In recent advancement, network technology is broadly used to store and transmit data between two or more individuals and organizations. For the elevation of virus, hacking of data, electronic theft and fraud, the privacy issues are gradually flourishing in the endeavor of cloud services, edge computing, Internet of Things (IoT), artificial intelligence and its applications and other next generation network applications. So privacy preservation of users’ data is much more in need before saving or sharing them on third-party servers. Moreover, the third-party servers may deal with some operations on the users’ data. The traditional public-key encryption system may be inadequate for such a task and hence generating interest in the study of higher cryptographic primitives like functional encryption (FE) and fully homomorphic encryption (FHE).

       FHE permits untrusted source or parties to do calculations on encrypted data without revealing any original data or secret key. It removes the need for private key exchanges at the server, raising the standard of security and privacy. This is really demanding in areas like healthcare, insurance, finance etc. which deals with extremely sensitive information but depends on cloud server for the seek of computation. The result of such computations remain in encrypted form which the owner can retrieve using his own secret key. Hence, the third-party server can perform calculations on encrypted data but it cannot perform calculations on original data if required. In many fields of application, the untrusted servers need to make some kind of decisions on the basis of the actual results. In such case, FHE cannot fulfill our requirements and we need functional encryption (FE).

      FE is a broad new method for encryption schemes which gives enormous freedom to access encrypted data. An FE scheme allows a user to learn about specific function on encrypted data by restricting functional key and without revealing any information about the original data. FE extends tradition of public key encryption in two different ways - it supports fine-grained access control and permits learning a function on encrypted data.

Fascinatingly, FE and FHE seem to be somehow interconnected. A noteworthy difference between FE and FHE is the method or process in which the functions are applied. In the light of current scenario with countless real-life applications of FE and FHE, I propose to focus my research on designing secure and efficient functional encryption for broader classes of functionals, fully homomorphic encryption in multi-key and threshold setting for distributed network and related cryptographic primitives for preserving privacy in cloud-assisted environments.