Hershey, Pennsylvania
New York, New YorkBeijing, China

Faisal Aburub

Faisal Aburub is a professor of Information Systems within the Faculty of Administrative and Financial Sciences at University of Petra, Jordan. Faisal completed his PhD in the University of the West of England - Bristol-UK. He joined University of Petra in September 2001. Professor Aburub currently is Dean of scientific research and graduate studies at University of Petra. His primary areas of research are business process modelling, business process reengineering, organizational agility and ERP systems. His research has been published extensively in academic journals and conferences. Professor Aburub’s research has focused significantly on bridging the gap between system models and business process models. His research has focused on using practical methods for modelling complex organizational settings and the potential role of IT systems within them.

Publications

The Role of Academic Leadership in Accelerating Smart Urban Governance
The Role of Academic Leadership in Accelerating Smart Urban Governance
Faisal Aburub, Saad Alateef, Ala Hamarsheh, Amjad Aldweesh. © 2025. 26 pages.
Urban settings in developing contexts face pressures arising from population growth, restricted resources, and evolving policy demands. Research insights from universities often...
Advanced AI for Network Security: Predictive Detection and Autonomous Defense
Advanced AI for Network Security: Predictive Detection and Autonomous Defense
Faisal Aburub, Saad Alateef. © 2025. 26 pages.
Organizations continue facing threats that exploit network vulnerabilities. Defenders seek approaches that detect anomalies and respond quickly to attacks. This chapter examines...
Theoretical Frameworks for Zero-Knowledge Proof Integration in Autonomous Defense Systems: A Mathematical Foundation for Privacy-Preserving Security
Theoretical Frameworks for Zero-Knowledge Proof Integration in Autonomous Defense Systems: A Mathematical Foundation for Privacy-Preserving Security
Mohammad Arafah, Faisal Asad Aburub, Sabreen Alhariri. © 2025. 28 pages.
The proposed research presents a theoretical investigation into the integration of zero-knowledge proofs (ZKP) within autonomous defense architectures, establishing rigorous...
AI-Powered Social Engineering and Impersonation Attacks
AI-Powered Social Engineering and Impersonation Attacks
Mohammad Arafah, Louay Karadsheh, Faisal Aburub, Sabreen Alhariri. © 2025. 20 pages.
This chapter presents a comprehensive analysis of advanced social engineering attack vectors enhanced by Generative Artificial Intelligence (GenAI) technologies, focusing on...
Building Human-Centric Defenses Against Generative AI Threats in Developing Countries
Building Human-Centric Defenses Against Generative AI Threats in Developing Countries
Faisal Aburub, Saad Alateef. © 2025. 20 pages.
Developing countries face heightened cybersecurity risks due to the accelerating adoption of generative AI tools. These technologies have created new vulnerabilities and widened...
Business Intelligence Threat Detection Through Advanced AI and ML
Business Intelligence Threat Detection Through Advanced AI and ML
Faisal Aburub, Ammar Almomani. © 2025. 22 pages.
Business intelligence (BI) systems are integral to strategic and operational decision-making in contemporary data-driven organizations. As these platforms accumulate increasingly...
Data-Driven Cyber Defense Leveraging Business Intelligence
Data-Driven Cyber Defense Leveraging Business Intelligence
Faisal Aburub, Ammar Almomani. © 2025. 26 pages.
Organizations operate in a global digital landscape where cyber threats continue to escalate in both complexity and volume, rendering traditional security models insufficient....
Secure Key Generation and Management Using Generative Adversarial Networks
Secure Key Generation and Management Using Generative Adversarial Networks
Mohammad Al Khaldy, Faisal Aburub, Ahmad Al-Qerem, Amjad Aldweesh, Ammar Almomani. © 2024. 26 pages.
The generation and control of cryptographic keys are the most important things when it comes to the security and integrity of encrypted data. The traditional key generation...
Privacy-Preserving Machine Learning Cryptographic Techniques for Secure Data Analysis
Privacy-Preserving Machine Learning Cryptographic Techniques for Secure Data Analysis
Mohammad Alauthman, Ahmad Al-Qerem, Ammar Almomani, Amjad Aldweesh, Faisal Aburub, Mouhammd Alkasassbeh. © 2024. 26 pages.
Machine learning models rely on sensitive personal data, creating tension between utility and privacy. Privacy-preserving machine learning aims to enable secure data analysis...