摘要
云存储作为云计算中最为广泛的应用之一,给用户带来了便利的接入和共享数据的同时,也产生了数据损坏和丢失等方面的数据完整性问题.现有的远程数据完整性验证中都是由可信任的第三方来公开执行数据完整性验证,这使得验证者有提供虚假伪造的验证结果的潜在威胁,从而使得数据完整性验证结果不可靠,尤其是当他与云存储提供者合谋时情况会更糟.提出一种数据验证结果的检测算法以抵御来自不可信验证结果的伪造欺骗攻击,算法中通过建立完整性验证证据和不可信检测证据的双证据模式来执行交叉验证,通过完整性验证证据来检测数据的完整性,利用不可信检测证据判定数据验证结果的正确性,此外,构建检测树来确保验证结果的可靠性.理论分析和模拟结果表明:该算法通过改善有效的验证结果来保证验证结果的可靠性和提高验证效率.
Cloud storage is one of the most widely used applications in cloud computing. It makes it convenient for users to access and share the data yet producing data integrity issues such as data corruption and loss. The existing remote data verification algorithms are based on the trusted third party who works as a public verifier to verify the outsourced data integrity. In this case, the verifier has a potential threat to provide false verification results, which cannot ensure the reliability of data verification. Especially, the situation can be even worse while the verifier is in collusion with the cloud storage providers. In this paper, we propose a check algorithm of incredible verification results in data integrity verification （CIVR） to resist the attacks of forgery and deception in incredible verification results. We utilize double verification proofs, i.e., integrity verification proof and incredible check proof, to execute the cross check. The integrity verification proof is to verify whether the data are intact. The incredible check proof is to check whether the verification results are correct. Moreover, the algorithm constructs the check tree to ensure the reliability of verification results. Theoretical analysis and simulation results show that the proposed algorithm can guarantee the reliability of verification results and increase the efficiency by improving the valid verification.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2017年第11期2487-2496,共10页
Journal of Computer Research and Development
基金
上海自然科学基金项目(15ZR1400900
15ZR1400300
16ZR1401100)
上海市教育科研项目(C160076)
国家自然科学基金项目(61402100
61772128)
同济大学高密度人居环境生态与节能教育部重点实验室种子基金项目
东华大学中央高校基本科研业务费专项资金项目(2232015D3-29)~~
关键词
数据完整性验证
不可信验证结果
验证结果检测
双证据
检测树
data integrity verification
incredible verification results
verification results checking
dual proofs
check tree
