Dependable security: testing network intrusion detection systems
HotDep'07 Proceedings of the 3rd workshop on on Hot Topics in System Dependability
Using Artificial Intelligence for Intrusion Detection
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Using Contextual Information for IDS Alarm Classification (Extended Abstract)
DIMVA '09 Proceedings of the 6th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment
Plug & execute framework for network traffic generation
Proceedings of the Sixth Annual Workshop on Cyber Security and Information Intelligence Research
Proceedings of the First Workshop on Building Analysis Datasets and Gathering Experience Returns for Security
A hybrid approach to operating system discovery based on diagnosis
International Journal of Network Management
Tunable immune detectors for behaviour-based network intrusion detection
ICARIS'11 Proceedings of the 10th international conference on Artificial immune systems
Methods for testing network-intrusion detection systems
Scientific and Technical Information Processing
Model-driven, network-context sensitive intrusion detection
MODELS'07 Proceedings of the 10th international conference on Model Driven Engineering Languages and Systems
Adversarial attacks against intrusion detection systems: Taxonomy, solutions and open issues
Information Sciences: an International Journal
Administrative evaluation of intrusion detection system
Proceedings of the 2nd annual conference on Research in information technology
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An Intrusion Detection System (IDS) is a crucial element of a network security posture. Although there are many IDS products available, it is rather difficult to find information about their accuracy. Only a few organizations evaluate these products. Furthermore, the data used to test and evaluate these IDS is usually proprietary. Thus, the research community cannot easily evaluate the next generation of IDS. Toward this end, DARPA provided in 1998, 1999 and 2000 an Intrusion Detection Evaluation Data Set. However, no new data set has been released by DARPA since 2000, in part because of the cumbersomeness of the task. In this paper, we propose a strategy to address certain aspects of generating a publicly available documented data set for testing and evaluating intrusion detection systems. We also present a tool that automatically analyzes and evaluates IDS using our proposed data set.