A multi‐agent based mechanism for collaboratively detecting distributed denial of service attacks in internet of vehicles. (7th March 2022)

• Record Type: Journal Article
• Authors: Dong, Tingting; Chen, Lei; Zhou, Li; Xue, Fei; Qin, Huilin
• Is Part Of: Concurrency and computation. Volume 34:Number 13(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-03-07
• Subjects: deep reinforcement learning -- distributed denial of service attacks -- hidden Markov model -- internet of vehicles -- multi‐agent learning; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.6904
• Languages: English
• ISSNs: 1532-0626

Abstract

Abstract: Distributed denial of service (DDoS) attacks have become a hidden danger in the development of the internet of vehicles (IoV). DDoS attacks for TCP protocol are studied to improve the information security environment of IoV. For the distribution characteristics of DDoS attacks, an information sharing and collaborative detection mechanism based on multi‐agent is proposed. Considering the relationship between the features of adjacent moments in the TCP communication, the DDoS detection model based on hidden Markov model is built, and the Viterbi algorithm is improved for the problem of the false alarm in the observation sequence. The optimal communication strategy among agents is determined by deep reinforcement learning, and fusion algorithm is designed to improve the current strategy of agents. Three groups of comparative experiments are designed and analyzed. The simulation results show that proposed algorithms are effective.