Dr. Saed Alrabaee

Assistant Professor in Information Systems and Security

Saed Alrabaee was born in the north region of Jordan. He is a proud former student of Concordia Institute for Information Systems Engineering (CIISE) in Canada. During his PhD, Saed was a member of software fingerprinting and malware analysis project. This project was part of a major research partnership between NSERC, Google and the Computer Security Laboratory (CSL) of the Concordia Institute for Information Systems Engineering (CIISE), Concordia University. The project pertained to the domain of software reverse engineering with applications to malware analysis. Saed is also a permanent research scientist at the National Cyber Forensic and Training Alliance (NCFTA) of Canada. The latter is an international organization which focuses on the investigation of cyber-crimes impacting citizens and businesses. With these experiences, Saed decided to join UAEU in order to transfer his expertise and knowledge by building a first reverse engineering laboratory in the Middle East. 

Passionate about developing advanced and smart technologies to enhance and ensure everyone life in the community, Dr Saed’s research insightfully explores, among other theories, neural computational approaches for cybersecurity, learning models to discover security breaches and vulnerabilities, automatic methods for learning the cyber attackers’ habits, and employing game theory approaches to mitigate the cybersecurity threats in critical infrastructures. His specialist areas, meanwhile, range from software security to cyber physical systems security.

In this domain, Dr Saed has published many articles in top tier journals and in prestigious conferences. Saed authored/co-authored: one book (published by Springer), 6 journal publications (one in Journal of Computer Security (JCS), one in ACM Transactions on Security and Privacy (TOPS), and 4 in the Elsevier Digital Investigation Journal), and 6 conference articles (ESORICS’2019, ESORICS’2018, Malware’2016, FPS’2016, DFRWS Symposium).  The authored book is entitled “Binary Code Fingerprinting for Cybersecurity: Application to Malicious Code Fingerprinting”, this book will definitely contribute to the community in UAE and worldwide. Recently, Saed received a Best Paper Award in the DFRWS Europe Symposium 2019. This award was given only to one research article among 21 accepted articles. In this article, Saed proposes a practical framework and a tool, BinChar, that captures various aspects of an author style, including code trait characteristics, code structure characteristics, and code behaviour characteristics. For the purpose of detection, a Convolutional Neural Network (CNN) is used. The results generated by the CNN are evaluated more precisely using Bayesian calibration. Also, a case study was reported in which it determines the author characteristics of the Mirai botnet and compare them with the author characteristics of 360,000 malware samples.

Aside from research, Saed was the recipient of Teaching Excellence Award 2016-2017, he was selected among 89 applicants. Saed’s teaching philosophy rests on four key principles: being organized and following a well-established schedule; applying an inside-out approach that relies on flexible, innovative teaching techniques; being supportive and motivating students, especially when they encounter difficulties; and guiding them to fulfill their potential. In UAEU, Saed always receives an evaluation above 4.6 out of 5.0. Outside the classroom the Jordan-born scientist, who spent a number of years living in Canada and US before coming to the Emirates, enjoys camping, soccer, and Hockey.