Detecting malicious groups of agents

被引:0
|
作者
Braynov, S [1 ]
Jadliwala, M [1 ]
机构
[1] Univ Illinois, Dept Comp Sci, Springfield, IL 62703 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
In this paper we study coordinated attacks launched by multiple malicious agents and the problem of detecting malicious groups of attackers. The paper proposes a formal method and an algorithm for detecting action interference between users. It has to be pointed out that some members of a malicious group may not necessarily perform illegal actions, for example, they can prepare and organize an attack without taking active part in the actual attack execution. In addition, members of a malicious group May not necessarily know each other The method we propose tries to solve these problems by building a Coordination graph which includes all users who, in some way or another, cooperate with each other i.e., the maximal malicious group of cooperating users including not only the executers of the attack but also their assistants. The paper also proposes formal metrics on coordination graphs that help differentiate central from peripheral attackers.
引用
收藏
页码:90 / 99
页数:10
相关论文
共 50 条
  • [1] Afriat's Test for Detecting Malicious Agents
    Krishnamurthy, Vikram
    Hoiles, William
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2012, 19 (12) : 801 - 804
  • [2] MalReG: Detecting and Analyzing Malicious Retweeter Groups
    Gupta, Sonu
    Kumaraguru, Ponnurangam
    Chakraborty, Tanmoy
    [J]. PROCEEDINGS OF THE 6TH ACM IKDD CODS AND 24TH COMAD, 2019, : 61 - 69
  • [3] AntiMSA: A framework for detecting malicious software agents in online multiplayer games
    Oros, Bogdan-Ioan
    Bacu, Victor Ioan
    [J]. 2022 IEEE 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTER COMMUNICATION AND PROCESSING, ICCP, 2022, : 283 - 288
  • [4] Detecting malicious SQL
    Fonseca, Jose
    Vieira, Marco
    Madeira, Henrique
    [J]. TRUST, PRIVACY AND SECURITY IN DIGITAL BUSINESS, PROCEEDINGS, 2007, 4657 : 259 - +
  • [5] A protocol for detecting malicious hosts based on limiting the execution time of mobile agents
    Esparza, O
    Soriano, M
    Muñoz, JL
    Forné, J
    [J]. EIGHTH IEEE INTERNATIONAL SYMPOSIUM ON COMPUTERS AND COMMUNICATION, VOLS I AND II, PROCEEDINGS, 2003, : 251 - 256
  • [6] Managing Trust and Detecting Malicious Groups in Peer-to-Peer IoT Networks
    Alhussain, Alanoud
    Kurdi, Heba
    Altoaimy, Lina
    [J]. SENSORS, 2021, 21 (13)
  • [7] Malicious Hubs: Detecting Abnormally Malicious Autonomous Systems
    Kalafut, Andrew J.
    Shue, Craig A.
    Gupta, Minaxi
    [J]. 2010 PROCEEDINGS IEEE INFOCOM, 2010,
  • [8] An Unsupervised-Learning Based Method for Detecting Groups of Malicious Web Crawlers in Internet
    Yue, Tianyi
    Zhou, Yadong
    Hu, Bowen
    Xu, Zhanbo
    Guan, Xiaohong
    Zhou, Hao
    Liu, Ting
    [J]. 2021 IEEE 17TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), 2021, : 367 - 372
  • [9] Characterizing and Detecting Malicious Crowdsourcing
    Wang, Tianyi
    Wang, Gang
    Li, Xing
    Zheng, Haito
    Zhao, Ben Y.
    [J]. ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2013, 43 (04) : 537 - 538
  • [10] Detecting Malicious Packet Losses
    Mizrak, Alper T.
    Savage, Stefan
    Marzullo, Keith
    [J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2009, 20 (02) : 191 - 206