Sazzadur Rahaman
- Assistant Professor, Computer Science
- Member of the Graduate Faculty
Contact
- (520) 621-4632
- Gould-Simpson, Rm. 734
- Tucson, AZ 85721
- sazz@arizona.edu
Degrees
- Ph.D. Computer Sciencne
- Virginia Tech, Blacksburg, Virginia, United States
- From Theory to Practice: Deployment-grade Tools and Methodologies for Software Security
Interests
No activities entered.
Courses
2024-25 Courses
-
Computer Security
CSC 566 (Spring 2025) -
Research
CSC 900 (Spring 2025) -
Computer Security
CSC 466 (Fall 2024) -
Directed Research
CSC 492 (Fall 2024) -
Honors Thesis
CSC 498H (Fall 2024) -
Research
CSC 900 (Fall 2024)
2023-24 Courses
-
Computer Security
CSC 566 (Spring 2024) -
Honors Thesis
CSC 498H (Spring 2024) -
Research
CSC 900 (Spring 2024) -
Computer Security
CSC 466 (Fall 2023) -
Honors Thesis
CSC 498H (Fall 2023) -
Research
CSC 900 (Fall 2023)
2022-23 Courses
-
Computer Security
CSC 466 (Spring 2023) -
Research
CSC 900 (Spring 2023) -
Computer Security
CSC 566 (Fall 2022) -
Honors Thesis
CSC 498H (Fall 2022) -
Research
CSC 900 (Fall 2022)
2021-22 Courses
-
Computer Security
CSC 466 (Spring 2022) -
Computer Security
CSC 566 (Spring 2022) -
Directed Research
CSC 492 (Spring 2022) -
Honors Thesis
CSC 498H (Spring 2022) -
Independent Study
CSC 599 (Spring 2022) -
Research
CSC 900 (Spring 2022) -
Thesis
CSC 910 (Spring 2022) -
Research
CSC 900 (Fall 2021)
2020-21 Courses
-
Advanced Topics in Security
CSC 696I (Spring 2021) -
Directed Research
CSC 492 (Spring 2021) -
Research
CSC 900 (Spring 2021) -
Directed Research
CSC 492 (Fall 2020) -
Research
CSC 900 (Fall 2020)
Scholarly Contributions
Journals/Publications
- Debray, S. K., Rahaman, S., & Jacobsen, B. (2021). Optimization to the Rescue: Evading Binary Code Stylometry with Adversarial Use of Code Optimizations. Proceedings of the 2021 Worksop on Research on offensive and defensive techniques in the Context of Man At The End (MATE) Attacks.More infoRecent work suggests that it may be possible to determine the author of a binary program simply by analyzing stylistic features preserved within it. As this poses a threat to the privacy of programmers who wish to distribute their work anonymously, we consider steps that can be taken to mislead such analysis. We begin by exploring the effect of compiler optimizations on the features used for stylistic analysis. Building on these findings, we propose a gray-box attack on a state-of-the-art classifier using compiler optimizations. Finally, we discuss our results, as well as implications for the field of binary stylometry.
