An efficient and DoS-resilient name lookup for NDN interest forwarding. Issue 3 (3rd July 2021)

• Record Type: Journal Article
• Authors: He, Dacheng; Zhang, Dafang; Li, Yanbiao; Liang, Wei; Hsieh, Meng-Yen
• Is Part Of: Connection science. Volume 33:Issue 3(2021)
• Page Start: 735
• Page End: 752
• Publication Date: 2021-07-03
• Subjects: NDN -- DoS -- name lookup -- feature prefix -- interest forwarding; Neural computers -- Periodicals; Artificial intelligence -- Periodicals; Cognitive science -- Periodicals; Connectionism -- Periodicals; 006.3
• DOI: 10.1080/09540091.2021.1875988
• Languages: English
• ISSNs: 0954-0091

Abstract

Abstract : As a novel Internet architecture focused on data contents, Named Data Networking (NDN) has been proven to be of great value in supporting the Internet of Things, Edge computing, Blockchain, and other popular topics. They can benefit mainly from NDN's intrinsic properties, such as flexible multicasting, in-network caching, among several others. However, once NDN's forwarding plane suffers Denial of Service (DoS) attacks, the overall system performance would be affected significantly. In NDN data transmission, interest forwarding is the most time-consuming operation and thus opens a possible vector of DoS attacks. It is proposed in this paper a fast name lookup algorithm for NDN interest forwarding, which selects feature prefixes instead of lengths to filter out interest packets in NDN interest forwarding. Due to the excellent filtration with feature prefixes, the algorithm accelerates NDN forwarding processes. Compared with other existing solutions, the proposed algorithm shows more than 70% of time improvement in forwarding malicious interests, while remaining at the same performance level in standard cases.