Anomaly-Based Network Intrusion Detection Using Outlier Subspace Analysis: A Case Study

被引：0
|
作者：
Kershaw, David [1 ]
Gao, Qigang [1 ]
Wang, Hai [2 ]
机构：
[1] Dalhousie Univ, Fac Comp Sci, Halifax, NS B3H 3J5, Canada
[2] St Marys Univ, Sobey Sch Business, San Antonio, TX 78228 USA
来源：
ADVANCES IN ARTIFICIAL INTELLIGENCE | 2011年 / 6657卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper employs SPOT (Stream Projected Outlier deTector) as a prototype system for anomaly-based intrusion detection and evaluates its performance against other major methods. SPOT is capable of processing high-dimensional data streams and detecting novel attacks which exhibit abnormal behavior, making it a good candidate for network intrusion detection. This paper demonstrates SPOT is effective to distinguish between normal and abnormal processes in a UNIX System Call dataset.
引用
收藏
页码：234 / 239
页数：6
相关论文
共 50 条
  • [41] Analysis of anomaly-based intrusion detection techniques for mobile wireless networks
    Liu, Lijun
    Ma, Hongxia
    Liu, Jianqiu
    Li, Zhuowei
    2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES: ITESS 2008, VOL 2, 2008, : 827 - 832
  • [42] A systematic literature review of methods and datasets for anomaly-based network intrusion detection
    Yang, Zhen
    Liu, Xiaodong
    Li, Tong
    Wu, Di
    Wang, Jinjiang
    Zhao, Yunwei
    Han, Han
    COMPUTERS & SECURITY, 2022, 116
  • [43] Game Theoretical Method for Anomaly-Based Intrusion Detection
    Wang, Zhiyong
    Xu, Shengwei
    Xu, Guoai
    Yin, Yongfeng
    Zhang, Miao
    Sun, Dawei
    SECURITY AND COMMUNICATION NETWORKS, 2020, 2020
  • [44] How Much Training Data is Enough? A Case Study for HTTP Anomaly-Based Intrusion Detection
    Estepa, Rafael
    Diaz-Verdejo, Jesus E.
    Estepa, Antonio
    Madinabeitia, German
    IEEE ACCESS, 2020, 8 (44410-44425) : 44410 - 44425
  • [45] SCADA Networks Anomaly-based Intrusion Detection System
    Almehmadi, Abdulaziz
    11TH INTERNATIONAL CONFERENCE ON SECURITY OF INFORMATION AND NETWORKS (SIN 2018), 2018,
  • [46] Anomaly-Based Intrusion Detection Algorithms for Wireless Networks
    Fragkiadakis, Alexandros G.
    Siris, Vasilios A.
    Petroulakis, Nikolaos
    WIRED-WIRELESS INTERNET COMMUNICATIONS, PROCEEDINGS, 2010, 6074 : 192 - 203
  • [47] Anomaly-based Intrusion Detection System for smart lighting
    Lara, Agustin
    Estepa, Antonio
    Estepa, Rafael
    Diaz-Verdejo, Jesus E.
    Mayor, Vicente
    INTERNET OF THINGS, 2024, 28
  • [48] Feature Selection for Effective Anomaly-Based Intrusion Detection
    Ghali, Noreen I.
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2009, 9 (03): : 285 - 289
  • [49] Anomaly-based intrusion detection system for IoT application
    Bhavsar M.
    Roy K.
    Kelly J.
    Olusola O.
    Discover Internet of Things, 2023, 3 (01):
  • [50] Fed-ANIDS: Federated learning for anomaly-based network intrusion detection systems
    Idrissi, Meryem Janati
    Alami, Hamza
    El Mahdaouy, Abdelkader
    El Mekki, Abdellah
    Oualil, Soufiane
    Yartaoui, Zakaria
    Berrada, Ismail
    EXPERT SYSTEMS WITH APPLICATIONS, 2023, 234
12345