Publication Date
Spring 2016
Degree Type
Master's Project
Degree Name
Master of Science (MS)
Department
Computer Science
First Advisor
Mark Stamp
Second Advisor
Thomas Austin
Third Advisor
Fabio Di Troia
Keywords
Android bytecode malware machine learning
Abstract
Static analysis relies on features extracted without executing code, while dynamic analysis extracts features based on code execution (or emulation). In general, static analysis is more e cient, while static analysis is often more informative, particularly in cases of highly obfuscated code. Static analysis of an Android application can rely on features extracted from the manifest le or the Java bytecode, while dynamic analysis of Android applications can deal with features involving dynamic code loading and system calls that are collected while the application is running. In this research, we analyzed the e ectiveness of combining static and dynamic features for detecting Android malware using machine learning techniques . We also carefully analyze the robustness of our scoring technique.
Recommended Citation
Kapratwar, Ankita, "Static and Dynamic Analysis for Android Malware Detection" (2016). Master's Projects. 488.
DOI: https://doi.org/10.31979/etd.za5p-mqce
https://scholarworks.sjsu.edu/etd_projects/488
