Mdlcompress for intrusion detection: Signature inference and masquerade attack

被引:0
|
作者
Evans, Scott [1 ]
Eiland, Earl [1 ]
Markham, Stephen [1 ]
Impson, Jeremy [2 ]
Laczo, Adam [2 ]
机构
[1] GE Res, New York, NY USA
[2] Lockheed Martin Corp, Owego, NY USA
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
MDLcompress is a grammar inference algorithm that uses Minimum Description Length principles from the theory of Kolmogorov Complexity and Algorithmic Information Theory to infer a grammar, finding patterns and motifs that aid most in compressing unknown data sets. This technology has been applied to detection of FTP exploits and inference of DNA sequence motifs related to breast cancer. In this paper we apply MDLcompress to infer grammars, and then apply those grammars to identify masquerades in the publicly available Schonlau system call data sets. Compared to similar protocols our system detects anomalous events with comparable performance with the advantage of executing in linear time.
引用
收藏
页码:1652 / +
页数:2
相关论文
共 50 条
  • [41] DOS intrusion attack detection by Using of Improved SVR
    Hosseini, Zohreh Sadat
    Mahdavi, Seyyed Javad Seyyed
    Kamel, Seyyed Reza
    SECOND INTERNATIONAL CONGRESS ON TECHNOLOGY, COMMUNICATION AND KNOWLEDGE (ICTCK 2015), 2015, : 159 - 164
  • [42] Design of Intrusion Detection System for Wormhole Attack Detection in Internet of Things
    Deshmukh-Bhosale, Snehal
    Sonavane, S. S.
    ADVANCED COMPUTING AND INTELLIGENT ENGINEERING, 2020, 1082 : 513 - 523
  • [43] An Authorized Access Attack Detection Method for Realtime Intrusion Detection System
    Youm, Sungkwan
    Kim, Yong-Kab
    Shin, Kwang-Seong
    Kim, Eui-Jik
    2020 IEEE 17TH ANNUAL CONSUMER COMMUNICATIONS & NETWORKING CONFERENCE (CCNC 2020), 2020,
  • [44] Attack Detection Capabilities of Intrusion Detection Systems for Wireless Sensor Networks
    Darra, Eleni
    Katsikas, Sokratis K.
    2013 FOURTH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS AND APPLICATIONS (IISA 2013), 2013, : 91 - 97
  • [45] An Intrusion Detection System for Denial of Service Attack Detection in Internet of Things
    Lira Melo Sousa, Breno Fabricio
    Abdelouahab, Zair
    Pavao Lopes, Denivaldo Cicero
    Soeiro, Natalia Costa
    Ribeiro, Willian Franca
    PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, DATA AND CLOUD COMPUTING (ICC 2017), 2017,
  • [46] Detection and Update Method for Attack Behavior Models in Intrusion Detection Systems
    Bin Ahmadon, Mohd Anuaruddin
    Yamaguchi, Shingo
    Gou, Zhaolong
    Gupta, B. B.
    PROCEEDINGS OF THE 10TH INDIACOM - 2016 3RD INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT, 2016, : 2119 - 2124
  • [47] Data Mining based CIDS: Cloud Intrusion Detection System for Masquerade Attacks [DCIDSM]
    Pratik, Jain P.
    Madhu, B. R.
    2013 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATIONS AND NETWORKING TECHNOLOGIES (ICCCNT), 2013,
  • [48] Quantifying the Attack Detection Accuracy of Intrusion Detection Systems in Virtualized Environments
    Milenkoski, Aleksandar
    Jayaram, K. R.
    Antunes, Nuno
    Vieira, Marco
    Kounev, Samuel
    2016 IEEE 27TH INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING (ISSRE), 2016, : 276 - 286
  • [49] Effective intrusion detection model through the combination of a signature-based intrusion detection system and a machine learning-based intrusion detection system
    Weon, Ill-Young
    Song, Doo Heon
    Lee, Chang-Hoon
    JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2006, 22 (06) : 1447 - 1464
  • [50] Multi-agent technologies for computer network security: Attack simulation, intrusion detection and intrusion detection learning
    Gorodetski, V
    Kotenko, I
    Karsaev, O
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2003, 18 (04): : 191 - 200