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Cited by 381

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A network security monitor

Heberlein, L.T., Dias, G.V., Levitt, K.N., Mukherjee, B., Wood, J., Wolber, D.·1990·Proceedings. 1990 IEEE Computer Society Symposium on Research in Security and Privacy

Abstract

This study concentrates on the security-related issues in a single broadcast LAN (local area network) such as Ethernet. The authors formalize various possible network attacks. Their basic strategy is to develop profiles of usage of network resources and then compare current usage patterns with the historical profile to determine possible security violations. Thus, the work is similar to the host-based intrusion-detection systems. Different from such systems, however, is the use of a hierarchical model to refine the focus of the intrusion-detection mechanism. The authors also report on the development of an experimental LAN monitor currently under implementation. Several network attacks have been simulated, and results on how the monitor has been able to detect these attacks are analyzed. Initial results demonstrate that many network attacks are detectable with the authors' monitor, although it can be defeated.>

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Metadata

Authors
Heberlein, L. T., Dias, G. V., Levitt, K. N., Mukherjee, B., Wood, J., & Wolber, D.
Venue
Proceedings. 1990 IEEE Computer Society Symposium on Research in Security and Privacy
Publisher
IEEE
Published
1990
Pages
296-304
OpenAlex
W2117002131
Cited by
381
References
1
FWCI
0.69
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: A network security monitor. https://app.cochat.ai/papers/10.1109/risp.1990.63859
The paper
Heberlein, L. T., Dias, G. V., Levitt, K. N., Mukherjee, B., Wood, J., & Wolber, D. (1990). A network security monitor. Proceedings. 1990 IEEE Computer Society Symposium on Research in Security and Privacy. https://doi.org/10.1109/risp.1990.63859

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.