Homomorphic Encryption Scheme Parties, Platforms, Techniques, Complexities, Limitations and Future Directions: A Systematic Review

Abstract

Homomorphic Encryption (HE) is a cryptographic encryption technique that allows computational functions being carried out on encrypted data with the view of maintaining the functional properties of the data that is encrypted. The outcome is that the computation performed on the encrypted data remain the same as the decrypted data. Homomorphic Encryption revolved around privacy enhancing technology which react to the challenges of data sharing in an organization such as Personal Identifiable Information, Health Care Information, and Financial Transaction Data. All these data require privacy which is a prevalent issue. Significant achievement and advancement has been achieved in the design, development and implementation of HE techniques, thereby enhancing their efficiency and its practical applicability. This study would explore the parties, platforms, techniques, complexities and limitations associated with HE Schemes. Articles written in English, published in peer-reviewed academic journals, and released between 2020 and 2025 met the inclusion criteria. In the end, this study examined 40 relevant articles in total. The review delves into the most recent advancement in HE techniques, complexities and limitations. Also, focus is given to the roles and responsibilities of various stakeholders, platforms and challenges encountered in real world application. Our key finding indicates that while HE offers important privacy benefits on applications, its deployment may be hindered by massive computational and communication overheads. This study clarifies the potential of HE in addressing the challenges in data privacy and security as it is applied in real-world situations such as cloud computing environments and federated learning while maintaining its computation feasibility.