Digital Trust

The book advocates for a global digital identification system inspired by successful national models to counter cybercrime and manage multiple online identities. Through its cohesive approach, it redefines digital governance, promotes ethical online engagement, and strengthens authenticity, privacy, and accountability in a rapidly evolving virtual world.It presents a comprehensive framework that merges Deep Learning (DL), Natural Language Processing (NLP), and advanced technologies such as IoT, RFID, GPS, and facial-age detection to ensure age-appropriate online interactions. The book addresses harmful content, excessive screen time, and privacy threats through AI-driven content monitoring, health-risk detection, and user authentication mechanisms that identify underage users, fraudulent profiles, and unauthorized access—while minimizing energy consumption and moving beyond SIM-based systems. It further proposes a global digital identification model, inspired by successful national initiatives, to combat cybercrime and manage multiple online identities. This volume offers researchers, policymakers, and technology developers an integrated approach to building safer, more ethical, and accountable digital environments.

A researcher and technologist, Dr Mah specializes in Artificial Intelligence, Deep Learning, and Natural Language Processing, with expertise in digital safety, identity protection, and ethical technology design. He has contributed to projects in secure communication systems, emotion-based text classification, and AI-driven digital governance. He is currently an External Supervisor at OPIT – Open Institute of Technology in Malta, focusing on privacy-preserving frameworks for adolescent online safety and responsible digital engagement.