Results 221 to 230 of about 11,445 (258)
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Robust Intrusion Detection in Dynamic Networks
2019 IEEE Conference on Control Technology and Applications (CCTA), 2019This paper considers the problem of robustly identifying m intruders in a network consisting of n cooperative agents which are subject to unknown disturbances. First, a distributed system model is introduced so that the relationship between agents, the attacks and unknown disturbances can be captured.
Sam Nazari +2 more
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Virtualization in Network Intrusion Detection Systems
2009This research work has focussed on analysing the efficacy of the virtualization concept for Network Intrusion Detection Systems (NIDS) in the high-speed environment. We have selected an open source NIDS, Snort for evaluation. Snort has been evaluated on virtual systems built on Windows XP SP2, Linux 2.6 and Free BSD 7.1 platforms.
Monis Akhlaq +5 more
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On network intrusion detection for deployment in the wild
2012 IEEE Network Operations and Management Symposium, 2012As the number of network-based attacks continue to increase, network operations and management tasks become more and more complex. As we have come to depend on reliable operations of networked systems, it is important to be able to provide security measures that both efficient in terms of processing speed as well as in detecting attacks that are not in
Sun-il Kim +4 more
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Self-Learning Network Intrusion Detection
it - Information Technology, 2011Zusammenfassung Services in the Internet are confronted with a growing amount and diversity of network attacks. Regular instruments of computer security increasingly fail to fend off this threat, as they rely on the manual generation of detection patterns and lack protection from unknown threats.
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Active learning for network intrusion detection
Proceedings of the 2nd ACM workshop on Security and artificial intelligence, 2009Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere enclosing network data, mapped to a vector space, such that points outside of the ball are considered anomalous.
Görnitz, Nico +3 more
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Honeypot Utilization for Network Intrusion Detection
2018For research purposes, a honeypot is a system that enables observing attacker’s actions in different phases of a cyberattack. In this study, a honeypot called Kippo was used to identify attack behavior in Finland. The gathered data consisted of dictionary attack login attempts, attacker location, and actions after successful login.
Simo Kemppainen, Tiina Kovanen
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The sound of intrusion: A novel network intrusion detection system
Computers and Electrical Engineering, 2022Mohammed Aldarwbi +2 more
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Autoencoder ensembles for network intrusion detection
2022 24th International Conference on Advanced Communication Technology (ICACT), 2022Chun Long +5 more
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Machine learning for Network Intrusion Detection
2020Rapidly advancing cyber technologies have been assisting threat actors in offensive cyber operations since the creation of computers, computer networks and computerized control systems. Exponentially evolving infiltration techniques and publicly available hacking tools facilitate implementation of attacks and increase their variability.
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Detection of Network Intrusions Using Anomaly Detection
2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA), 2023André Manuel Macedo +1 more
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