Cloud computing and big data analytics have transformed enterprise operations, yet traditional perimeter-based security models fail in distributed, multi-cloud environments. Zero Trust Architecture (ZTA) addresses these limitations by enforcing continuous verification and identity-centric controls. This study examines Zero Trust principles applied to cloud-based big data systems, focusing on micro-segmentation, policy-as-code enforcement, and continuous authentication mechanisms.

It has become more difficult to manage modern telecom infrastructure due to complex networks and unpredictable traffic patterns. We designed and tested a generative AI-based system that makes network optimization decisions automatically. To construct a multi-objective optimizer that can handle speed, response time, and running costs simultaneously, the system combines transformer-based large language models with reinforcement learning agents.

Artificial intelligence is increasingly used to support complex decision workflows, yet its adoption in regulated industries remains limited. Medical device regulation, pharmaceutical oversight, aviation safety, and financial governance all rely on strict documentation, traceable reasoning, and verifiable evidence.

The constantly growing demands in the healthcare sector have increased the need to possess intelligent and scalable and secure systems to improve the quality of services, efficiency in operations, and patient outcomes. Healthcare routing of cases is a significant factor that defines how much clinical and administrative processes can be utilized fully as they are now able to allocate cases to the appropriate resources depending on urgency, expertise and needs of compliance.