TY - GEN
T1 - Distributed Detection with Multiple Sensors in the Presence of Sybil Attacks
AU - Hashlamoun, Wael
AU - Brahma, Swastik
AU - Varshney, Pramod K.
N1 - Funding Information:
This work was supported in part by the U.S. NSF under Award Number CCF-2047701 and in part by the Zamalah Program, Bank of Palestine.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper considers the problem of distributed detection in the presence of a Sybil attack where a malicious sensor node can send multiple falsified decisions using multiple fake identities to a Fusion Center (FC) to degrade its decision-making performance. We study the problem under the Neyman-Pearson (NP) setup. We find that, due to the Sybil attack, the decisions received at the FC become correlated and that the degree of correlation is dependent on the number of fake identities used. The paper characterizes the optimal Sybil attack that blinds the FC, i.e., makes the FC incapable of making an informed decision. We find that if the sum of the local detection and false alarm probabilities of the sensor nodes is 1, the FC can be made blind when at least 50% of the decisions are sent using fake identities. However, if this condition is not met, then all decisions would have to be sent using fake identities in order to blind the FC. The paper also investigates strategic interactions between the FC and the Sybil attacker using Game Theory and proves the existence of a Nash Equilibrium (NE). Numerical results are presented to gain important insights.
AB - This paper considers the problem of distributed detection in the presence of a Sybil attack where a malicious sensor node can send multiple falsified decisions using multiple fake identities to a Fusion Center (FC) to degrade its decision-making performance. We study the problem under the Neyman-Pearson (NP) setup. We find that, due to the Sybil attack, the decisions received at the FC become correlated and that the degree of correlation is dependent on the number of fake identities used. The paper characterizes the optimal Sybil attack that blinds the FC, i.e., makes the FC incapable of making an informed decision. We find that if the sum of the local detection and false alarm probabilities of the sensor nodes is 1, the FC can be made blind when at least 50% of the decisions are sent using fake identities. However, if this condition is not met, then all decisions would have to be sent using fake identities in order to blind the FC. The paper also investigates strategic interactions between the FC and the Sybil attacker using Game Theory and proves the existence of a Nash Equilibrium (NE). Numerical results are presented to gain important insights.
KW - Data Falsification
KW - Distributed Detection
KW - Game Theory
KW - Sensor Networks
KW - Sybil Attack
UR - http://www.scopus.com/inward/record.url?scp=85146942672&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146942672&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM48099.2022.10001514
DO - 10.1109/GLOBECOM48099.2022.10001514
M3 - Conference contribution
AN - SCOPUS:85146942672
T3 - 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings
SP - 2770
EP - 2775
BT - 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Global Communications Conference, GLOBECOM 2022
Y2 - 4 December 2022 through 8 December 2022
ER -