Date of Award

Spring 1-1-2013

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

First Advisor

Shivakant Mishra

Second Advisor

Richard Han

Third Advisor

Qin Lv

Fourth Advisor

John Black

Fifth Advisor

Eric Keller

Abstract

In recent years there has been a growing number of viruses, rootkits, and malware designed to gain access to system resources and information stored on smartphones. Most current approaches for detecting this malicious code have detrimental impacts on the user in terms of reduced functionality, slower network speeds, or loss of battery life. This work presents a number of approaches that have a minimal impact on the user but offer successful detection of potential malicious code on the smartphone. We do this primarily by focusing on anomalous power use as a method for detecting the presence of malicious code. This work also introduces ways to fine-tune the process by establishing a normal profile of power usage for each user, which increases the rate of malware detection.

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