Zobrazeno 1 - 10
of 260
pro vyhledávání: '"Charles A. Kamhoua"'
Autor:
Priva Chassem Kamdem, Alain B. Zemkoho, Laurent Njilla, Marcellin Nkenlifack, Charles A. Kamhoua
Publikováno v:
IEEE Access, Vol 12, Pp 171559-171570 (2024)
Cyber-physical systems (CPS) are increasingly vulnerable to sophisticated cyber-attacks that can target multiple layers within the system. To strengthen defenses against these complex threats, deception-based techniques have emerged as a promising so
Externí odkaz:
https://doaj.org/article/cdaa03326af64fec980452af7bbff1b2
Autor:
Fabrice Setephin Atedjio, Jean-Pierre Lienou, Frederica F. Nelson, Sachin S. Shetty, Charles A. Kamhoua
Publikováno v:
IEEE Access, Vol 12, Pp 169432-169441 (2024)
Due to the popularity of Android mobile devices over the past ten years, malicious Android applications have significantly increased. Systems utilizing machine learning techniques have been successfully applied for Android malware detection to counte
Externí odkaz:
https://doaj.org/article/9fa1039004f747c8a292c8b40fca3669
Autor:
Fabrice Setephin Atedjio, Jean-Pierre Lienou, Frederica F. Nelson, Sachin S. Shetty, Charles A. Kamhoua
Publikováno v:
IEEE Access, Vol 12, Pp 162685-162696 (2024)
Adversarial attacks pose significant threats to Android malware detection by undermining the effectiveness of machine learning-based systems. The rapid increase in Android apps complicates the management of malicious software that can compromise user
Externí odkaz:
https://doaj.org/article/6c702a9e703944e6b8adeb5b7dd9c758
Publikováno v:
IEEE Transactions on Network and Service Management. 19:3438-3452
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::10316b3f10313f7117f3343933ef08eb
https://doi.org/10.1109/tnsm.2022.3179965
https://doi.org/10.1109/tnsm.2022.3179965
Publikováno v:
2023 57th Annual Conference on Information Sciences and Systems (CISS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::886ba503a20cd43e305399e9472f9992
https://doi.org/10.1109/ciss56502.2023.10089630
https://doi.org/10.1109/ciss56502.2023.10089630
Publikováno v:
IEEE Transactions on Network and Service Management. 19:112-129
Defensive deception techniques have emerged as a promising proactive defense mechanism to mislead an attacker and thereby achieve attack failure. However, most game-theoretic defensive deception approaches have assumed that players maintain consisten
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48f3bb8bcaa7ea560ad4180b713e9a9b
https://doi.org/10.1109/tnsm.2021.3117698
https://doi.org/10.1109/tnsm.2021.3117698
Publikováno v:
2023 International Conference on Computing, Networking and Communications (ICNC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::280a27bbbe796a9d3c04699fe098c3c2
https://doi.org/10.1109/icnc57223.2023.10074241
https://doi.org/10.1109/icnc57223.2023.10074241
Publikováno v:
GLOBECOM 2022 - 2022 IEEE Global Communications Conference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e61a7b3a3ed9457369589afaab4fc70
https://doi.org/10.1109/globecom48099.2022.10000813
https://doi.org/10.1109/globecom48099.2022.10000813
Publikováno v:
Game Theory and Machine Learning for Cyber Security
In this chapter, we introduce a cyber deception defense approach and propose a scalable allocation algorithm to place honeypots over an attack graph. We formulate a two‐person zero‐sum strategic game between the network defender and an attacker.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85f2f8be13108bd73d0979b7a0c97af8
https://doi.org/10.1002/9781119723950.ch4
https://doi.org/10.1002/9781119723950.ch4
Publikováno v:
Game Theory and Machine Learning for Cyber Security. :1-19
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d353820fc2c1504e6b8eef72ccd3682
https://doi.org/10.1002/9781119723950.ch1
https://doi.org/10.1002/9781119723950.ch1