Defense Against SSDF Attack in Cognitive Radio Networks: Attack-Aware Collaborative Spectrum Sensing Approach

The reliability of the collaborative spectrum sensing (CSS) can be severely decreased by spectrum sensing data falsification (SSDF) attacks. In an SSDF attack, some malicious users intentionally report incorrect local sensing results to the fusion center (FC) and disrupt the global decision-making p...

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Bibliographic Details
Published in:IEEE communications letters 2016-01, Vol.20 (1), p.93-96
Main Authors: Sharifi, Abbas Ali, Musevi Niya, Mir Javad
Format: Article
Language:English
Subjects:
Attack Strength
Attack-Aware
Bayes Risk
Bayesian analysis
Cascading style sheets
Cognitive radio
Collaboration
Decision making
Detection
Estimates
Estimation
Networks
Optimization
Sensors
Signal to noise ratio
Spectrum Sensing
Strength
Transmitters
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Summary:The reliability of the collaborative spectrum sensing (CSS) can be severely decreased by spectrum sensing data falsification (SSDF) attacks. In an SSDF attack, some malicious users intentionally report incorrect local sensing results to the fusion center (FC) and disrupt the global decision-making process. The present study introduces a new defense scheme called attack-aware CSS (ACSS). The proposed method estimates attack strength and applies it in the k-out-N rule to obtain the optimum value of k that minimizes the Bayes risk. The attack strength is defined as the ratio of the number of malicious users to the total number of users, which is equal to the probability that a specific user is malicious.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2015.2499286