Securely Search on Encrypted Data

Abstract

In our usual life, data is all around us, everywhere we look! Now a days every individuals and organizations continue to generate, store, and share vast amounts of data and as a result the role of cloud storage becomes important to us. In the context of cloud computing, where vast amounts of data are stored and processed remotely, ensuring the privacy and security of sensitive information becomes even more challenging. Traditional approaches to data storage and retrieval often require decrypting the data on the cloud server, which introduces the security concerns of the data. One promising solution to address this concern is to enable secure search operations on data that is stored in the cloud in an encrypted form. Implementing a searchable encryption scheme using Homomorphic Encryption (HE) allow users to perform searches on encrypted data without compromising its confidentiality. By developing such a scheme, this thesis aims to contribute to the advancement of privacy-preserving data management in cloud environments. With HE, complex mathematical operations can be conducted on ciphertexts, preserving the privacy of the underlying data throughout the computation. This opens up a path for searching and retrieving data from an encrypted dataset, as it enables to operate directly on encrypted inputs and produce encrypted outputs, thereby ensuring end-to-end data confidentiality. However, the adoption of HE on encrypted data is not without its challenges. The computational overhead associated with HE operations, coupled with performance limitations, poses significant obstacles to scalability and efficiency. In light of these considerations, the aim of this thesis is to build a practical scheme using Homomorphic Encryption (HE) for encrypted searching. By investigating the applications, challenges, and potential contributions of HE in secure search operations, this research endeavors to advance our understanding of privacy-preserving data management and pave the way for practical implementations in real-world scenarios