A Taxonomy of Malicious Traffic for Intrusion Detection Systems

June 09, 2018 ยท The Cartographer ยท ๐Ÿ› 2018 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA)

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Taxonomy of Malicious Traffic for Intrusion Detection Systems"

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Authors Hanan Hindy, Elike Hodo, Ethan Bayne, Amar Seeam, Robert Atkinson, Xavier Bellekens arXiv ID 1806.03516 Category cs.CR: Cryptography & Security Citations 15 Venue 2018 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA) Last Checked 2 days ago
Abstract
With the increasing number of network threats it is essential to have a knowledge of existing and new network threats in order to design better intrusion detection systems. In this paper we propose a taxonomy for classifying network attacks in a consistent way, allowing security researchers to focus their efforts on creating accurate intrusion detection systems and targeted datasets.
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