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Abbas Ali Sharifi

Abbas Ali Sharifi

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId:
HIndex: 0/00
Faculty: Faculty of Engineering
Address:
Phone: 041-37745000

Research

Title
An Effective and Optimal Fusion Rule in the Presence of Probabilistic Spectrum Sensing Data Falsification Attack
Type
JournalPaper
Keywords
Attack-aware; optimal voting rule; spectrum sensing data falsification attack; cognitive radio.
Year
2019
Journal Journal of Communication Engineering
DOI
Researchers Abbas Ali Sharifi

Abstract

Cognitive radio (CR) network is an excellent solution to the spectrum scarcity problem. Cooperative spectrum sensing (CSS) has been widely used to precisely detect primary user (PU) signals. The trustworthiness of the CSS is vulnerable to spectrum sensing data falsification (SSDF) attack. In an SSDF attack, some malicious users intentionally report wrong sensing results to cheat the fusion center (FC) and disturb the FC’s global decision on the PU activity. In this paper, we introduce an effective data fusion rule called attack-aware optimal voting rule (AOVR) to confront the SSDF attack in the CSS procedure. In the beginning stages of the cooperative sensing, two important SSDF attack parameters are estimated and then applied in a conventional voting rule to acquire an optimal number of CR users to minimize the global error probability. Two estimated attack parameters include the probabilities of attack in both occupied and empty frequency bands. Simulation results confirm that the proposed attack-aware approach achieves very good performance over the existing conventional cooperative sensing methods.