The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Program analysis for android security and reliability
Author:	Rahaman, Sydur
View Online:	njit-etd2023-043 (xx, 189 pages ~ 12.5 MB pdf)
Department:	Department of Computer Science
Degree:	Doctor of Philosophy
Program:	Computer Science
Document Type:	Dissertation
Advisory Committee:	Neamtiu, Iulian (Committee chair) Mili, Ali (Committee member) Borcea, Cristian (Committee member) Khreishah, Abdallah (Committee member) Qian, Zhiyun (Committee member)
Date:	2023-08
Keywords:	Dynamic analysis Fingerprinting PHI Security Static analysis Taint analysis
Availability:	Unrestricted
Abstract:	The recent, widespread growth and adoption of mobile devices have revolutionized the way users interact with technology. As mobile apps have become increasingly prevalent, concerns regarding their security and reliability have gained significant attention. The ever-expanding mobile app ecosystem presents unique challenges in ensuring the protection of user data and maintaining app robustness. This dissertation expands the field of program analysis with techniques and abstractions tailored explicitly to enhancing Android security and reliability. This research introduces approaches for addressing critical issues related to sensitive information leakage, device and user fingerprinting, mobile medical score calculators, as well as termination-induced data loss. Through a series of comprehensive studies and employing novel approaches that combine static and dynamic analysis, this work provides valuable insights and practical solutions to the aforementioned challenges. In summary, this dissertation makes the following contributions: (1) precise identifier leak tracking via a novel algebraic representation of leak signatures, (2) identifier processing graphs (IPGs), an abstraction for extracting and subverting user-based and device-based fingerprinting schemes, (3) interval-based verification of medical score calculator correctness, and (4) identifying potential data losses caused by app termination.