A systematic survey on multi-step attack detection

被引:88
|
作者
Navarro, Julio [1 ,2 ]
Deruyver, Aline [1 ,2 ]
Parrend, Pierre [1 ,2 ,3 ]
机构
[1] Univ Strasbourg, ICube Lab, 300 Bd Sebastien Brant, F-67412 Illkirch Graffenstaden, France
[2] UNESCO Unitwin, Complex Syst Digital Campus, Paris, France
[3] ECAM Strasbourg Europe, 2 Rue Madrid, F-67300 Schiltigheim, France
关键词
Advanced persistent threat; Event correlation; Intrusion detection system; Multi-stage attack; Multi-step attack; Network security; INTRUSION DETECTION; ALERT CORRELATION; SITUATIONAL AWARENESS; REPRODUCIBLE RESEARCH; ALGORITHM; FRAMEWORK; MODELS; EVENT;
D O I
10.1016/j.cose.2018.03.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Since the beginning of the Internet, cyberattacks have threatened users and organisations. They have become more complex concurrently with computer networks. Nowadays, attackers need to perform several intrusion steps to reach their final objective. The set of these steps is known as multi-step attack, multi-stage attack or attack scenario. Their multi-step nature hinders intrusion detection, as the correlation of more than one action is needed to understand the attack strategy and identify the threat. Since the beginning of 2000s, the security research community has tried to propose solutions to detect this kind of threat and to predict further steps. This survey aims to gather all the publications proposing multi-step attack detection methods. We focus on methods that go beyond the detection of a symptom and try to reveal the whole structure of the attack and the links between its steps. We follow a systematic approach to bibliographic research in order to identify the relevant literature. Our effort results in a corpus of 181 publications covering 119 methods, which we describe and classify. The analysis of the publications allows us to extract some conclusions about the state of research in multi-step attack detection. As far as we know, this is the first survey fully dedicated to multi-step attack detection methods as mechanisms to reveal attack scenarios composed of digital traces left by attackers. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:214 / 249
页数:36
相关论文
共 50 条
  • [1] MAD: A Middleware Framework for Multi-Step Attack Detection
    Papadopoulos, Panagiotis
    Petsas, Thanasis
    Christou, Giorgos
    Vasiliadis, Giorgos
    [J]. 2015 4TH INTERNATIONAL WORKSHOP ON BUILDING ANALYSIS DATASETS AND GATHERING EXPERIENCE RETURNS FOR SECURITY (BADGERS), 2015, : 8 - 15
  • [2] Multi-layer episode filtering for the multi-step attack detection
    Soleimani, Mahbobeh
    Ghorbani, Ali A.
    [J]. COMPUTER COMMUNICATIONS, 2012, 35 (11) : 1368 - 1379
  • [3] Multi-Step Attack Pattern Detection on Normalized Event Logs
    Jaeger, David
    Ussath, Martin
    Cheng, Feng
    Meinel, Christoph
    [J]. 2015 IEEE 2nd International Conference on Cyber Security and Cloud Computing (CSCloud), 2015, : 390 - 398
  • [4] LActDet: An Automatic Network Attack Activity Detection Framework for Multi-step Attacks
    Yang, Huiran
    Kang, Jiaqi
    Dai, Yueyue
    Sun, Jiyan
    Zhang, Yan
    Cui, Huajun
    Ma, Can
    [J]. 2023 IEEE 22ND INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS, TRUSTCOM, BIGDATASE, CSE, EUC, ISCI 2023, 2024, : 676 - 685
  • [5] Multi-step attack detection in industrial control systems using causal analysis
    Jadidi, Zahra
    Hagemann, Joshua
    Quevedo, Daniel
    [J]. COMPUTERS IN INDUSTRY, 2022, 142
  • [6] Multi-Step Attack Detection Based on Pre-Trained Hidden Markov Models
    Zhang, Xu
    Wu, Ting
    Zheng, Qiuhua
    Zhai, Liang
    Hu, Haizhong
    Yin, Weihao
    Zeng, Yingpei
    Cheng, Chuanhui
    [J]. SENSORS, 2022, 22 (08)
  • [7] Multi-step attack detection in industrial networks using a hybrid deep learning architecture
    Jamal, Muhammad Hassan
    Khan, Muazzam A.
    Ullah, Safi
    Alshehri, Mohammed S.
    Almakdi, Sultan
    Rashid, Umer
    Alazeb, Abdulwahab
    Ahmad, Jawad
    [J]. MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2023, 20 (08) : 13824 - 13848
  • [8] A Multi-Step Attack Detection Model Based on Alerts of Smart Grid Monitoring System
    Zhang, Hua
    Jin, Xueqi
    Li, Ying
    Jiang, Zhengwei
    Liang, Ye
    Jin, Zhengping
    Wen, Qiaoyan
    [J]. IEEE ACCESS, 2020, 8 : 1031 - 1047
  • [9] RTECA: Real time episode correlation algorithm for multi-step attack scenarios detection
    Ramaki, Ali Ahmadian
    Amini, Morteza
    Atani, Reza Ebrahimi
    [J]. COMPUTERS & SECURITY, 2015, 49 : 206 - 219
  • [10] Foundations and applications of artificial Intelligence for zero-day and multi-step attack detection
    Parrend, Pierre
    Navarro, Julio
    Guigou, Fabio
    Deruyver, Aline
    Collet, Pierre
    [J]. EURASIP JOURNAL ON INFORMATION SECURITY, 2018,