Cyber Threat Detection in 6G Internet of Things Using Deep Learning and Privacy Preservation via Blockchain

The quick propagation of Internet of Things (IoT) devices in 6th Generation (6G) networks intensifies security challenges due to high‐dimensional and diverse nature of IoT data, which complicates feature selection and increases computational overhead. Dynamic and evolving attack patterns, including various intrusion types, malware, denial‐of‐service attempts, and coordinated botnet attacks, further reduce detection reliability. To address these challenges, Optimized Periodic Implicit Generative Adversarial networks with advanced Transformer (OPIGAT) proposes an end‐to‐end framework for robust and scalable IoT security. The framework begins with a preprocessing stage that handles missing values, outliers, and normalization for clean and consistent data. Feature optimization occurs through a Hybrid Tuna Particle Swarm Optimization Algorithm (HTPSO), which Merges Particle Swarm Optimization (PSO) global search capability with Tuna Swarm Optimization (TSO) spiral foraging‐inspired local refinement, enabling precise selection of compact and highly discriminative features while reducing dimensionality. OPIGAT classifier detects diverse attacks, with the generative component synthesizing realistic traffic patterns and the transformer module capturing contextual relationships, enhancing anomaly detection and reducing false positives. Finally, a lightweight blockchain integrated with InterPlanetary File System (IPFS) ensures secure and scalable data management, employing proof of authority, Elliptic Curve Cryptography (ECC) with Ring signature encryption, and smart contract–based revocation to maintain privacy, integrity, and efficiency. Extensive experiments on CICIoT‐2023 and ROUT‐4‐2023 datasets demonstrate superior accuracy (98.78% and 97%), high detection efficiency (98.21%), and a low false alarm rate (20%), while IPFS‐enabled storage supports seamless scalability. These results establish OPIGAT as a secure, efficient, and highly effective solution for 6G IoT intrusion detection.