Efficient Encryption using Quondam Signature Algorithm and Modified Lean Six Sigma for Sustainability with Supply Chain Management

Abstract

This paper presents a novel blockchain-based Industrial Internet of Things (IIIoT) security approach. The proposed architecture uses an eco-friendly federated learning AI-driven paradigm with cutting-edge Quondam Signature Algorithm technology and efficient encryption. The research also uses Modified Lean Six Sigma for sustainable supply chain management. The framework combines these aspects to synergistically increase IIIoT systems cyber resilience and environmental sustainability. The proposed work explores advanced encryption and process optimization methods to develop robust security architecture and advance safe and environmentally friendly IIIoT applications in supply chain management. We analyze cost-in-communication systems, focusing on federated learning and encryption. The suggested method uses an online/offline system, an elliptic curve digital signature technique, and online phase signature generation to combine offline phase calculations and optimize temporal complexity. Since it uses federated learning and encryption, the proposed method looks to improve efficiency and lower communication costs. This proposed work also shows that the recommended technique reduces communication costs, improves analytical capabilities, and protects IIoT systems from various attacks.