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Blockchain brings various advantages to online transactions. However, the total transparency of these transactions may leakage users sensitive information. Requirements on both cooperation and anonymity for companies/organizations become necessary. In this paper, we propose a Multi-center Anonymous Blockchain-based (MAB) system, with joint management for the consortium and privacy protection for the participants. To achieve that, we formalize the syntax used by the MAB system and present a general construction based on a modular design. By applying cryptographic primitives to each module, we instantiate our scheme with anonymity and decentralization. Furthermore, we carry out a comprehensive formal analysis of the proposed solution. The results demonstrate our constructed scheme is secure and efficient.
The public key infrastructure (PKI) based authentication protocol provides the basic security services for vehicular ad-hoc networks (VANETs). However, trust and privacy are still open issues due to the unique characteristics of vehicles. It is cruci
Cyber attacks are becoming more frequent and sophisticated, introducing significant challenges for organizations to protect their systems and data from threat actors. Today, threat actors are highly motivated, persistent, and well-founded and operate
Privacy preservation is a big concern for various sectors. To protect individual user data, one emerging technology is differential privacy. However, it still has limitations for datasets with frequent queries, such as the fast accumulation of privac
Mobile service providers (MSPs) are particularly vulnerable to roaming frauds, especially ones that exploit the long delay in the data exchange process of the contemporary roaming management systems, causing multi-billion dollars loss each year. In t
There has been an intense concern for security alternatives because of the recent rise of cyber attacks, mainly targeting critical systems such as industry, medical, or energy ecosystem. Though the latest industry infrastructures largely depend on AI