Submitting Campus
Prescott
Student Status
Undergraduate
Class
Undergraduate Student Works
Advisor Name
Zhiyong Shan
Second Advisor Name
Vinod Namboodiri
Abstract/Description
Certain Android applications, such as but not limited to malware, conceal their presence from the user, exhibiting a self-hiding behavior. Consequently, these apps put the user’s security and privacy at risk by performing tasks without the user’s awareness. Static analysis has been used to analyze apps for self-hiding behavior, but this approach is prone to false positives and suffers from code obfuscation. This research proposes a set of three tools utilizing a dynamic analysis method of detecting self-hiding behavior of an app in the home, installed, and running application lists on an Android emulator. Our approach proves both highly accurate and efficient, providing tools usable by the Android marketplace for enhanced security screening.
Document Type
Presentation without Video
Publication/Presentation Date
11-4-2019
Sponsorship/Conference/Institution
The Sixth National Workshop for REU Research in Networking and Systems
Location
Monterey, CA
Scholarly Commons Citation
Baird, L. (2019). Automated Dynamic Detection of Self-Hiding Behaviors. , (). Retrieved from https://commons.erau.edu/student-works/149
