Verifiable Aggregation for Heterogeneous Decentralized Identity in Internet of Things
Kai Ding, Tianxiu Xie, Keke Gai, Jing Yu, Chennan Guo, Zhengkang Fang, Liehuang Zhu, Weizhi Meng · IEEE Internet of Things Journal · 2025
Blockchain-based decentralized identity (DID) typically employs identity aggregation techniques to support efficient and trustworthy identity authentication in order to meet the requirements of the high volume of service requests in Internet of Things (IoT). Due to the lack of effective mechanisms for heterogeneous DID (H-DID) aggregation, a complete aggregated identity authentication often requires multiple rounds of signature verification for different identity attributes. However, this setting brings trust and privacy issues, and one notable threat is the potential disclosure of secret identity information through the linkage of heterogeneous identity attributes when enormous IoT devices/accesses are involved. In this article, we focus on trustworthy authentication of DID and propose a novel anonymous verifiable credential-based aggregation for h-DID (AVCA-hDID). Our AVCA-hDID model supports anonymous ownership verification of DIDs through label randomization, thereby effectively safeguarding identity privacy in IoT. AVCA-hDID involves identifier aggregation and attribute aggregation for H-DIDs, ensuring both authentication efficiency and balancing trustworthiness and adoptability. We analyze the security and unlinkablility of our proposed model and further experiment evaluation demonstrates the efficiency and effectiveness of AVCA-hDID.