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Detekcija botnetov iz podatkov omrežnega prometa z razširitvijo na mobilnih napravah
Žitnik, Anže (Author), Dobravec, Tomaž (Mentor) More about this mentor... This link opens in a new window

URLURL - Presentation file, Visit http://eprints.fri.uni-lj.si/3210/ This link opens in a new window

Abstract
Cilj te magistrske naloge je bil spoznavanje klasičnih in mobilnih botnetov ter možnosti njihove detekcije, implementacija detektorja botnetov iz podatkov omrežnega prometa in mobilne aplikacije za detekcijo zlonamerne programske opreme na operacijskem sistemu Android. Izdelali smo detektor botnetov,ki uporablja model strojnega učenja za uvrščanje omrežnih tokov med legitimen promet ali promet botnetov. Detektor smo ovrednotili s testiranjem na dva različna načina ter komentirali njegove prednosti in omejitve. Razvili smo aplikacijo za platformo Android, ki zaznava zlonamerno programsko opremo s spremljanjem omrežnih povezav na nevarne vire in izkoriščanja nekaterih znanih varnostnih ranljivosti v operacijskem sistemu. Aplikacijo smo testirali na nekaj primerih zlonamernih programov ter jo ponudili za prenos uporabnikom uradne trgovine Android.

Language:Unknown
Keywords:računalniška varnost, botnet, detekcija botnetov, analiza omrežnega prometa, varnost mobilnih naprav, zlonamerna programska oprema, Android
Work type:Not categorized (r6)
Organization:FRI - Faculty of computer and information science
Year:2015
COBISS.SI-ID:1536606659 Link is opened in a new window
Views:513
Downloads:135
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Secondary language

Language:Unknown
Title:Botnet detection on network traffic data with an extension on mobile devices
Abstract:
The goal of this thesis was a study of classic and mobile botnets and the possibilities of their detection, implementation of a network traffic based botnet detector and a mobile application for malware detection on the Android operating system. We created a botnet detector that uses a machine learning model for classification of network flows as either legitimate or botnet-induced traffic. We evaluated the detector by two distinct testing procedures and commented on its advantages and limitations. We developed an Android application that detects malware by observing network connections to malicious resources and exploiting some of the known security vulnerabilities in the operating system. We tested the application on some malware samples and offered it to the users of the official Android marketplace.

Keywords:computer security, botnet, botnet detection, network traffic analysis, security of mobile devices, malware, Android

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