Digital Trust

Beschreibung

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.

Autor*in

Pascal Muam Mah

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Cybercrime Deep Learning Natural Language Processing Cyberkriminalität Künstliche Intelligenz

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