Online harassment, incitement to violence, racist behavior, and other harmful content on social media can damage social harmony and even break the law. Traditional blocklisting technologies can block malicious users, but this comes at the expense of identity privacy. The anonymous blocklisting has emerged as an effective mechanism to restrict the abuse of freedom of speech while protecting user identity privacy. However, the state-of-the-art anonymous blocklisting schemes suffer from either poor dynamism or low efficiency. In this paper, we propose $\mathsf{ShadowBlock}$, an efficient dynamic anonymous blocklisting scheme. Specifically, we utilize the pseudorandom function and cryptographic accumulator to construct the public blocklisting, enabling users to prove they are not on the blocklisting in an anonymous manner. To improve verification efficiency, we design an aggregation zero-knowledge proof mechanism that converts multiple verification operations into a single one. In addition, we leverage the accumulator's property to achieve efficient updates of the blocklisting, i.e., the original proof can be reused with minimal updates rather than regenerating the entire proof. Experiments show that $\mathsf{ShadowBlock}$ has better dynamics and efficiency than the existing schemes. Finally, the discussion on applications indicates that $\mathsf{ShadowBlock}$ also holds significant value and has broad prospects in emerging fields such as cross-chain identity management.
翻译:社交媒体上的网络骚扰、煽动暴力、种族歧视行为及其他有害内容会损害社会和谐,甚至触犯法律。传统的封禁列表技术能够阻止恶意用户,但这以牺牲身份隐私为代价。匿名封禁列表作为一种有效机制应运而生,它能在保护用户身份隐私的同时限制言论自由的滥用。然而,现有的先进匿名封禁列表方案要么动态性不足,要么效率低下。本文提出 $\mathsf{ShadowBlock}$,一种高效的动态匿名封禁列表方案。具体而言,我们利用伪随机函数和密码累加器构建公共封禁列表,使用户能够以匿名方式证明自己不在封禁列表中。为提高验证效率,我们设计了一种聚合零知识证明机制,将多次验证操作转换为单次验证。此外,我们利用累加器的特性实现封禁列表的高效更新,即原始证明可在最小化更新的情况下重复使用,而无需重新生成整个证明。实验表明,$\mathsf{ShadowBlock}$ 在动态性和效率上均优于现有方案。最后,应用讨论表明 $\mathsf{ShadowBlock}$ 在跨链身份管理等新兴领域也具有重要价值和广阔前景。