Department of Computer Science & Engineering · Louisiana State University
aonik1@lsu.edu
Abdur Rahman Onik
Abdur Rahman Onik — PhD Candidate at Louisiana State University

Abdur Rahman Onik

PhD Candidate in Computer Science & Engineering

I am a PhD candidate in Computer Science and Engineering at Louisiana State University. My research asks a practical question: when modern apps and devices rely on cloud backends, how do we make security and privacy claims testable in the real world? My work combines systems security and data-driven analysis to study app-to-cloud behavior, cloud APIs, authentication and session handling, telemetry, and the security consequences of opaque backend storage. I build measurement and validation methods that help researchers and practitioners understand what data flows occur, what security assumptions fail under real constraints, and how incident response can be supported with auditable evidence. I also study public incident response and trust during large disruptions using computational analysis of online discussions, connecting technical failures to how people interpret risk and responsibility. I have published peer-reviewed work in ACM Computing Surveys and Forensic Science International: Digital Investigation, and I maintain open-source tools such as PyRoomba, PyShot, and the Burner Forensics Cloud Client to support reproducible experiments and student projects.

aonik1@lsu.edu Google Scholar GitHub LinkedIn
439 Total Citations
7 h-index
11 Publications
4 Under Review

Research Interests

My research focuses on uncovering discrepancies between how mobile applications claim to handle user data and how they actually handle it. I develop forensic methods to extract and analyze app data from device storage and network traffic, with a particular focus on privacy compliance in practice.

I am currently designing a novel framework that uses Large Language Models to automatically parse privacy policies and compare them with empirically observed data collection behaviors. As part of this work, I am developing the App Privacy Compliance Index (APCI), a standardized metric to quantify app transparency.

Mobile Application Security & Privacy
Digital Forensics of Messaging Apps
Cloud Forensics & IoT Device Analysis
LLM-based Privacy Policy Analysis
Automotive Telematics Forensics
Social Media Platform Forensics

Selected Publications

11 total · 439 citations
2025
A Systematic Literature Review of Secure Instant Messaging Applications from a Digital Forensics Perspective
AR Onik, J Brown, C Walker, I Baggili
ACM Computing Surveys 57(9), 1–36
Q1 A* Digital Forensics 5 citations
Money on My Mind: Forensic Investigation of Venmo Payment App
T Spinosa, A Onik, J Rovira, I Baggili
International Conference on Availability, Reliability and Security (ARES), 60–77
Mobile Forensics
2024
Hit and Run: Forensic Vehicle Event Reconstruction Through Driver-Based Cloud Data from Progressive's Snapshot Application
AR Onik, TT Spinosa, AM Asad, I Baggili
Forensic Science International: Digital Investigation 49, 301762
Q1 Automotive 4 citations
So Fresh, So Clean: Cloud Forensic Analysis of the Amazon iRobot Roomba Vacuum
AR Onik, R Alsmadi, I Baggili, AM Webb
Forensic Science International: Digital Investigation 48, 301686
Q1 IoT Cloud Forensics 9 citations
Blue Skies from (X's) Pain: A Digital Forensic Analysis of Threads and Bluesky
J Brown, AR Onik, I Baggili
Proceedings of the 19th International Conference on Availability, Reliability and Security (ARES)
Social Media 11 citations
2015–2017
A Network Intrusion Detection Framework Based on Bayesian Network Using Wrapper Approach
MR Kabir, AR Onik, T Samad
International Journal of Computer Applications 166(4), 13–17 (2017)
Machine Learning 69 citations
Application of Machine Learning Approaches in Intrusion Detection System: A Survey
NF Haq, AR Onik, MAK Hridoy, M Rafni, FM Shah, DM Farid
IJARAI — International Journal of Advanced Research in Artificial Intelligence (2015)
Survey IDS 221 citations
An Ensemble Framework of Anomaly Detection Using Hybridized Feature Selection Approach (HFSA)
NF Haq, AR Onik, FM Shah
2015 SAI Intelligent Systems Conference (IntelliSys), 989–995
Anomaly Detection 59 citations
An Analytical Comparison on Filter Feature Extraction Method in Data Mining Using J48 Classifier
AR Onik, NF Haq, L Alam, TI Mamun
International Journal of Computer Applications 124(13) (2015)
Data Mining 29 citations
Cross-Breed Type Bayesian Network Based Intrusion Detection System (CBNIDS)
AR Onik, NF Haq, W Mustahin
2015 18th International Conference on Computer and Information Technology
IDS 13 citations
Predictive Analysis and Warehousing of Web Log Data
AR Onik, M Zaman, RT Islam, FY Sabah
International Journal of Computer Applications 975, 8887 (2017)
Web Analytics 1 citation