计算机科学
数据完整性
随机预言
云计算
计算机安全
可验证秘密共享
密码学
上传
审计
服务器
方案(数学)
单点故障
密钥托管
信息隐私
共谋
架空(工程)
混淆
数据验证
瓶颈
加密
双线性插值
云存储
公钥密码术
重复数据消除
密文
计算机网络
密码分析
块链
数学证明
算法
安全性分析
可检索性
甲骨文公司
分布式计算
作者
Chen Zhu,Yang Lu,Nian Xia,Jiguo Li,Yinxia Sun
标识
DOI:10.1109/tifs.2026.3652010
摘要
Data Integrity Auditing (DIA) enables users to remotely verify whether their data saved in third-party clouds has been maliciously tampered with or compromised. As an extension of DIA in certificateless cryptography, certificateless DIA (CL-DIA) integrates the merits of conventional public-key cryptography (no key escrow) and identity-based cryptography (no certificates). However, CL-DIA schemes depend on a reliable third-party auditor (TPA) to perform integrity audits, inevitably suffering from performance bottleneck and single-point failure problems. Moreover, almost all current CL-DIA schemes were designed with computationally expensive bilinear pairings. Cryptanalysis demonstrates that the existing unique pairing-free CL-DIA scheme fails to achieve the unforgeable security of auditing proofs. In this work, we put forward a lightweight blockchain-assisted CL-DIA scheme. The scheme achieves DIA through the blockchain instead of a single TPA, thereby overcoming the problems caused by the TPA-based centralized auditing model. Then, by avoiding time-consuming pairing operations and employing edge servers in generating verifiable tags for the uploaded data of users, its performance surpasses previous pairing-based CL-DIA schemes, particularly in terms of computation efficiency. Furthermore, we provide formal proofs in the random oracle model demonstrating that our scheme achieves unforgeability of verifiable tags and auditing proofs, ensures data privacy secrity, and is resistant to collusion attacks between the EN and the CSP. Finally, experimental results show that when auditing 25 file blocks, our scheme only costs 0.29s, which reduces the total time cost of integrity auditing phase by 48.2%-85.5% compared to current pairing-based CL-DIA schemes.
科研通智能强力驱动
Strongly Powered by AbleSci AI