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The Convergence of Emerging Technologies and AI-Driven Autonomous Cybersecurity in Smart Digital Ecosystems

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Publicado en:The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings (2025), p. 1-6
Autor principal: Traian-Cristian Ureche
Otros Autores: Boicescu, Laurentiu, Raducanu, Mircea, Popovici, Eduard-Cristian, Halunga, Simona, Dragos Nicolae Vizireanu
Publicado:
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Materias:
Quantum cryptography
Convergence
Internet of Things
Artificial intelligence
Health care
Ecosystems
Cybersecurity
Literature reviews
Threat evaluation
Multiagent systems
Anomalies
Deep learning
Machine learning
Real time
Federated learning
Intelligence gathering
New technology
Economic
Acceso en línea:Citation/Abstract
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Resumen:Conference Title: 2025 IEEE 2nd International Conference on Blockchain, Smart Healthcare and Emerging Technologies (SmartBlock4Health)Conference Start Date: 2025 June 19Conference End Date: 2025 June 20Conference Location: Bucharest, RomaniaThe increasing complexity of smart digital ecosystems, encompassing smart logistics, the Internet of Things (IoT), digital transformation, and emerging technologies, has significantly expanded the attack surface for cyber threats. Traditional cybersecurity approaches struggle to address the dynamic nature of these threats, necessitating the integration of artificial intelligence (AI)-driven autonomous cybersecurity frameworks. This paper provides a systematic literature review on the convergence of emerging technologies and AI-driven cybersecurity solutions, emphasizing their role in enabling real-time anomaly detection, proactive threat mitigation, and self-adaptive cybersecurity architectures. The study explores AI techniques such as deep learning, behavior-based analytics, and reinforcement learning, applied across multiple domains, including smart infrastructure, industrial IoT, healthcare, and critical digital services. Additionally, we introduce agent-based AI systems as a paradigm shift in autonomous cybersecurity, leveraging multi-agent collaboration, retrieval-augmented generation (RAG), and distributed threat intelligence to enhance security resilience. The paper further examines the integration of AI with emerging cybersecurity frameworks, such as federated learning, quantum cryptography, and AI-powered security automation. Lastly, we discuss key challenges, including interoperability, computational scalability, regulatory compliance, and adversarial AI threats. The findings underscore the pivotal role of AI and autonomous agents in securing interconnected smart ecosystems against evolving cyber threats.
DOI:10.1109/SmartBlock4Health64843.2025.11189602
Fuente:Science Database