A fully homomorphic encryption based on magic number fragmentation and El-Gamal encryption: Smart healthcare use case

Nowadays, cloud computing offers a digital infrastructure for smart city development. Cognitive cities are steadily automating daily urban processes. The ever expanding objective-driven communities gather and share sensitive data that must be stored securely. Cloud computing offers a suitable platform that allows cognitive smart cities to access and re-access data to learn from their past to adapt its current behaviour. However, the cloud is an untrusted entity that may expose data when decrypted for processing by systems. In this paper, we treat the issue of encrypted data processing. Often, the data is encrypted prior to transferring it to the cloud, where the cloud must have the data in clear to be able to make calculations which raises security and privacy threats if the cloud is considered untrusted. The scenario of asking users to make the calculations after decrypting the received cloud data and encrypting the obtained results before sending them back to the cloud is not a practical solution in distributed multi-tenant architectures. Homomorphic encryption allows offers a solution for processing encrypted data. Many existing homomorphic encryption schemes suffer from limitations that hinder their usability. This paper presents an efficient fully homomorphic encryption scheme using twin key encryption and magic number fragmentation. The details of the scheme are presented along with cryptanalytic attacks to assess its effectiveness. The proposed scheme exhibits strong resilience against brute-force attacks compared to its rivals from the literature. Finally, we illustrate the applicability of the proposed scheme using a cognitive smart city application.