AS-TRUST: A Trust Quantification Scheme for Autonomous Systems in BGP

被引:0
|
作者
Chang, Jian [1 ]
Venkatasubramanian, Krishna K. [1 ]
West, Andrew G. [1 ]
Kannan, Sampath [1 ]
Loo, Boon Thau [1 ]
Sokolsky, Oleg [1 ]
Lee, Insup [1 ]
机构
[1] Univ Penn, Dept Comp & Informat Sci, 200 S 33Rd St, Philadelphia, PA 19104 USA
关键词
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The Border Gateway Protocol (BGP) works by frequently exchanging updates that disseminate reachability information about IP prefixes (i.e., IP address blocks) between Autonomous Systems (ASes) on the Internet. The ideal operation of BGP relies on three major behavioral assumptions (BAs): (1) information contained in the update is legal and correct, (2) a route to a prefix is stable, and (3) the route adheres to the valley free routing policy. The current operation of BGP implicitly trusts all ASes to adhere to these assumptions. However, several documented violation of these assumptions attest to the fact that such an assumption of trust is perilous. This paper presents AS-TRUST, a scheme that comprehensively characterizes the trustworthiness of ASes with respect to their adherence of the behavioral assumptions. AS-TRUST quantifies trust using the notion of AS reputation. To compute reputation, AS-TRUST analyzes updates received in the past. It then classifies the resulting observations into multiple types of feedback. The feedback is used by a reputation function that uses Bayesian statistics to compute a probabilistic view of AS trustworthiness. This information can then be used for improving quotidian BGP operation by enabling improved route preference and dampening decision making at the ASes. Our implementation of AS-TRUST scheme using publicly available BGP traces demonstrates: (1) the number of ASes involved in violating the BGP behavioral assumptions is significant, and (2) the proposed reputation mechanism provides multi-fold improvement in the ability of ASes to operate in the presence of BA violations.
引用
收藏
页码:262 / 276
页数:15
相关论文
共 50 条
  • [31] Supporting Trust in Autonomous Driving
    Haeuslschmid, Renate
    von Buelow, Max
    Pfleging, Bastian
    Butz, Andreas
    IUI'17: PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON INTELLIGENT USER INTERFACES, 2017, : 319 - 329
  • [32] Autonomous distributed trust mode
    Zhan, Yang
    Pang, Liao-Jun
    Zhu, Xiao-Yan
    Wang, Yu-Min
    Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2008, 35 (03): : 469 - 473
  • [33] Trust of Customers in Autonomous Vehicles
    Köster, Nils
    Salge, Torsten-Oliver
    ATZ worldwide, 2021, 123 (7-8) : 40 - 45
  • [34] Trust based quantification of quality in multi-agent systems
    Department of Computer Sciences, University of Delhi, Delhi-110007, India
    Inf. Technol. J., 2007, 3 (414-423):
  • [35] Computational quantification of trust updates
    Ramer, Arthur
    AIDM 2006: International Workshop on Integrating AI and Dating Mining, 2006, : 73 - 78
  • [36] Trust Traversal: A trust link detection scheme in social network
    Zhang, Bo
    Zhang, Huan
    Li, Meizi
    Zhao, Qin
    Huang, Jifeng
    COMPUTER NETWORKS, 2017, 120 : 105 - 125
  • [37] Can We Trust Trust Management Systems?
    Marche, Claudio
    Nitti, Michele
    IOT, 2022, 3 (02): : 262 - 272
  • [38] A Secure and Decentralized Trust Management Scheme for Smart Health Systems
    Ebrahimi, Maryam
    Haghighi, Mohammad Sayad
    Jolfaei, Alireza
    Shamaeian, Nasrin
    Tadayon, Mohammad Hesam
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2022, 26 (05) : 1961 - 1968
  • [39] BGP Neighbor Trust Establishment Mechanism Based on the Bargaining Game
    Li, Peipei
    Lu, Bin
    Li, Daofeng
    INFORMATION, 2021, 12 (03) : 1 - 14
  • [40] A Trust Propagation Scheme in VANETs
    Wang, Jian
    Liu, Yanheng
    Liu, Xiaomin
    Zhang, Jing
    2009 IEEE INTELLIGENT VEHICLES SYMPOSIUM, VOLS 1 AND 2, 2009, : 1067 - 1071