You Can Jam But You Cannot Hide: Defending Against Jamming Attacks for Geo-Location Database Driven Spectrum Sharing

Zhu, Haojin; Fang, Chenliaohui; Liu, Yao; Chen, Cailian; Li, Mengyuan; Shen, Xuemin

doi:10.1109/jsac.2016.2605799

Cited by 57 publications

(19 citation statements)

References 37 publications

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“…The SSP mechanism in the Bluetooth standard is responsible for this task. In addition, when we build a secure home network system, the SSP mechanism also is the backbone of the Bluetooth solution to cooperate with other kinds of secure schemes [24][25][26][27][28][29].…”

Section: Performance Analysis Of Improved Passkey Entry Protocolmentioning

confidence: 99%

Man-in-the-middle attacks on Secure Simple Pairing in Bluetooth standard V5.0 and its countermeasure

Sun

Susilo

2017

Pers Ubiquit Comput

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Bluetooth devices are widely employed in the home network systems. It is important to secure the home members' Bluetooth devices, because they always store and transmit personal sensitive information. In the Bluetooth standard, Secure Simple Pairing (SSP) is an essential security mechanism for Bluetooth devices. We examine the security of SSP in the recent Bluetooth standard V5.0. The passkey entry association model in SSP is analyzed under the man-in-the-middle (MITM) attacks. Our contribution is twofold. (1) We demonstrate that the passkey entry association model is vulnerable to the MITM attack, once the host reuses the passkey. (2) An improved passkey entry protocol is therefore designed to fix the reusing passkey defect in the passkey entry association model. The improved passkey entry protocol can be easily adapted to the Bluetooth standard, because it only uses the basic cryptographic components existed in the Bluetooth standard. Our research results are beneficial to the security enhancement of Bluetooth devices in the home network systems.

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Section: Performance Analysis Of Improved Passkey Entry Protocolmentioning

confidence: 99%

Man-in-the-middle attacks on Secure Simple Pairing in Bluetooth standard V5.0 and its countermeasure

Sun

Susilo

2017

Pers Ubiquit Comput

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“…if collision from Jammer then 9: C πi = C πi + 1 10: else 11: r t ← 1 12: end if 13: end if 14: end for 15…”

Section: Su Algorithm: Cnjmentioning

confidence: 99%

Learning to Coordinate in a Decentralized Cognitive Radio Network in Presence of Jammers

Sawant

Kumar

Hanawal

et al. 2020

IEEE Trans. on Mobile Comput.

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Efficient utilization of licensed spectrum in the cognitive radio network is challenging due to lack of coordination among the Secondary Users (SUs). Distributed algorithms proposed in the literature aim to maximize the network throughput by ensuring orthogonal channel allocation for the SUs. However, these algorithms work under the assumption that all the SUs faithfully follow the algorithms which may not always hold due to the decentralized nature of the network. In this paper, we study distributed algorithms that are robust against malicious behavior (jamming attack). We consider both the cases of jammers launching coordinated and uncoordinated attacks. In the coordinated attack, the jammers select non-overlapping channels to attack in each time slot and can significantly increase the number of collisions for SUs. We setup the problem in each scenario as a multi-player bandit and develop algorithms. The analysis shows that when the SUs faithfully implement proposed algorithms, the regret is constant with high probability.We validate our claims through exhaustive synthetic experiments and also through a realistic USRP based experiment. IndexTerms-Cognitive radio network, jamming attack, distributed learning ! PLACE PHOTO HERE Sunnet Sawant received his B.Tech and M.Tech. dual degree in Electrical Engineering from IIT Bombay in 2017. His research interests include communication networks PLACE PHOTO HERE Rohit Kumar received his B.

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“…A larger u c o f f indicates that c is better and more suitable for data transmission. It is assumed that each node independently estimates PUs' activities using the above ON/OFF model instead of relying on a geo-location database [34].…”

Section: Problem Formulationmentioning

confidence: 99%

CDCS: Cluster-Based Distributed Compressed Sensing to Facilitate QoS Routing in Cognitive Video Sensor Networks

Shen

Wang

et al. 2019

Entropy

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Compressed sensing based in-network compression methods which minimize data redundancy are critical to cognitive video sensor networks. However, most existing methods require a large number of sensors for each measurement, resulting in significant performance degradation in energy efficiency and quality-of-service satisfaction. In this paper, a cluster-based distributed compressed sensing scheme working together with a quality-of-service aware routing framework is proposed to deliver visual information in cognitive video sensor networks efficiently. First, the correlation among adjacent video sensors determines the member nodes that participate in a cluster. On this basis, a sequential compressed sensing approach is applied to determine whether enough measurements are obtained to limit the reconstruction error between decoded signals and original signals under a specified reconstruction threshold. The goal is to maximize the removal of unnecessary traffic without sacrificing video quality. Lastly, the compressed data is transmitted via a distributed spectrum-aware quality-of-service routing scheme, with an objective of minimizing energy consumption subject to delay and reliability constraints. Simulation results demonstrate that the proposed approach can achieve energy-efficient data delivery and reconstruction accuracy of visual information compared with existing quality-of-service routing schemes.

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You Can Jam But You Cannot Hide: Defending Against Jamming Attacks for Geo-Location Database Driven Spectrum Sharing

Cited by 57 publications

References 37 publications

Man-in-the-middle attacks on Secure Simple Pairing in Bluetooth standard V5.0 and its countermeasure

Man-in-the-middle attacks on Secure Simple Pairing in Bluetooth standard V5.0 and its countermeasure

Learning to Coordinate in a Decentralized Cognitive Radio Network in Presence of Jammers

CDCS: Cluster-Based Distributed Compressed Sensing to Facilitate QoS Routing in Cognitive Video Sensor Networks

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