Leakless privacy-preserving multi-keyword ranked search over encrypted cloud data
Khosro Salmani, Ken Barker · Journal of Surveillance Security and Safety · 2020
Aim: During the last decade, various type of cloud services have encouraged individuals and enterprises to store personal data in the cloud.Despite its flexibility, cost efficiency, and convenient service, protecting security and privacy of the outsourced data has always been a primary challenge.Although data encryption retains the outsourced data's security and privacy to some extent, it does not permit traditional plaintext keyword search mechanisms, and it comes at the cost of efficiency.Hence, proposing an efficient encrypted cloud data search service would be an important step forward.Related work focuses on single keyword search and even those which support multi-keyword search suffer from private information leakage.Methods: Our proposed method, employs the secure inner product similarity and our chaining encryption notion.The former helps to provide sufficient search accuracy and the latter yields the privacy requirements.Results: In this paper, we address the problem of leakless privacy-preserving multi-keyword ranked search over encrypted cloud data (LRSE), and our new contributions address challenging problems of search pattern, and cooccurrence information leakage in the cloud.Conclusion: Our security and performance analysis shows that the proposed scheme guarantees a high level of privacy/security and efficiency.