Assure deletion supporting dynamic insertion for outsourced data in cloud computing. (September 2020)

• Record Type: Journal Article
• Authors: Yang, Changsong; Liu, Yueling; Tao, Xiaoling
• Is Part Of: International journal of distributed sensor networks. Volume 16:Number 9(2020)
• Publication Date: 2020-09
• Subjects: Cloud storage -- secure data deletion -- dynamic data insertion -- public verifiability -- Merkle sum hash tree; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147720958294
• Languages: English
• ISSNs: 1550-1329

Abstract

With the rapid development of cloud computing, an increasing number of data owners are willing to employ cloud storage service. In cloud storage, the resource-constraint data owners can outsource their large-scale data to the remote cloud server, by which they can greatly reduce local storage overhead and computation cost. Despite plenty of attractive advantages, cloud storage inevitably suffers from some new security challenges due to the separation of outsourced data ownership and its management, such as secure data insertion and deletion. The cloud server may maliciously reserve some data copies and return a wrong deletion result to cheat the data owner. Moreover, it is very difficult for the data owner to securely insert some new data blocks into the outsourced data set. To solve the above two problems, we adopt the primitive of Merkle sum hash tree to design a novel publicly verifiable cloud data deletion scheme, which can also simultaneously achieve provable data storage and dynamic data insertion. Moreover, an interesting property of our proposed scheme is that it can satisfy private and public verifiability without requiring any trusted third party. Furthermore, we formally prove that our proposed scheme not only can achieve the desired security properties, but also can realize the high efficiency and practicality.