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Game-theoretic decision support for cyber forensic investigations

Game-theoretic decision support for cyber forensic investigations

Nisioti, Antonia, Loukas, George ORCID: 0000-0003-3559-5182, Rass, Stefan and Panaousis, Emmanouil ORCID: 0000-0001-7306-4062 (2021) Game-theoretic decision support for cyber forensic investigations. Sensors, 21 (16):5300. ISSN 1424-8220 (doi:https://doi.org/10.3390/s21165300)

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Abstract

The use of anti-forensic techniques is a very common practice that stealthy adversaries may deploy to minimise their traces and make the investigation of an incident harder by evading detection and attribution. In this paper, we study the interaction between a cyber forensic Investigator and a strategic Attacker using a game-theoretic framework. This is based on a Bayesian game of incomplete information played on a multi-host cyber forensics investigation graph of actions traversed by both players. The edges of the graph represent players’ actions across different hosts in a network. In alignment with the concept of Bayesian games, we define 8 two Attacker types to represent their ability of deploying anti-forensic techniques to conceal their activities. In this way, our model allows the Investigator to identify her optimal investigating 10 policy taking into consideration the cost and impact of the available actions, while coping with the uncertainty of the Attacker’s type and strategic decisions. To evaluate our model, we construct a realistic case study based on threat reports and data extracted from the MITRE ATT&CK STIX repository, Common Vulnerability Scoring System (CVSS), and interviews with cyber-security practitioners. We use the case study to compare the performance of the proposed method against 15 two other investigative methods and three different types of Attackers.

Item Type: Article
Uncontrolled Keywords: cyber forensics; digital forensics; game theory; bayesian game; multi-stage attacks; decision support; optimisation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Faculty / School / Research Centre / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Internet of Things and Security (ISEC)
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CMS)
Last Modified: 23 Sep 2021 14:25
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/33601

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