TY - GEN
T1 - PSO-Meme
T2 - 2024 IEEE Global Communications Conference, GLOBECOM 2024
AU - Wu, Xinhan
AU - Guo, Hongzhi
AU - Zhou, Xiaoyi
AU - Mao, Bomin
AU - Liu, Jiajia
AU - Xun, Yijie
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - As a critical element in intelligent transportation systems (ITS), roadside units (RSUs) are pivotal in delivering superior Internet of Vehicles (IoV) services encompassing intelligent traffic management, accident prevention, and emergency rescue. Considering the high deployment and maintenance costs of RSUs, many studies focus on the efficient RSU deployment issues. However, due to the high visibility of the ITS system, RSUs are highly susceptible to external attacks, which is commonly overlooked in existing RSU deployment researches. Specifically, the Sybil attack is one of the most dangerous attacks against ITS, it can reshape the network state by forging multiple identities, interfering with the operator's reputation assessment or causing severe DDoS. Therefore, we propose a joint heuristic scheme that combines the advantages of particle swarm optimization and double local-search memetic algorithm to solve the city RSU deployment problem in Sybil attack environments. It can find solutions with higher fitness values and guarantees that the IoV has the capability to detect Sybil attacks. Numerical results show that our proposed scheme not only outperforms other traditional solutions regarding signal validity coverage, overlap rate, and initial propagation speed of accident information, but also performs satisfactorily in Sybil attack detection.
AB - As a critical element in intelligent transportation systems (ITS), roadside units (RSUs) are pivotal in delivering superior Internet of Vehicles (IoV) services encompassing intelligent traffic management, accident prevention, and emergency rescue. Considering the high deployment and maintenance costs of RSUs, many studies focus on the efficient RSU deployment issues. However, due to the high visibility of the ITS system, RSUs are highly susceptible to external attacks, which is commonly overlooked in existing RSU deployment researches. Specifically, the Sybil attack is one of the most dangerous attacks against ITS, it can reshape the network state by forging multiple identities, interfering with the operator's reputation assessment or causing severe DDoS. Therefore, we propose a joint heuristic scheme that combines the advantages of particle swarm optimization and double local-search memetic algorithm to solve the city RSU deployment problem in Sybil attack environments. It can find solutions with higher fitness values and guarantees that the IoV has the capability to detect Sybil attacks. Numerical results show that our proposed scheme not only outperforms other traditional solutions regarding signal validity coverage, overlap rate, and initial propagation speed of accident information, but also performs satisfactorily in Sybil attack detection.
KW - heuristic algorithm
KW - intelligent transportation system
KW - internet of vehicles
KW - RSU deployment
KW - Sybil attacks
UR - http://www.scopus.com/inward/record.url?scp=105000831054&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM52923.2024.10901630
DO - 10.1109/GLOBECOM52923.2024.10901630
M3 - 会议稿件
AN - SCOPUS:105000831054
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 511
EP - 516
BT - GLOBECOM 2024 - 2024 IEEE Global Communications Conference
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 December 2024 through 12 December 2024
ER -