EFFICIENT AND EXPRESSIVE SEARCH OVER ENCRYPTED DATA WITH MULTI FACTOR AUTHENTICATION SCHEME

Abstract

More data owners are tempted to outsource their data to cloud services as a result of the development of cloud storage. Sensitive data should be encrypted before being outsourced due to privacy concerns. To assure data availability, a variety of searchable encryption techniques are used. However, the effectiveness of data consumers' queries is not given much consideration by the current search algorithms, particularly in the case of several owners. In this study, linguistic coefficients are used to create an encrypted search index. In particular, the encrypted search index utilizing Lagrange co-efficient makes use of secure inner-product calculation for both search and relevance assessment by taking into account a sizable amount of data in the cloud. A system architecture of preferred search over encrypted data in the cloud scene is built, and the requirements in terms of efficiency and privacy are specified. This enables the clo ud servers to do a secure search without knowing any sensitive data (e.g., keywords and trapdoors).For each data owner, the Lagrange coefficient is used to build indices that can support searches over numerous keyword fields and enable accu rate relevance computation in order to produce an efficient search.To protect user data privacy, a multifactor authenticati on technique might be utilised.After logging in to the system, the user will receive three different sorts of authentications, including an OTP utilizing a number, a captcha, and an OTP image. This picture will serve as a key. In order to accomplish secure search and relevance score calculation, the user's preference and the search query are expressed in vector form. Additionally, Preferred Search over Encrypted Data (PSED) is consistent with cloud computing's scalability and adaptability. Finally, a thorough security study verifies the security of our scheme, and a performance analysis highlights its effectiveness and efficiency. Keywords: Encrypted Data, Inner product calculation, Multifactor authentication, Data privacy