Intrusion detection method using a combination of Neural Network algorithms
Anton Mavrov graduated from Kharkiv National University of Radioelectronics (KNURE), Ukraine, and has recently passed his MPhil viva at the Wessex Institute of Technology, with a thesis on ‘Intrusion detection method using a combination of Neural Network algorithms’. The external examiner was Dr Nathan Clarke from the University of Plymouth, and the internal examiner was Prof Viktor Popov.
In his thesis Intrusion Detection Systems were investigated. The main aim of research was to develop an intrusion detection method with increased efficiency. The method used a combination of Kohonen neural networks algorithms to improve the classification accuracy. The Distributed Denial of Service attack type was chosen to test the proposed method as it still remains one of the most widely spread information security threats. The research showed that the presented model is more effective than the standalone algorithms, and in comparison with competing ones it has better characteristics.
Also the detailed treatment to Intrusion Detection Systems was given. The work describes their types, locations and detection approaches. Finally the anatomy of Distributed Denial of Service attack and basic methods and algorithms for anomaly detection systems were reviewed and analyzed.
As a result of this research both examiners recommended that Anton be awarded the degree of Master of Philosophy.