Results 211 to 220 of about 11,445 (258)

Network Intrusion Detection in Encrypted Traffic

2022 IEEE Conference on Dependable and Secure Computing (DSC), 2022
Traditional signature-based intrusion detection systems inspect packet headers and payloads to report any malicious or abnormal traffic behavior that is observed in the network. With the advent and rapid adoption of network encryption mechanisms, typical deep packet inspection systems that monitor network packet payload contents are becoming less ...
Papadogiannaki, Eva, Tsirantonakis, Giorgos, Ioannidis, Sotiris   +2 more
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Attribute Normalization in Network Intrusion Detection

2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks, 2009
Anomaly intrusion detection is an important issue in computer network security. As a step of data preprocessing, attribute normalization is essential to detection performance. However, many anomaly detection methods do not normalize attributes before training and detection.
Wei Wang 0012, Xiangliang Zhang 0001, Sylvain Gombault, Svein J. Knapskog   +3 more
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Network intrusion detection

Proceedings of the 26th Annual Computer Security Applications Conference, 2010
Research on network intrusion detection has produced a number of interesting results. In this paper, I look back to the NetSTAT system, which was presented at ACSAC in 1998. In addition to describing the original system, I discuss some historical context, with reference to well-known evaluation efforts and to the evolution of network intrusion ...
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Network Traffic Intrusion Detection

2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
The paper explores the application of machine learning algorithms for network traffic intrusion detection with the aim of enhancing the security of information systems. More specifically, it provides a comprehensive insight into the current state of the art in intrusion detection, and gives a review of relevant literature, research methodology ...
Frane Zada, Martina Antonic
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Neural network approach for intrusion detection

Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human, 2009
Intrusion Detection System is based on the belief that an intruder's behavior will be noticeably different from that of a legitimate user and would exploit security vulnerabilities. This paper proposes a neural network approach to improve the alert throughput of a network and making it attack prohibitive using IDS.
Amit Kumar Choudhary, Akhilesh Swarup
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ULISSE, a network intrusion detection system

Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead, 2008
In this paper we present a tool for network anomaly detection and network intelligence which we named ULISSE. It uses a two tier architecture with unsupervised learning algorithms to perform network intrusion and anomaly detection. ULISSE uses a combination of clustering of packet payloads and correlation of anomalies in the packet stream.
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Network Intrusion Detection

2015
With the developing of Internet, network intrusion has becoming more and more common.Extreme learning machine (ELM) is an efficient learning algorithm for generalized single hidden layer feed-forward networks. ELM can be used for network intrusion detection.This work introduces a method using extreme learning machine to detect network intrusion.
Zhifan Ye, Yuanlong Yu
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Intelligent system for detection of networking intrusion

Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2011
A modified neural detector and a method of principal components analysis were considered to improve a quality of network attacks detection.
Myroslav Komar, Vladimir A. Golovko, Anatoly Sachenko, Sergei V. Bezobrazov   +3 more
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Integrating intrusion detection and network management

NOMS 2002. IEEE/IFIP Network Operations and Management Symposium. ' Management Solutions for the New Communications World'(Cat. No.02CH37327), 2003
The problems of detecting and resolving performance in distributed systems have become increasingly important and challenging due to the tremendous growth in network-based services. There is a need for a predictive and proactive approach so that appropriate and timely actions can be taken before service disruptions escalate and become widespread.
Xinzhou Qin, Wenke Lee, Lundy M. Lewis, João B. D. Cabrera   +3 more
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Visualizing network traffic for intrusion detection

Proceedings of the 6th conference on Designing Interactive systems, 2006
Intrusion detection, the process of using network data to identify potential attacks, has become an essential component of information security. Human analysts doing intrusion detection work utilize vast amounts of data from disparate sources to make decisions about potential attacks. Yet, there is limited understanding of this critical human component.
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