AI systems face several security threats that can affect their accuracy, confidentiality, and reliability. One major threat is Data Poisoning, where attackers intentionally insert malicious, false, or deceptive data into …
As an accomplished professional with a Master Degree in Computer Science (Specialization in Software Engineering) and a PGD in Management Information Systems, over 20 years of hands-on experience in Information Technology, Data Governance, Data Management, and PDPL plus NCA Compliance. Expertise spans diverse sectors, including Aviation, Healthcare, Investment, Education, and Construction, allowing me to effectively bridge the gap between technical and business needs.
Leadership roles include Manager – Data Management (DMO), Manager Systems, Sr. Team Lead – Data Specialist, Manager Applications, and Adjunct Faculty Member among others. I am also deeply involved in applied research, focusing on Big Data Governance, Privacy, Security, and Compliance. My work has been published in prestigious international journals, offering valuable insights into solving industry challenges.
Possesses extensive expertise spanning a diverse range of platforms, tools, technologies, hardware, software, and operating systems, effectively leveraging this knowledge to address complex challenges in Data governance, security, privacy and compliance.
With 45+ professional certifications, including Certified Data Management Professional (CDMP), GDPR, CCPA, Certified Data Protection Officer (CDPO), ITIL, EC-Council Disaster Recovery Professional, AWS Cloud Certified, Oracle Technologies including e-Business, Databases, and Oracle Cloud Infrastructure (OCI). I have continually enhanced my expertise in the ever-evolving field of data privacy and security. My competencies also include Disaster Recovery, Business Continuity, Regulatory Compliance (GDPR, NCA, CCPA, NDMO), Data Architecture, Metadata Management, and more.
Numerous initiatives in Data Governance, Data Management, Data Privacy, Data Protection, ensuring compliance with international, and local standards such as NCA, GDPR, KSA PDPL, and NDMO.
The Core Principles for Integrated AI (Artificial Intelligence) Framework
Principles are essential for Integrated AI because AI systems do not function in isolation. They interact with multiple systems, databases, business processes, users, regulatory requirements, and decision-making environments. Without well-defined …
What is Integrated AI (Artificial Intelligence)?
AI (Artificial Intelligence) is the capability of computer systems, machines or software to perform tasks that normally require human intelligence, such as learning, reasoning, understanding language, recognizing patterns, and making …
Data Masking Techniques for Big Data
Data Masking means hiding sensitive data so that unauthorized people cannot see the real information, while the system can still work normally. In other words, you replace real sensitive data …
Six Essential Practices for Responsible AI Governance
Responsible AI governance ensures AI is used safely, fairly, and transparently, while keeping humans in control. In aviation, this is critical because AI decisions can affect passenger safety, security, operational …
DiD – Defense-in-Depth Principle
The Defense-in-Depth Principle is a cybersecurity strategy that emphasizes using multiple layers of security controls to protect systems, networks, and data. The core idea is that no single defense mechanism …
Leveraging Big Data through NoSQL Databases (Architecture Methodologies, and Strategic Applications)
The rise of Big Data has necessitated the evolution of databases beyond traditional relational models, paving the way for NoSQL databases to manage unstructured and semi-structured data at scale. This …
GDPR Aligned – Big Data Security Processes – Across the Data Lifecycle
Managing privacy and security in Big Data environments requires multi-layered strategies that address volume, velocity, and variety of datasets while ensuring GDPR compliance. The following nine features provide a comprehensive …
Navigating the Big Data Lifecycle: From Collection to Insight
Data Creation & Collection: Data is first generated by users, applications, or digital systems and then collected from multiple sources. For example, when a user registers on an online platform, …
Zero-Knowledge Proof (ZKP) – A Professional Review
Abstract ZKP (Zero-Knowledge Proof) is a modern cryptographic concept that allows one party (the prover) to prove to another party (the verifier) that a statement is true without revealing any …