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Open Access Publications from the University of California

Visual-based Anomaly Detection for BGP Orign AS Change Events

  • Author(s): Teoh, Soon Tee
  • Ma, Kwan-Liu
  • Wu, Felix S.
  • Massey, Dan
  • Zhao, Xiaoliang
  • Pei, Dan
  • Wang, Lan
  • Zhang, Lixia
  • Bush, Randy
  • et al.
Abstract

Instead of relying completely on machine intelligence in anomaly event analysis and correlation, in this paper, we take one step back and investigate the possibility of a human-interactive visual-based anomaly detection system for faults and security attacks related to the BGP (Border Gateway Protocol) routing protocol. In particular, we have built and tested a program, based on fairly simple information visualization techniques, to navigate interactively real-life BGP OASC (Origin AS Change) events. Our initial experience demonstrates that the integration of mechanic analysis and human intelligence can effectively improve the performance of anomaly detection and alert correlation. Furthermore, while a traditional representation of OASC events provides either little or no valuable information, our program can accurately identify, correlate previously unknown BGP/OASC problems, and provide network operators with a valuable high-level abstraction about the dynamics of BGP.

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