A System for Formal Digital Forensic Investigation Aware of Anti-Forensic Attacks

被引:21
|
作者
Rekhis, Slim [1 ]
Boudriga, Noureddine [1 ]
机构
[1] Univ Carthage, Commun Networks & Secur Res Lab, Ariana 2083, Tunisia
关键词
Anti-forensic attacks investigation; formal attack scenarios reconstruction; inference system;
D O I
10.1109/TIFS.2011.2176117
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
To defeat the process of investigation and make the analysis and reconstruction of attack scenarios difficult, challenging, or even impossible, attackers are motivated by conducting anti-forensic attacks. Several methods were proposed by the literature to formally reconstruct the sequence of events executed during the incident using theoretical and scientifically proven methods. However, these methods are not tailored to cope with anti-forensic attacks, as they assume that the collected evidence is trusted, do not model anti-forensic actions, and do not characterize provable anti-forensic attacks based on the knowledge of attacks, security solutions, and forms of evidence expected to be generated. We develop in this work a theoretical approach of digital investigation aware of anti-forensic attacks. After describing an investigation process which is able to address these attacks, we develop a state-based logic to describe the investigated system, the deployed security solution, the evidence they provide, and the library of attacks. An inference system is proposed to mitigate anti-forensic attacks and generate potential scenarios starting from traces that were targeted by these attacks. To exemplify the proposal, we provide a case study related to the investigation of an incident that exhibited anti-forensic attacks.
引用
收藏
页码:635 / 650
页数:16
相关论文
共 50 条
  • [1] A Hierarchical Visibility theory for formal digital investigation of anti-forensic attacks
    Rekhis, Slim
    Boudriga, Noureddine
    [J]. COMPUTERS & SECURITY, 2012, 31 (08) : 967 - 982
  • [2] Digital Image Forensic Approach to Counter the JPEG Anti-Forensic Attacks
    Kumar, Amit
    Singh, Gurinder
    Kansal, Ankush
    Singh, Kulbir
    [J]. IEEE ACCESS, 2021, 9 : 4364 - 4375
  • [3] An Approach for Validation of Digital Anti-Forensic Evidence
    Shanmugam, Karthikeyan
    Powell, Roger
    Owens, Tom
    [J]. INFORMATION SECURITY JOURNAL, 2011, 20 (4-5): : 219 - 230
  • [4] ANTI-FORENSIC THREAT MODELING
    Hoelz, Bruno
    Maues, Marcelo
    [J]. ADVANCES IN DIGITAL FORENSICS XIII, 2017, 511 : 169 - 183
  • [5] Performance of Blind Microphone Recognition Algorithms in the Presence of Anti-Forensic Attacks
    Hafeez, Azeem
    Malik, Hafiz
    Mahmood, Khalid
    [J]. 2017 AES INTERNATIONAL CONFERENCE ON AUDIO FORENSICS, 2017,
  • [6] Noninvasive Detection of Anti-Forensic Malware
    Guri, Mordehai
    Kedma, Gabi
    Sela, Tom
    Carmeli, Buky
    Rosner, Amit
    Elovici, Yuval
    [J]. PROCEEDINGS OF THE 2013 8TH INTERNATIONAL CONFERENCE ON MALICIOUS AND UNWANTED SOFTWARE: THE AMERICAS (MALWARE), 2013, : 1 - 10
  • [7] A framework for the identification of suspicious packets to detect anti-forensic attacks in the cloud environment
    Rani, Deevi Radha
    Geethakumari, G.
    [J]. PEER-TO-PEER NETWORKING AND APPLICATIONS, 2021, 14 (04) : 2385 - 2398
  • [8] Anti-forensic resilient memory acquisition
    Stuettgen, Johannes
    Cohen, Michael
    [J]. DIGITAL INVESTIGATION, 2013, 10 : S105 - S115
  • [9] DETECTING ANTI-FORENSIC ATTACKS ON DEMOSAICING-BASED CAMERA MODEL IDENTIFICATION
    Chen, Chen
    Zhao, Xinwei
    Stamm, Matthew C.
    [J]. 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2017, : 1512 - 1516
  • [10] A framework for the identification of suspicious packets to detect anti-forensic attacks in the cloud environment
    Rani, Deevi Radha
    Geethakumari, G.
    [J]. PEER-TO-PEER NETWORKING AND APPLICATIONS, 2020,