<p>U ovoj doktorskoj disertaciji predložen je i analiziran metod koji kombinuje primenu entropije odabranih obeležja mrežnog saobraćaja i Takagi-Sugeno-Kang (TSK) neuro-fazi modela u detekciji DoS napada. Entropija je primenjena jer omogućava detekciju širokog spektra statističkih anomalija uzrokovanih DoS napadima dok TSK neuro-fazi model daje dodatni kvalitet u konačnom određivanju tačaka početka i kraja napada povećavajući odnos ispravno i pogrešno detektovanih napada.</p> / <p>In this thesis a new method for DoS attack detection is proposed. This method<br />combines the use of entropy of some characteristic parameters of network traffic<br />and Takagi-Sugeno-Kang (TSK) neuro-fuzzy model. Entropy has been used because<br />it enables detection of wide spectar of network anomalies caused by DoS attacks,<br />while TSK adds new value to final detection of the start and the end of an attack<br />increasing ratio between true and false detections.</p>
Identifer | oai:union.ndltd.org:uns.ac.rs/oai:CRISUNS:(BISIS)107396 |
Date | 24 September 2018 |
Creators | Petković Miodrag |
Contributors | Bašičević Ilija, Popović Miroslav, Teslić Nikola, Tomašević Milo, Kukolj Dragan |
Publisher | Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, University of Novi Sad, Faculty of Technical Sciences at Novi Sad |
Source Sets | University of Novi Sad |
Language | Serbian |
Detected Language | Unknown |
Type | PhD thesis |
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