Detection Model for Cyber Attacks-Application of Data Mining

ISBN-13: 9786203042290 / Angielski / Miękka / 52 str.

Amruta Surana

Opis

Intrusion detection systems (IDS) are important elements in network defenses to help protect against increasingly sophisticated cyber attacks. This project objective presents a novel anomaly detection technique that can be used to detect previously unknown attacks on a network by identifying attack features. This effects-based feature identification method uniquely combines k-means clustering; NaiveBayes feature selection and C4.5 decision tree classification for finding cyber attacks with a high degree of accuracy and it used KDD99CUP dataset as input. Basically it detects whether the attacks are there or not, like IPSWEEP, NEPTUNE, SMURF.

O autorze

Surana, Amruta Prof. Amruta Surana holds a Master of engineering in computer science. She is currently pursuing her PHD in Computer Engineering from Poornima University Jaipur. She has more than 9 years of teaching experience. Currently associated with Nutan Maharashtra Institute of Engineering and Technology, Talegaon Dabhade.