Lightweight intrusion detection for mobile devices. (c2012)

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dc.contributor.author Breidi, Fawzi
dc.date.accessioned 2012-09-26T08:33:54Z
dc.date.available 2012-09-26T08:33:54Z
dc.date.copyright 2012 en_US
dc.date.issued 2012-09-26
dc.date.submitted 2012-05-23
dc.identifier.uri http://hdl.handle.net/10725/1250
dc.description Includes bibliographical references (leaves 90-93). en_US
dc.description.abstract Current mobile devices are capable of providing connectivity anytime anywhere while supporting multitude of services and applications. This luxury of all-time connectivity makes mobile devices targets for a wide range of security attacks. Malware can be deployed to steal private data stored on the mobile device such as text messages, call history, photos, emails and others. More serious attacks may occur where malware initiates communication rather than just access stored information. In this thesis, we design and implement a lightweight malware detection technique that appropriately suits resource-constrained mobile devices in terms of low storage and computational requirements. The proposed technique utilizes several user parameters (such as SMS and call activity) and system parameters (such as CPU and memory utilization) over a period of time to model the activity profile of the mobile user rather than storing and checking a large number of abnormal behaviors (such as signatures of possible attacks). These parameters are continuously adapted based on the user behavior. Any violation to the constructed user profile will issue an alert for a potential security threat. We implemented and tested the proposed technique on Android mobile devices with several possible attacks. Results demonstrated its capabilities in terms of high malware detection success rate in addition to low storage and computational requirements. en_US
dc.language.iso en en_US
dc.subject Cell phone systems -- Security measures en_US
dc.subject Mobile communication systems -- Security measures en_US
dc.subject Malware (Computer software) -- Prevention en_US
dc.subject Data protection en_US
dc.title Lightweight intrusion detection for mobile devices. (c2012) en_US
dc.type Thesis en_US
dc.term.submitted Spring en_US
dc.author.degree MS in Computer Science en_US
dc.author.school Arts and Sciences en_US
dc.author.idnumber 200400542 en_US
dc.author.commembers Dr. Faisal Abu Khuzam
dc.author.commembers Dr. Nashaat Mansour
dc.author.woa OA en_US
dc.description.physdesc 1 bound copy: xv, 105 leaves; col. ill.; 30 cm. available at RNL. en_US
dc.author.division Computer Science en_US
dc.author.advisor Dr. Sanaa Sharafeddine
dc.keywords Computer Science en_US
dc.keywords Intrusion detection en_US
dc.keywords IDS en_US
dc.keywords Lightweight en_US
dc.keywords Mobile en_US
dc.keywords Smartphone en_US
dc.keywords Android en_US
dc.keywords Standalone en_US
dc.keywords Security en_US
dc.identifier.doi https://doi.org/10.26756/th.2012.17 en_US
dc.publisher.institution Lebanese American University en_US

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