Ibrahim "Abe" Bagili
Division Chair & Roger Richardson Professor Louisiana State University
- Baton Rouge LA
Dr. Baggili is a proven visionary higher education leader and builder with expertise in computing and cybersecurity research and education.
Media
Biography
Abe currently holds the rank of Professor of Computer Science at the University of New Haven. He also leads the University of New Haven's Cyber Forensics Research and Education Group (UNHcFREG). Abe also is the founding director of the Connecticut Institute of Technology.
Abe was born in Amman Jordan to his parents Moussa Baggili and Rebecca Melikian. So basically, he is a mutt - of both Jordanian / Armenian descent. Abe was raised in the United Arab Emirates and then moved to the USA to pursue his education at Purdue University. After finishing all his degrees at Purdue he went back to the United Arab Emirates and worked at Zayed University where he established and led the development of the first cyber forensics research laboratory in the Arab World.
Areas of Expertise
Research Focus
Digital Forensics & Cybersecurity
Dr. Baggili’s research focuses on digital and cyber forensics—from cloud, mobile, and IoT platforms to XR and drone systems—probing how emerging technologies introduce new security threats. He blends memory and network forensics, malware analysis, and AI-driven data analytics to develop investigative frameworks that safeguard critical infrastructure as chair of LSU’s Computer Science & Engineering division.
Accomplishments
European Alliance for Innovation Fellow
2019
CT Magazine 40 Under 40
2018
Finalist, Cybersecurity Excellence Award
2016
Education
Purdue University
Ph.D.
Cyber Forensics & Cybersecurity
2009
Purdue University
M.Sc.
Mobile Device Programming
2005
Purdue University
B.Sc.
Network Engineering Technology
2002
Affiliations
- Upsilon Pi Epsilon - The International Honor Society for the Computing and Information Disciplines
Media Appearances
LSU professor discusses Global IT outage
KALB 5 tv
2024-07-19
KALB spoke with Ibrahim Baggili, Professor of Computer Science & Cybersecurity at LSU, about the impacts of the Global IT Outage on July 19.
Cyber School
TIME Magazine for Kids online
2022-08-28
“Cybersecurity is not a stagnant thing,” Baggili says. “Every day, you’re going to be facing a different challenge. Someone is going to attack you, and you’ll have to defend yourself.”
What Is the Metaverse? An Explanation for People Who Don’t Get It.
VICE online
2022-05-15
“It’s not real at this stage, and won’t become real until people have a single location they can go to to get into in a virtual world they could live in,” Ibrahim Baggili, a cybersecurity expert and the founding director of the Connecticut Institute of Technology at the University of New Haven, told VICE.
VR systems Oculus Rift, HTC Vive may be vulnerable to hacks
CNET online
2018-04-17
In fact, the systems include no protection to stop these kinds of attacks, Ibrahim Baggili, director of the university's Cyber Forensics Research and Education Group (Unhcfreg), and the paper's co-author, Peter Gromkowski, said in an interview.
Articles
Tapping. IPAs: An automated analysis of iPhone applications using apple silicon macs
Forensic Science International: Digital Investigation2025
Dynamic analysis of iOS applications poses significant challenges due to the platform's stringent security measures. Historically, investigations often required jailbreaking, but recent enhancements in iOS security have diminished the viability of this approach. Consequently, alternative methodologies are necessary. In this study, we explore the feasibility of automated iOS application analysis on the ARM-based M1 Mac platform. To do so, we utilized an ARM-based Mac to install several popular iOS applications. Our manual analysis using existing macOS tools demonstrated the potential to uncover artifacts such as chat messages and browsing history. To streamline this process, we developed a tool, AppTap, which facilitates the entire forensic procedure from installation to artifact extraction.
ForensicLLM: A local large language model for digital forensics
Forensic Science International: Digital Investigation2025
Large Language Models (LLMs) excel in diverse natural language tasks but often lack specialization for fields like digital forensics. Their reliance on cloud-based APIs or high-performance computers restricts use in resource-limited environments, and response hallucinations could compromise their applicability in forensic contexts. We introduce ForensicLLM, a 4-bit quantized LLaMA-3.1–8B model fine-tuned on Q&A samples extracted from digital forensic research articles and curated digital artifacts. Quantitative evaluation showed that ForensicLLM outperformed both the base LLaMA-3.1–8B model and the Retrieval Augmented Generation (RAG) model. ForensicLLM accurately attributes sources 86.6 % of the time, with 81.2 % of the responses including both authors and title.
Hit and run: Forensic vehicle event reconstruction through driver-based cloud data from Progressive's snapshot application
Forensic Science International: Digital Investigation2024
Driving Insurance Applications (DIAs) have emerged as a valuable resource in the ever-evolving digital landscape. Automobile owners are storing extensive data on driving behaviors and patterns. This study pioneers the forensic analysis of Progressive's Snapshot application, focusing on the extraction and potential forensic use of data that remains inaccessible through the mobile application's interface. In our approach we focused on four research questions: How accurate is location and speed data collected by Progressive Snapshot?, What forensically relevant data can we extract from the Progressive Cloud that is unavailable to the user from the mobile application interface?, Can we employ anti-forensics techniques, specifically fake location data, to create false trip details?, Can we reconstruct a hit-and-run scenario from trip event details?
A step in a new direction: NVIDIA GPU kernel driver memory forensics
Forensic Science International: Digital Investigation2024
In the ever-expanding landscape of computation, graphics processing units have become one of the most essential types of devices for personal and commercial needs. Nearly all modern computers have one or more dedicated GPUs due to advancements in artificial intelligence, high-performance computing, 3D graphics rendering, and the growing demand for enhanced gaming experiences. As the GPU industry continues to grow, forensic investigations will need to incorporate these devices, given that they have large amounts of VRAM, computing power, and are used to process highly sensitive data. Past research has also shown that malware can hide its payloads within these devices and out of the view of traditional memory forensics.
On enhancing memory forensics with FAME: Framework for advanced monitoring and execution
Forensic Science International: Digital Investigation2024
Memory Forensics (MF) is an essential aspect of digital investigations, but practitioners often face time-consuming challenges when using popular tools like the Volatility Framework (VF). VF, a widely-adopted Python-based memory forensics tool, presents difficulties for practitioners due to its slow performance. Thus, in this study, we evaluated methods to accelerate VF without modifying its code by testing four alternative Python Just In Time (JIT) interpreters - CPython, Pyston, PyPy, and Pyjion - using CPython as our baseline. Tests were conducted on 14 memory samples, totaling 173 GB, using a search-intensive VF plugin for Windows hosts. Employing our custom Framework for Advanced Monitoring and Execution (FAME), we deployed interpreters in Docker containers and monitored their real-time performance.
Event Appearances
Digital Forensics in the Next Five Years
2020 | Interpol Digital Forensics Expert Group Online
Virtual Reality Insanity: Cybersecurity and Forensics of Immersive Virtual Reality
2020 | Invited Talk by Women In Cyber Security (WICyS) Mid Atlantic Online
Virtual Reality Insanity: Cybersecurity and Forensics of Immersive Virtual Reality
2020 | Invited Talk by Southern Connecticut State University New Haven, CT
Research Grants
In-Memory Object Recovery From the V8 JavaScript Engine
NSA/DoD
2020
Project IRONCLAD – cybersecurIty tRaining for the cOnNeCticut nationaL guArD
NSA/DoD
2020
University of New Haven Department of Defense (DoD) Cyber Scholarship (CySP): Cyber Operative Scholars (CCOS
NSA/DoD
2020
