attack Wireless Sensor Networks

Nurellari

McLernon

Ghogho

2018

IEEE Trans. on Signal and Inf. Process. over Networks

View full text Add to dashboard Cite

Abstract-We address the problem of centralized detection of a binary event in the presence of β fraction falsifiable sensor nodes (SNs) (i.e., controlled by an attacker) for a bandwidthconstrained under − attack spatially uncorrelated distributed wireless sensor network (WSN). The SNs send their one-bit test statistics over orthogonal channels to the fusion center (FC), which linearly combines them to reach to a final decision. Adopting the modified deflection coefficient as an alternative function to be optimized, we first derive in a closed-form the FC optimal weights combining. But as these optimal weights require a − priori knowledge that cannot be attained in practice, this optimal weighted linear FC rule is not implementable. We also derive in a closed-form the expressions for the attacker "flipping probability" (defined in paper) and the minimum fraction of compromised SNs that makes the FC incapable of detecting. Next, based on the insights gained from these expressions, we propose a novel and non-complex reliability-based strategy to identify the compromised SNs and then adapt the weights combining proportional to their assigned reliability metric. In this way, the FC identifies the compromised SNs and decreases their weights in order to reduce their contributions towards its final decision. Finally, simulation results illustrate that the proposed strategy significantly outperforms (in terms of FC's detection capability) the existing compromised SNs identification and mitigation schemes.

show abstract

Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

Cited by 206 publications

References 106 publications

Robust and Low‐Complexity Cooperative Spectrum Sensing via Low‐Rank Matrix Recovery in Cognitive Vehicular Networks

Robust and Low‐Complexity Cooperative Spectrum Sensing via Low‐Rank Matrix Recovery in Cognitive Vehicular Networks

Distributed Binary Event Detection Under Data-Falsification and Energy-Bandwidth Limitation

A Secure Optimum Distributed Detection Scheme in Under-Attack Wireless Sensor Networks

Contact Info

Product

Resources

About