Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Jan Stiborek"'
Publikováno v:
Computers & Security. 74:221-239
We propose a method to automatically group unknown binaries executed in sandbox according to their interaction with system resources (files on the filesystem, mutexes, registry keys, network communication with remote servers and error messages genera
Publikováno v:
IEEE Intelligent Systems. 31:16-22
Malware authors and operators typically collaborate to achieve the optimal profit. They also frequently change their behavior and resources to avoid detection. The authors propose a social similarity metrics that exploits these relationships to impro
Publikováno v:
Computers & Security. 45:100-123
The results of botnet detection methods are usually presented without any comparison. Although it is generally accepted that more comparisons with third-party methods may help to improve the area, few papers could do it. Among the factors that preven
Publikováno v:
IEEE Intelligent Systems. 24:16-25
Individual anomaly-detection methods for monitoring computer network traffic have relatively high error rates. An agent-based trust-modeling system fuses anomaly data and progressively improves classification to achieve acceptable error rates.
Publikováno v:
Transactions on Computational Collective Intelligence XV ISBN: 9783662447499
We present a self-adaptation mechanism for network intrusion detection system based on the use of game-theoretical formalism. The key innovation of our method is a secure runtime definition and solution of the game and real-time use of game solutions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0db6c4b7b18ef7b29dea8d8b62832b4d
https://doi.org/10.1007/978-3-662-44750-5_7
https://doi.org/10.1007/978-3-662-44750-5_7
Publikováno v:
Transactions on Computational Collective Intelligence XV ISBN: 9783662447499
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76ca9d1733d8503c1f4f1e23391550d6
https://doi.org/10.1007/978-3-662-45910-2_7
https://doi.org/10.1007/978-3-662-45910-2_7
Publikováno v:
Advances in Intelligent and Soft Computing ISBN: 9783642287855
PAAMS
PAAMS
We present a self-adaptation mechanism for Network Intrusion Detection System which uses a game-theoretical mechanism to increase system robustness against targeted attacks on IDS adaptation. This system has been used to ensure the robustness of comm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91221fc9f8fa8a6c00afaa480a4c11ce
https://doi.org/10.1007/978-3-642-28786-2_40
https://doi.org/10.1007/978-3-642-28786-2_40
Publikováno v:
2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.
We present an empirical study of distributed adaptation in an Intrusion Detection System. The adaptation model is based on a game-theoretical approach and we use regret minimization techniques to find globally robust behavior. We compare the effectiv
Publikováno v:
CICS
We present an empirical study of regret minimization procedure used in a distributed Intrusion Detection System (IDS) to independently adapt the self-contained components of the system without any explicit coordination. We show that the regret minimi
Autor:
Thomas Engel, Eugen Staab, Martin Rehak, Jan Stiborek, Michal Pechoucek, Volker Fusenig, Karel Bartos, Martin Grill
Publikováno v:
ICAC
We present a mechanism for autonomous self-adaptation of a network-based intrusion detection system (IDS). The system is composed of a set of cooperating agents, each of which is based on an existing network behavior analysis method. The self adaptat