PROJECT TITLE :

ESVSSE Enabling Efficient, Secure, Verifiable Searchable Symmetric Encryption

ABSTRACT:

It is believed that symmetric searchable encryption, also known as SSE, will solve the problem of privacy in data outsourcing while also maintaining operability and confidentiality. However, the vast majority of SSE schemes operate under the assumption that the cloud is trustworthy but inquisitive. It is not always the case that this assumption is correct. And even if some schemes supported verification, integrity, or freshness checking in a malicious cloud, the performance and security functionalities are not being fully exploited even though they have the potential to do so. In this paper, we propose an efficient SSE scheme that supports secure verification, dynamic updating, and multi-user queries. This scheme is based on B+-Tree and Counting Bloom Filter (CBF). When compared to the previous state of the art, we designed the new data structure CBF to support dynamic updating and boost verification. This was done in order to compare favorably with the state of the art. Additionally, in order to stop the malicious cloud from launching a replay attack, we make use of the timestamp mechanism that is included in the scheme. The newly designed CBF functions similarly to a front-engine to reduce the amount of money spent by users on querying and verifying information. When there is no value that matches the keyword that is being queried, it is able to achieve more efficient querying and verification with a negligible amount of false positives. The Bloom Filter is combined with a one-dimensional array that has counting capabilities to create the CBF, which enables the CBF to support efficient dynamic updating. In addition, we are in charge of the development of the authenticator for CBF. We choose to use B+-Tree because it is a popular choice among a variety of database engines and file systems. In addition to that, we present a condensed proof of our scheme's safety. After that, we will present a comprehensive performance analysis. In the end, we put our plan through its paces by conducting exhaustive experiments. The findings support our interpretation of the data and indicate that the proposed system is not only safe but also more effective than other schemes that have been proposed in the past that have the same functionalities. When there is a missing rate of 20 percent of the searching keywords, the average performance of both the cloud servers and the users can be improved by approximately 20 percent, which is a significant amount. And the missing rate itself has a direct correlation to how much room there is for improvement in overall performance.