Intrusion detection with neural networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Temporal sequence learning and data reduction for anomaly detection
ACM Transactions on Information and System Security (TISSEC)
Applying data mining to intrusion detection: the quest for automation, efficiency, and credibility
ACM SIGKDD Explorations Newsletter
Mining intrusion detection alarms for actionable knowledge
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
ADMIT: anomaly-based data mining for intrusions
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Statistical Identification of Encrypted Web Browsing Traffic
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Clustering intrusion detection alarms to support root cause analysis
ACM Transactions on Information and System Security (TISSEC)
Behavioral Authentication of Server Flows
ACSAC '03 Proceedings of the 19th Annual Computer Security Applications Conference
HMM profiles for network traffic classification
Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security
Intrusion detection via analysis and modelling of user commands
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
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Traffic analysis is an important issue for network monitoring and security. We focus on identifying protocols for network traffic by analysing the size, timing and direction of network packets. By using these network stream characteristics, we propose a technique for modelling the behaviour of various TCP protocols. This model can be used for recognising protocols even when running under encrypted tunnels. This is complemented with experimental evaluation on real world network data.