Open Access
INTRUSION DETECTION SYSTEM USING KDD'99 CUP DATASET
Author(s) -
Satyendra Vishwakarma* Vivek Sharma
Publication year - 2017
Publication title -
zenodo (cern european organization for nuclear research)
Language(s) - English
DOI - 10.5281/zenodo.574456
Subject(s) - intrusion detection system , computer science , data mining , artificial intelligence , pattern recognition (psychology)
Today we are going up against with the issue of high dimensionality and outsized measure of information, network intrusion detection is always the focus of current research in the network security field. It is the spoiling of data security rules by pernicious exercises. Interruption discovery (ID) is a progression of strategies for distinguishing and perceiving incredulous activities that make the move acknowledgment of benchmarks of protection/classification, prominence, unwavering quality, and accessibility of a PC based system framework. The KDD Cup 99 dataset has been the purpose of fascination for some analysts in the field of interruption discovery from the most recent decade. Numerous scientists have contributed their endeavors to break down the dataset by various methods. It grants recognizing Denial of organization (DoS), User to root (U2R), Remote to login (R2L) and Probe assault. For the identification of interruption/dangers distinctive information mining calculation has been connected by different creators. In this paper, we present the literature study of the previous work done in the field of intrusion detection with their merits and demerits