Optimizing Knowledge Sharing of Library Big Data in <scp>5G</scp> / <scp>6G</scp> Cloud‐Edge Environments Under Secure Network Frameworks

ABSTRACT Digital libraries increasingly use cloud–edge infrastructures to safely and effectively handle and communicate enormous amounts of academic material as 5G and 6G networks evolve. Existing cloud‐only designs still have capacity constraints during peak transmission, fragmented data distribution that slows retrieval, and inadequate real‐time threat detection. The proposed KSEdge‐Trust framework addresses this gap with an edge‐oriented, security‐aware knowledge‐sharing architecture for next‐generation library big‐data settings. The framework uses Edge‐Centric Knowledge Orchestration for locality‐aware data partitioning, an Adaptive Trust Layer with blockchain‐based consensus for integrity assurance, and a Secure Transmission Optimizer for lightweight encryption and intelligent traffic regulation to speed delivery. Compared to cloud‐only systems, KSEdge‐Trust reduces end‐to‐end latency by 47%, improves retrieval efficiency by 39%, and raises threat‐detection accuracy by 92%, attaining 300 ms and 95% retrieval efficiency. These performance gains confirm the framework's capability to deliver secure, scalable, and high‐performing knowledge dissemination within advanced 5G/6G cloud–edge ecosystems.