Shadowblock Achieves Efficient Dynamic Anonymous Blocklisting, Protecting User Privacy Online

The proliferation of harmful content online, including harassment and incitement to violence, presents a significant challenge to maintaining social harmony and upholding the law. Haotian Deng, Mengxuan Liu, and Chuan Zhang, all from the Beijing Institute of Technology, alongside colleagues, address this issue with a new approach to anonymous blocklisting, called ShadowBlock. Existing methods struggle to balance the need for dynamic updates with efficient verification, often compromising user privacy or system performance. ShadowBlock overcomes these limitations by employing a pseudorandom function and cryptographic accumulator, allowing users to anonymously prove they are not on a blocklist, while a novel aggregation technique streamlines the verification process. This innovation not only improves both the speed and efficiency of blocklisting, but also opens up possibilities for applications in areas such as cross-chain identity management, representing a substantial advance in online safety and privacy technologies.

Blockchain, 6G, and Generative AI Convergence

Research currently focuses heavily on the intersection of blockchain, cryptography, and security, with growing interest in applying these technologies to emerging areas like 6G, wireless sensing, and generative AI. A strong research presence at the Beijing Institute of Technology indicates a concentrated effort in these fields, exploring applications in identity management, secure data services, network security, and even e-government and online gambling. Current work addresses challenges in areas like spamming botnets, phishing attacks, and data breaches, aiming to create more secure and privacy-preserving online environments.

Efficient Anonymous Blocklisting with Proof Reuse

Scientists engineered an efficient dynamic anonymous blocklisting scheme to overcome limitations in existing systems, which struggle with both dynamism and efficiency. This work utilizes a pseudorandom function and cryptographic accumulator to construct a public blocklist, enabling users to anonymously prove they are not listed. Users generate a proof, accepted by the service provider via verification, granting access or indicating inclusion on the blocklist. To address computational overhead, the team developed a dynamic scheme for efficiently updating and maintaining the blocklist, allowing for the addition and removal of members without complete proof regeneration. When a user is unblocked, the system eliminates their tag and updates the cryptographic accumulator, publishing the revised list on a blockchain for transparent auditability. An aggregation mechanism for non-membership proofs further reduces verification overhead by combining multiple proofs into a single verification, improving scalability and efficiency.

Dynamic Anonymous Blocklists with Cryptographic Accumulators

Researchers developed a new method for efficiently managing blocklists while preserving user privacy, addressing limitations in existing anonymous blocklisting schemes. The core of this breakthrough lies in a dynamic system utilizing pseudorandom functions and cryptographic accumulators to construct a public blocklist, allowing users to anonymously prove they are not listed. The system allows for dynamic updates to the blocklist, enabling the addition and removal of members without requiring complete regeneration of user proofs. When a user’s ban is lifted, the system eliminates their tag and updates the cryptographic accumulator, publishing the revised list on a blockchain for transparent auditability. The research introduces an aggregation technique for non-membership proofs, combining multiple individual proofs into a single, unified proof, reducing verification overhead and offering substantial scalability improvements.

Anonymous Blocklisting with Scalable Zero-Knowledge Proofs

ShadowBlock represents a significant advancement in anonymous blocklisting technology, addressing limitations in existing systems regarding both efficiency and dynamic management. Researchers developed a system utilizing pseudorandom functions and cryptographic accumulators to enable users to anonymously prove they are not included on a blocklist, a crucial feature for protecting user privacy while mitigating harmful online behavior. Experimental results demonstrate that ShadowBlock outperforms current approaches in terms of both speed and scalability, offering strong security and privacy guarantees. The system’s use of accumulators allows for efficient updates to the blocklist, minimizing the need for complete regeneration of proofs, making it well-suited for real-time applications and rapidly evolving online environments.