cybersecurity

Muhammad Samiullah

Cyber Security, FPGA security, AI/ML security

Omar Rushdi

Visiting Student
Cyber Security, Phishing Detection, LLM

Jalal Saleem

Visiting Student
Cyber Security, LEO Satellite Constellation, Collision Avoidance

Ahmar Husain

Visiting Student
Cyber Security, Malware Analysis, LLM

Abidalrahman Obaidi

Visiting Student
Cybersecurity, Intrusion DetectionIDS, LLMs

Abdullah Alobaidi

Visiting Student
Cybersecurity, SOC Analysis, SIEM, LLM

Ahmad Didouh

Postdoctoral Research Fellow
Ali Hassan

Ali Hassan

Instructional Professor, Computer Science
Ali Hassan is an instructional professor in the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) Division at KAUST.

Security analysis of Docker-based containerized environments

Operating System (OS) virtualization, also known as container-based virtualization, has gained momentum over the past few years thanks to its lightweight nature and support for agility. However, its compelling features come at the price of a reduced isolation level compared to the traditional host-based virtualization techniques, exposing workloads to various faults, such as container escape. Those faults might be manifested as host OS bugs, container runtime vulnerabilities, and/or poor container deployment choices and profile configuration. The latter aspect is particularly critical as

Monitoring containerized environments for security state error detection

Operating System (OS) virtualization, also known as container-based virtualization, has gained momentum over the past few years thanks to its lightweight nature and support for agility. However, its compelling features come at the price of a reduced isolation level compared to the traditional host-based virtualization techniques, exposing workloads to various threats, such as container escape. In those threats, compromised or rogue containers might exploit existing vulnerabilities or poor container deployment choices to successfully inject security state errors (e.g., breaking out of the

Advanced Breach and Attack Simulation using ML

Cybersecurity is becoming a need more than ever. Organizations need to protect their digital assets and are required to earn certifications to prove the compliance to the regulations and rules. For this, these assets must be assessed to ensure the target security posture and to get certified or pass an audit on yearly basis. This is a daunting and costly task as it often requires a third-party tester that tries to penetrate the system, under agreement. Breach and Attack Simulation is a new method that allows to do this penetration testing in-house, using some automation tools. Some of these

Breaking the Vehicle Over-The-Air Update System

A modern vehicle is composed of around 100 Electronic Control Unit (ECU) connected via several types of networks. An ECU is an embedded device, similar to a RaspberryPI, running an operating system, e.g., Linux-based or real-time OS, on top of which different software and firmware may run, depending on the application. Due to the imperfection of humans, software can have faults and vulnerabilities, which can lead to catastrophic failures that threatens human lives. This makes the manufacturers liable to such failures and thus often caused millions of vehicles recalls for repair. A smart

Xiaojie Zhu

Xiaojie Zhu is a staff research scientist at KAUST. Prior to that, he was an assistant professor of cybersecurity in the Department of Computer Science and Information Technology, College of Engineering, Abu Dhabi University. He received his Ph.D. from the Department of Computer Science, University of Oslo, Norway. Xiaojie's research interests are data security and privacy, software security, decentralized trust and infrastructure, and applied cryptography. He has published in prestigious journals such as IEEE TDSC, IEEE TPDS, JNCA, and JOS. One of his articles was included in the 21st annual

Noor Hussein

Noor Hussein is a dedicated learner in Machine Learning and Artificial Intelligence. She earned her undergraduate degree in Applied Mathematics and Statistics from Khalifa University (KU) in Abu Dhabi, UAE, with the highest honors. In the fall of 2022, Hussein embarked on her academic journey by joining the Master's program in Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, UAE. She is expected to graduate from MBZUAI in the summer of 2024. During the summer of 2023, Hussein got the opportunity to join as a Visiting student at King Abdullah