Graduate School of Informatics /Information Systems

In partial fulfillment of the requirements for the degree of Master of Science Alper Sarıkaya will defend his thesis.

Title: ANOMALY-BASED CYBER INTRUSION DETECTION SYSTEM WITH ENSEMBLE CLASSIFIER

Date: 06th September 2018

Time: 14:00 PM

Place: A-212

Thesis Abstract : Nowadays, cyber attacks are beginning to occur at an increasing rate. Along with this, diversity, size and density of the cyber attacks are increasing accordingly. When we analyze log in the security devices, we find that the massive amount of attacks sign was created. Besides, It is also difficult for human to evaluate the log accurately. Therefore, the identification of key data, which can be used to distinguish attack from this very large data set, is important for both rapid detection of attack and rapid response of security devices. In this study, we will focus on selection of appropriate data from the log via machine learning and determine the distinctive attributes specific to the attack in the selection of these data. Thus, we will research on the classification of the data to be used in the attack detection via machine learning.