TY - GEN
T1 - A density based scheme to countermeasure spectrum sensing data falsification attacks in cognitive radio networks
AU - Chen, Changlong
AU - Song, Min
AU - Xin, Chunsheng
PY - 2013
Y1 - 2013
N2 - Cognitive radio networks are a promising solution to the spectrum scarcity issue. In cognitive radio networks, because of the low reliability of individual spectrum sensing by a single secondary user, cooperative spectrum sensing is critical to accurately detect the existence of a primary user signal. However, cooperative spectrum sensing is vulnerable to the spectrum sensing data falsification (SSDF) attack. Specifically, a malicious user can send a falsified sensing report to mislead other (benign) secondary users to make an incorrect decision on the PU activity. Therefore, detecting the SSDF attack or identifying the malicious sensing reports is extremely important for robust cooperative spectrum sensing. This paper proposes a distributed density based SSDF detection (DBSD) scheme to countermeasure the SSDF attack. DBSD can effectively exclude the malicious sensing reports from SSDF attackers, so that a benign secondary user can effectively detect the PU activity in distributed cooperative spectrum sensing. Furthermore, DBSD can also exclude abnormal sensing reports from ill-functioned secondary users. Simulation results show that DBSD achieves very good performance in cooperative spectrum sensing.
AB - Cognitive radio networks are a promising solution to the spectrum scarcity issue. In cognitive radio networks, because of the low reliability of individual spectrum sensing by a single secondary user, cooperative spectrum sensing is critical to accurately detect the existence of a primary user signal. However, cooperative spectrum sensing is vulnerable to the spectrum sensing data falsification (SSDF) attack. Specifically, a malicious user can send a falsified sensing report to mislead other (benign) secondary users to make an incorrect decision on the PU activity. Therefore, detecting the SSDF attack or identifying the malicious sensing reports is extremely important for robust cooperative spectrum sensing. This paper proposes a distributed density based SSDF detection (DBSD) scheme to countermeasure the SSDF attack. DBSD can effectively exclude the malicious sensing reports from SSDF attackers, so that a benign secondary user can effectively detect the PU activity in distributed cooperative spectrum sensing. Furthermore, DBSD can also exclude abnormal sensing reports from ill-functioned secondary users. Simulation results show that DBSD achieves very good performance in cooperative spectrum sensing.
KW - SSDF attack
KW - cognitive radio networks
KW - probability density based SSDF detection
UR - http://www.scopus.com/inward/record.url?scp=84904137004&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904137004&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2013.6831141
DO - 10.1109/GLOCOM.2013.6831141
M3 - Conference contribution
AN - SCOPUS:84904137004
SN - 9781479913534
SN - 9781479913534
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 623
EP - 628
BT - 2013 IEEE Global Communications Conference, GLOBECOM 2013
T2 - 2013 IEEE Global Communications Conference, GLOBECOM 2013
Y2 - 9 December 2013 through 13 December 2013
ER -