The human internet of things (HIoT) is a promising trend that adopts a user-centered vision to improve life quality by interacting with heterogeneous physical and virtual entities and the internet. However, It refers to exchanging contextual data between collaborative entities that raise privacy concerns. Emerging blockchain technology allows a digital identity management system (IDM) to be deployed in it, which largely alleviates the problems caused by the centralized third party. Still, its inherent transparency and lack of privacy pose a considerable challenge to IDM. We propose verifiable anonymous identity management (VAIM) connecting privacy channels between users by constructing identity verification and access control provisioning via user-centric decisions and an anonymous identity management system. This work has the following contributions: (1) We establish a novel IDM system by analyzing the existing scheme. In this regard, we improve the traditional claim identity model in blockchain by implementing zero-knowledge proof (ZKP) algorithms to achieve identity unlinkability, essentially preventing the disclosure of attribute ownership. (2) We implement a system that includes blind ordered multi-signature (BOMS) protocol, which allows users to processes efficiently and trusts the verification of anonymous transactions. (3) Finally, specific ZKP-based algorithm (commonly used practical ZKP such as Camenisch and Lysyanskaya signature (CL-Signature) and zero-knowledge succinct non-interactive argument of knowledge (ZK-SANRKS)) implementation and various environment performance evaluation and security analysis show that our scheme achieves efficient privacy protection and a broader application scope compared with the prior model. To the best of our knowledge, existing zero-knowledge proof-based IDM has not developed or compared each scheme before.

This paper proposes a novel data-owner-driven privacy-aware cloud data acquisition framework for intelligent big data analytics for service providers and users. To realize this idea, we propose three main components. The first one is a new global identity provider concept to support fine-grained access control for a federated outsourcing cloud, namely called P-FIPS (Privacy-enhanced Federated Identity Provider System), in which data owners perform identity access control with the operator of the federated outsourcing cloud so that the service providers can selectively use their encrypted data on the cloud for various purpose such as intelligent big data analytics. In P-FIPS, data owners manage the access privilege of service providers over their encrypted data on the cloud by (a) labeling the scope of use (e.g., user connection, user disconnection, user tracking) on each encrypted data on the cloud, and (b) by selectively providing the information regarding the data owners to the service provider. The label also includes the attributes related to the data owner’s identity, and this allows service providers to locate the target data with the assist of cryptographic computation according to the scope of the use at the cloud outsourcing server. The second one is a new ambiguous data acquisition mechanism integrated with P-FIPS from a cloud to a service provider. The last one is the Decentralized Audit and Ordering (DAO) Chain mechanism which provides the correctness of obtained data to the service provider as well as ensures the owners that their data is being used for the approved purpose only. Most importantly, we show that our framework is much more efficient than the existing alternative in the scheme.

A permissioned blockchain includes a user in the network after verifying the user’s identity, in contrast to Bitcoin, which is a public blockchain that allows network participation without third-party approval. The two types of permissioned blockchains are private blockchains, each consisting of one server and multiple users, and consortium blockchains, which consist of groups of private blockchains. However, a blockchain has privacy issues, such as user tracking and inference. Therefore, cryptography should be applied for user privacy in a blockchain. There is a lot of research on anonymous protocols for privacy in a blockchain. In this paper, we provide a scheme for user management, i.e., identification and authorization, in a permissioned blockchain. We also propose an anonymous protocol with user identification and transaction linking capabilities provided by the private server, strictly to solve privacy concerns.

Recently, the adoption of the industrial Internet of things (IIoT) has optimized many industrial sectors and promoted industry “smartization.” Smart factories and smart industries connect the real and virtual worlds through cyber-physical systems (CPS). However, these linkages will increase the cyber security danger surface to new levels, putting millions of dollars' worth of assets at risk if communications in big network systems like IIoT settings are left unsecured. To solve these problems, the fundamental method is security, such as authentication and confidentiality, and it should require the encryption key. However, it is challenging the security performance with the limited performance of the sensor. Blockchain-based identity management is emerging for lightweight, integrity and persistence. However, the key generation and management issues of blockchain face the same security performance issues. First, through blockchain smart contracts and hierarchical deterministic (HD) wallets, hierarchical key derivation efficiently distributes and manages keys by line and group in the IIoT environment. Second, the pairing verification value based on an elliptic curve single point called Root Signature performs efficient public key certificate registration and verification and improves the key storage space. Third, the identity log recorded through the blockchain is the global transparency of the key lifecycle, providing system reliability from various security attacks. Keyless Signature Infrastructure (KSI) is adopted to perform efficiently via hash-based scheme (hash calendar, hash tree etc.). We analyze our framework compared to hash-based state commitment methods. Accordingly, our method achieves a calculation efficiency of O(nlog N) and a storage space saving of 60% compared to the existing schemes.