A novel approach for anti-pollution attacks in network coding. Issue 3 (3rd July 2021)

• Record Type: Journal Article
• Authors: Ning, Zuoting; Shi, Weiqi; Xiao, Lijun; Liang, Wei; Weng, Tien-Hsiung
• Is Part Of: Connection science. Volume 33:Issue 3(2021)
• Page Start: 447
• Page End: 462
• Publication Date: 2021-07-03
• Subjects: Network coding -- pollution attack -- security -- malicious node; Neural computers -- Periodicals; Artificial intelligence -- Periodicals; Cognitive science -- Periodicals; Connectionism -- Periodicals; 006.3
• DOI: 10.1080/09540091.2020.1841109
• Languages: English
• ISSNs: 0954-0091

Abstract

Abstract : Network coding remarkably improves network performance and transmission efficiency for multi-cast. Nevertheless, as its inherent defect, it is vulnerable to pollution attacks, bringing in a severe decrease of the network performance. In the proposed work, a novel approach is put forwarded, which can rapidly identify and isolate the malicious nodes from the networks as early as possible. On the one hand, we raise a secure infrastructure, on the other hand, we advocate a secure transmission protocol to verify every received packet. Theoretical analysis and experimental results demonstrate that the proposed scheme has the optimal performance in terms of security, network delay and network throughput.