Abstract
Recently, the rapid development of Internet of things (IoT) has resulted in the generation of a considerable amount of data, which should be stored. Therefore, it is necessary to develop methods that can easily capture, save, and modify these data. The data generated using IoT contain private information; therefore sufficient security features should be incorporated to ensure that potential attackers cannot access the data. Researchers from various fields are attempting to achieve data security. One of the major challenges is that IoT is a paradigm of how each device in the Internet infrastructure is interconnected to a globally dynamic network. When searching in dynamic cloud-stored data, sensitive data can be easily leaked. IoT data storage and retrieval from untrusted cloud servers should be secure. Searchable symmetric encryption (SSE) is a vital technology in the field of cloud storage. SSE allows users to use keywords to search for data in an untrusted cloud server but the keywords and the data content are concealed from the server. However, an SSE database is seldom used by cloud operators because the data stored on the cloud server is often modified. The server cannot update the data without decryption because the data are encrypted by the user. Therefore, dynamic SSE (DSSE) has been developed in recent years to support the aforementioned requirements. Instead of decrypting the data stored by customers, DSSE adds or deletes encrypted data on the server. A number of DSSE systems based on linked list structures or blind storage (a new primitive) have been proposed. From the perspective of functionality, extensibility, and efficiency, these DSSE systems each have their own advantages and drawbacks. The most crucial aspect of a system that is used in the cloud industry is the trade-off between performance and security. Therefore, we compared the efficiency and security of multiple DSSE systems and identified their shortcomings to develop an improved system.
Highlights
The rapid development of Internet of things (IoT) and cloud computing has resulted in a high demand for cloud storage environments
The client can add or delete file queries to the server, causing the server to add the new file or delete an existing file while only learning trivial information about the files
This paper compared the performance of seven dynamic SSE (DSSE) schemes, including SPS, NPG, KPR, SPS, HK, CJJJ and the proposed DSSE scheme combining modified SPS, NPG, and HK, called hybrid DSSE (HDSSE)
Summary
The rapid development of Internet of things (IoT) and cloud computing has resulted in a high demand for cloud storage environments In these systems, to protect privacy, users query some information multiple times and receive the content of the query, but their identity or the content of the stored message is not revealed. If sensitive data are to be stored in an untrusted server, the data should be encrypted to ensure attackers and administrators cannot access plaintext data without appropriate keys. This method increases security and reduces privacy risks, a simple search is not possible. In 2000, Song et al [1] proposed the SE technique for searching encrypted data, in which the server can support the search function without decrypting the data, with a small information loss
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