MIS: Malicious nodes identification scheme in network-coding-based peer-to-peer streaming

Qiyan Wang, Long Vu, Klara Nahrstedt, Himanshu Khurana

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Network coding has been shown to be capable of greatly improving quality of service in P2P live streaming systems (e.g., IPTV). However, network coding is vulnerable to pollution attacks where malicious nodes inject into the network bogus data blocks that are combined with other legitimate blocks at downstream nodes, leading to incapability of decoding the original blocks and substantial degradation of network performance. In this paper, we propose a novel approach to limiting pollution attacks by rapidly identifying malicious nodes. Our scheme can fully satisfy the requirements of live streaming systems, and achieves much higher efficiency than previous schemes. Each node in our scheme only needs to perform several hash computations for an incoming block, incurring very small computational latency. The space overhead added to each block is only 20 bytes. The verification information given to each node is independent of the streaming content and thus does not need to be redistributed. The simulation results based on real PPLive channel overlays show that the process of identifying malicious nodes only takes a few seconds even in the presence of a large number of malicious nodes.

Original languageEnglish (US)
Title of host publication2010 Proceedings IEEE INFOCOM
StatePublished - 2010
EventIEEE INFOCOM 2010 - San Diego, CA, United States
Duration: Mar 14 2010Mar 19 2010

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Country/TerritoryUnited States
CitySan Diego, CA

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering


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