Mohcine KODAD is an associate professor of Computer Science at the Higher School of Technology (ESTO), Mohammed First University, Oujda, Morocco, where he has been serving since 2017. He holds a Ph.D. in Computer Science (2016) and previously earned a Specialized Master’s degree in Software Quality. His career spans academia, applied IT engineering, and institutional leadership. Prior to joining the university, he worked for three years as a Design and Development Engineer at an International IT company based in Oujda, Morocco, where he led the development and management of digital solutions for various industrial projects. His professional experience notably includes contributions to digital public platforms and corporate information systems. His research interests focus on Social Network Analysis, Machine Learning, Smart Cities, SIG, NLP, and Data Analysis.Omar MOUSSAOUI is a full professor of Computer Science at the Higher School of Technology of Oujda (ESTO), University Mohammed Premier, Morocco, where he has been a member of the Computer Science Department since 2013. He obtained his Ph.D. in Computer Science from the University of Cergy-Pontoise, France, in 2006, and his Habilitation (Associate Professorship) in Computer Science from University Mohammed Premier in 2018. He is currently the Director of the MATSI research laboratory. His research activities focus on cybersecurity, the Internet of Things (IoT), artificial intelligence, and emerging intelligent systems. He has authored and co-authored more than 60 scientific publications in indexed international journals and conferences, as well as several book chapters and edited volumes, with an h-index of 15 (Scopus). Professor Moussaoui has served on scientific and organizing committees of numerous international conferences and acts as a reviewer for several international journals.

• An Enhanced Elliptic Curve Cryptography-Based Approach for Color Image Encryption.- Mechanisms for hardening SSH access on a Linux server.- New Variant of Hill Encryption Scheme using a Chaotic Control Vector.- Machine Learning Approaches for Intrusion Detection in IoT Systems: Taxonomy and Challenges.- Weighted Core Attack Graph for Honeypot Allocation Against Lateral Movement in Advanced Persistent Threats.- Dynamic Chaotic Hill Cipher for Secure Image Encryption in Z/212Z.- Secure Agentic Reinforcement Learning for LLM-Driven SaaS Systems.- A Comparative Study of Supervised and Semi-Supervised Machine Learning for Intrusion Detection in BLE Enabled IoMT Systems.- Web Tracking Protection Methods: A Systematic Review with Cross-Platform Experimental Validation.

Mohcine KODAD is an associate professor of Computer Science at the Higher School of Technology (ESTO), Mohammed First University, Oujda, Morocco, where he has been serving since 2017. He holds a Ph.D. in Computer Science (2016) and previously earned a Specialized Master’s degree in Software Quality. His career spans academia, applied IT engineering, and institutional leadership. Prior to joining the university, he worked for three years as a Design and Development Engineer at an International IT company based in Oujda, Morocco, where he led the development and management of digital solutions for various industrial projects. His professional experience notably includes contributions to digital public platforms and corporate information systems. His research interests focus on Social Network Analysis, Machine Learning, Smart Cities, SIG, NLP, and Data Analysis.Omar MOUSSAOUI is a full professor of Computer Science at the Higher School of Technology of Oujda (ESTO), University Mohammed Premier, Morocco, where he has been a member of the Computer Science Department since 2013. He obtained his Ph.D. in Computer Science from the University of Cergy-Pontoise, France, in 2006, and his Habilitation (Associate Professorship) in Computer Science from University Mohammed Premier in 2018. He is currently the Director of the MATSI research laboratory. His research activities focus on cybersecurity, the Internet of Things (IoT), artificial intelligence, and emerging intelligent systems. He has authored and co-authored more than 60 scientific publications in indexed international journals and conferences, as well as several book chapters and edited volumes, with an h-index of 15 (Scopus). Professor Moussaoui has served on scientific and organizing committees of numerous international conferences and acts as a reviewer for several international journals.

• An Enhanced Elliptic Curve Cryptography-Based Approach for Color Image Encryption.- Mechanisms for hardening SSH access on a Linux server.- New Variant of Hill Encryption Scheme using a Chaotic Control Vector.- Machine Learning Approaches for Intrusion Detection in IoT Systems: Taxonomy and Challenges.- Weighted Core Attack Graph for Honeypot Allocation Against Lateral Movement in Advanced Persistent Threats.- Dynamic Chaotic Hill Cipher for Secure Image Encryption in Z/212Z.- Secure Agentic Reinforcement Learning for LLM-Driven SaaS Systems.- A Comparative Study of Supervised and Semi-Supervised Machine Learning for Intrusion Detection in BLE Enabled IoMT Systems.- Web Tracking Protection Methods: A Systematic Review with Cross-Platform Experimental Validation.

Mohcine KODAD is an associate professor of Computer Science at the Higher School of Technology (ESTO), Mohammed First University, Oujda, Morocco, where he has been serving since 2017. He holds a Ph.D. in Computer Science (2016) and previously earned a Specialized Master’s degree in Software Quality. His career spans academia, applied IT engineering, and institutional leadership. Prior to joining the university, he worked for three years as a Design and Development Engineer at an International IT company based in Oujda, Morocco, where he led the development and management of digital solutions for various industrial projects. His professional experience notably includes contributions to digital public platforms and corporate information systems. His research interests focus on Social Network Analysis, Machine Learning, Smart Cities, SIG, NLP, and Data Analysis.Omar MOUSSAOUI is a full professor of Computer Science at the Higher School of Technology of Oujda (ESTO), University Mohammed Premier, Morocco, where he has been a member of the Computer Science Department since 2013. He obtained his Ph.D. in Computer Science from the University of Cergy-Pontoise, France, in 2006, and his Habilitation (Associate Professorship) in Computer Science from University Mohammed Premier in 2018. He is currently the Director of the MATSI research laboratory. His research activities focus on cybersecurity, the Internet of Things (IoT), artificial intelligence, and emerging intelligent systems. He has authored and co-authored more than 60 scientific publications in indexed international journals and conferences, as well as several book chapters and edited volumes, with an h-index of 15 (Scopus). Professor Moussaoui has served on scientific and organizing committees of numerous international conferences and acts as a reviewer for several international journals.

• An Enhanced Elliptic Curve Cryptography-Based Approach for Color Image Encryption.- Mechanisms for hardening SSH access on a Linux server.- New Variant of Hill Encryption Scheme using a Chaotic Control Vector.- Machine Learning Approaches for Intrusion Detection in IoT Systems: Taxonomy and Challenges.- Weighted Core Attack Graph for Honeypot Allocation Against Lateral Movement in Advanced Persistent Threats.- Dynamic Chaotic Hill Cipher for Secure Image Encryption in Z/212Z.- Secure Agentic Reinforcement Learning for LLM-Driven SaaS Systems.- A Comparative Study of Supervised and Semi-Supervised Machine Learning for Intrusion Detection in BLE Enabled IoMT Systems.- Web Tracking Protection Methods: A Systematic Review with Cross-Platform Experimental Validation.