Contribution to Abnormality Detection by Use of Clust-Density Algorithm
Chaimae Saadi, Habiba Chaoui, Hassan Erguig · International Review on Computers and Software (IRECOS) · 2015
In recent years with the remarkable development of technologies, in particular the Internet, the number of attacks has increased significantly. For this purpose, the use of an intrusion detection system has become an indispensable need for the fight against cybercrime in complex environments. For this, the evolution of the IDS is required to study the abnormal behavior, tactics and motivations hackers and ensure a higher level of security. In this paper, we propose an abnormally detection system based on new data mining algorithm called clust-density. We also analyze and implement tests in real use case to prove correctness of our approach and performance compared to other algorithms.