Intrusion Detection System using datamining techniques - Puthran, Shubha;Shah, Ketan
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Security is a big issue for all networks including defense and government infrastructure. Attacks on network infrastructure are threats against the information security. The Intrusion detection system (IDS) is one that scans incoming data activities and attempt to detect the intrusions. The classification algorithms in IDS are used to categorize the well known large variety of intrusions. In recent years, data mining based IDS have executed good performance. Still challenges exist in the design and implementation of quality IDSs. The goal of this classification and clustering based IDS system…mehr

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Produktbeschreibung
Security is a big issue for all networks including defense and government infrastructure. Attacks on network infrastructure are threats against the information security. The Intrusion detection system (IDS) is one that scans incoming data activities and attempt to detect the intrusions. The classification algorithms in IDS are used to categorize the well known large variety of intrusions. In recent years, data mining based IDS have executed good performance. Still challenges exist in the design and implementation of quality IDSs. The goal of this classification and clustering based IDS system is to decrease the False alarm rates and increase the accuracy.
Autorenporträt
Prof.Shubha Puthran is M.Tech in Computer Engineering from MPSTME, NMIMS University. B.E in Computer Engineering from M.I.T, Manipal, Mangalore University. She has 9 Papers in national/International Conference, Journals and Posters to her credit. She is Asst.Professor in MPSTME, NMIMS University. She is life time member of ISTE.