Downloads: 111 | Views: 371 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1
M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 3 Issue 5, May 2014 | Popularity: 6.9 / 10
An Intrusion Detection Model for Detecting Type of Attack Using Data Mining
Amruta Surana, Shyam Gupta
Abstract: Intrusion detection systems (IDS) are important elements in a networks defenses to help protect against increasingly sophisticated cyber attacks. This project objective presents a novel anomaly detection technique that can b e u s e d to detect previously unknown attacks on a network by identifying attack features. This effects -based feature identification method uniquely combines k-means clustering; NaveBayes feature selection and 4.5 d e c i s i o n tree classification for finding cyber attacks with a high degree of accuracy and it used KDD99CUP dataset as input. Basically it detect whether this attacks are there or not like IPSWEEP; NEPTUNE; SMURF. Conclusions: Give brief concluding remarks on outcomes of what attacks are present and how to find.
Keywords: Clustering, Classification, Decision trees, Feature, selection, Intrusion detection
Edition: Volume 3 Issue 5, May 2014
Pages: 1496 - 1500
Please Disable the Pop-Up Blocker of Web Browser
Verification Code will appear in 2 Seconds ... Wait