Abstract
Database mining can be defined as the process of mining for implicit, previously unknown, and potentially useful information from very large databases by efficient knowledge discovery techniques. Naturally such a process may open up new inference channels, detect new intrusion patterns, and raises new security problems. New security concern and research problems are addressed and identified. Finally a particularly well developed theory, rough set theory, is discussed and some potential applications to security problems are illustrated.
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Pawlak, Z. (1990). Rough sets. Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, 1992
Lin, T. Y. (1994), “Anamoly Detection — A Soft Computing Approach”, Proceedings in the ACM SIGSAC New Security Paradigm Workshop, Aug 3–5, 1994,44–53. This paper reappeared in the Proceedings of 1994 National Computer Security Center Conference under the title “Fuzzy Patterns in data”.
Lin, T. Y. (1993), “Rough Patterns in Data-Rough Sets and Intrusion Detection Systems”, Journal of Foundation of Computer Science and Decision Support, Vol.18, No. 3–4, 1993. pp. 225–241. The extended version of “Patterns in Data-Rough Sets and Foundation of Intrusion Detection Systems” presented at the First Invitational Workshop on Rough Sets, PoznanKiekrz, September 2–4. 1992.
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© 1996 IFIP International Federation for Information Processing
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Lin, T.Y., Hinke, T.H., Marks, D.G., Thuraisingham, B. (1996). Security and Data Mining. In: Spooner, D.L., Demurjian, S.A., Dobson, J.E. (eds) Database Security IX. IFIP Advances in Information and Communication Technology. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-34932-9_25
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DOI: https://doi.org/10.1007/978-0-387-34932-9_25
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-5041-2954-1
Online ISBN: 978-0-387-34932-9
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