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Ιδρυματικό Αποθετήριο [SANDBOX]
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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| URI | http://purl.tuc.gr/dl/dias/C261F0BB-A07D-45B8-8B7F-7DFD52339A08 | - |
| Αναγνωριστικό | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096654979&partnerID=40&md5=77bfe04749005b25eff5436afb3fe0dd | - |
| Αναγνωριστικό | www.ifaamas.org/proceedings.html | - |
| Αναγνωριστικό | 978-145037518-4 | - |
| Γλώσσα | en | - |
| Μέγεθος | 9 pages | en |
| Τίτλος | Bayesian active malware analysis | en |
| Δημιουργός | Sartea Riccardo | en |
| Δημιουργός | Chalkiadakis Georgios | en |
| Δημιουργός | Χαλκιαδακης Γεωργιος | el |
| Δημιουργός | Farinelli Alessandro | en |
| Δημιουργός | Murari Matteo | en |
| Εκδότης | International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) | en |
| Περίληψη | We 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 |
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Full Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2022-07-26 | - |
| Ημερομηνία Δημοσίευσης | 2020 | - |
| Θεματική Κατηγορία | Malware | en |
| Θεματική Κατηγορία | Autonomous agents | en |
| Θεματική Κατηγορία | Multi agent systems | en |
| Θεματική Κατηγορία | Decision making | en |
| Βιβλιογραφική Αναφορά | R. 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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