TASS: Threshold Adaptor Signature Scheme for Holographic IoT Consumer Devices in Blockchain Enabled Federated Learning

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Abstract
The integration of virtual medical assistants utilizing holographic projections has transformed holographic IoT consumer devices, fostering advanced healthcare interactions and attracting significant interest from industry and academia. Most federated learning (FL) systems in holographic IoT consumer devices are centrally managed, which exposes them to risks such as medical data breaches and single points of failure. Although blockchain technology provides an effective solution by enabling decentralized model training, it faces inherent limitations in terms of computational efficiency and security. Adapter signatures (AS) offload some of the computation on the blockchain to mitigate these problems through means such as key revelation. Despite their advantages, existing AS schemes suffer from bilateral design constraints, which increase the risks of key loss, single points of failure, and lack support for multi-party transaction scenarios. This paper proposes a novel threshold adapter signature scheme (TASS) based on elliptic curve cryptography (ECC) to address these challenges. TASS allows a group of entities to collaboratively generate partial signatures in a distributed manner, reducing the risks associated with key loss and single points of failure. Each participant holds only a share of the private key, ensuring that no single entity has complete control. This distributed approach enhances the system’s resilience against attacks and operational failures. Unlike traditional AS schemes that primarily support one-to-one transactions, TASS is designed to facilitate one-to-many and many-to-many transactions. Experimental evaluations demonstrate the superior performance of ECC-driven TASS in large-scale participants, providing a secure, efficient, and scalable foundation for integrating holographic interactions and blockchain technology within holographic IoT consumer devices.
Funding Information
  • National Key Research and Development Program of China (2022YFB2701400)
  • National Natural Science Foundation of China (62372083, 62072074)
  • Ongoing Research Funding Program, King Saud University, Riyadh, Saudi Arabia

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