Hits:

Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院

Journal:Lect. Notes Inst. Comput. Sci. Soc. Informatics Telecommun. Eng.

Abstract:In the recent time a huge number of public and commercial service is used through internet so that the vulnerabilities of current security systems have become the most important issue in the society and threats from hackers have also increased. Many researchers feel intrusion detection systems can be a fundamental line of defense. Intrusion Detection System (IDS) is used against network attacks for protecting computer networks. On another hand, data mining techniques can also contribute to intrusion detection. The intrusion detection has two fundamental classes, Anomaly based and Misuse based. One of the biggest problem with the anomaly base intrusion detection is detecting a high numbers of false alarms. In this paper a solution is provided to increase the attack recognition rate and a minimal false alarm generation is achieved with the study of different Tree-based data mining techniques. KDD cup dataset is used for research purpose by using WEKA tool. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

ISSN No.:1867-8211

Translation or Not:no

Date of Publication:2018-01-01

Co-author:Khudadad, Mirza

Correspondence Author:Huang ZhiQiu