The fast development of Information and Communication Technology (ICT) has changed digital infrastructures into connected, smart, and data-focused systems. Today's ICT environments produce large amounts of different data from Internet of Things (IoT) devices, business systems, cloud platforms, mobile networks, and spread-out communication setups. While new technologies like Artificial Intelligence (AI), Machine Learning (ML), Big Data Analytics, Cloud Computing, and improved Cybersecurity methods have shown significant progress in automation and scalability, using them separately often leads to fragmented structures, issues with compatibility, and security risks. This research proposes a detailed multi-layer framework for smart and secure Information and Communication Systems using new ICT technologies. The framework combines real-time data collection, distributed data handling, AI-driven predictive analytics, encryption-based communication methods, anomaly detection systems, and hybrid cloud orchestration into one architecture. The proposed model focuses on modularity, scalability, interoperability, and built-in security features to ensure resilience against changing cyber threats. Experimental validation using simulated distributed ICT datasets shows notable performance improvements. These include a 32% reduction in latency, a 34% boost in throughput, and a 96.4% accuracy rate in detecting anomalies. The framework can be applied in smart cities, healthcare systems, enterprise automation, and intelligent transportation systems. This study offers a clear plan for future ICT architectures that support sustainable and secure digital change.
Sarjun et al. (Thu,) studied this question.