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Bayesian active malware analysis

Sartea Riccardo, Chalkiadakis Georgios, Farinelli Alessandro, Murari Matteo

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/C261F0BB-A07D-45B8-8B7F-7DFD52339A08-
Αναγνωριστικόhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85096654979&partnerID=40&md5=77bfe04749005b25eff5436afb3fe0dd-
Αναγνωριστικόwww.ifaamas.org/proceedings.html-
Αναγνωριστικό978-145037518-4-
Γλώσσαen-
Μέγεθος9 pagesen
ΤίτλοςBayesian active malware analysisen
ΔημιουργόςSartea Riccardoen
ΔημιουργόςChalkiadakis Georgiosen
ΔημιουργόςΧαλκιαδακης Γεωργιοςel
ΔημιουργόςFarinelli Alessandroen
ΔημιουργόςMurari Matteoen
ΕκδότηςInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)en
ΠερίληψηWe propose a novel technique for Active Malware Analysis (AMA) formalized as a Bayesian game between an analyzer agent and a malware agent, focusing on the decision making strategy for the analyzer. In our model, the analyzer performs an action on the system to trigger the malware into showing a malicious behavior, i.e., by activating its payload. The formalization is built upon the link between malware families and the notion of types in Bayesian games. A key point is the design of the utility function, which reflects the amount of uncertainty on the type of the adversary after the execution of an analyzer action. This allows us to devise an algorithm to play the game with the aim of minimizing the entropy of the analyzer’s belief at every stage of the game in a myopic fashion. Empirical evaluation indicates that our approach results in a significant improvement both in terms of learning speed and classification score when compared to other state-of-the-art AMA techniques.en
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2022-07-26-
Ημερομηνία Δημοσίευσης2020-
Θεματική ΚατηγορίαMalwareen
Θεματική ΚατηγορίαAutonomous agentsen
Θεματική ΚατηγορίαMulti agent systemsen
Θεματική ΚατηγορίαDecision makingen
Βιβλιογραφική ΑναφοράR. Sartea, G. Chalkiadakis, A. Farinelli, and M. Murari, “Bayesian active malware analysis,” In Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), vol 2020, B. An, N. Yorke-Smith, A. El Fallah Seghrouchni, G. Sukthankar, Eds., USA: IFAAMAS, 2020, pp. 1206 - 1214.en

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