Feel the Quantum Functioning: Instantiating Generic Multi-Input Functional Encryption from Learning with Errors

Bakas, Alexandros; Michalas, Antonis; Frimpong, Eugene; Rabaninejad, Reyhaneh

doi:10.1007/978-3-031-10684-2_16

Cited by 2 publications

(1 citation statement)

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“…To this day, most works in FE revolve around designing schemes for sums [13,8,11], inner products [1,3,2], as well as quadratic functions [40]. Unfortunately, except a handful works that rely on Multi-Party Computation (MPC) [11,12], most of FE schemes are highly centralized and require the existence of a fully trusted central authority. -Provable Secure Protocols for Cloud Security using HHE : Designing provable secure protocols that utilize modern cryptography is not novel.…”

Section: Related Workmentioning

confidence: 99%

Symmetrical Disguise: Realizing Homomorphic Encryption Services from Symmetric Primitives

Bakas

Frimpong

Michalas

2023

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Homomorphic Encryption (HE) is a modern cryptographic technique that allows direct computations on encrypted data. While relatively new to the mainstream debate, HE has been a solid topic in research for decades. However, and despite the technological advances of the past years, HE's inefficiencies render it impractical for deployment in realistic scenarios. Hence research in the field is still in its initial phase. To overcome certain challenges and bring HE closer to a realization phase, researchers recently introduced the promising concept of Hybrid Homomorphic Encryption (HHE) -a primitive that combines symmetric cryptography with HE. Using HHE, users perform local data encryptions using a symmetric encryption scheme and then outsource them to the cloud. Upon reception, the cloud can transform the symmetrically encrypted data to homomorphic ciphertexts without decrypting them. Such an approach can be seen as an opportunity to build new, privacy-respecting cloud services, as the most expensive operations of HE can be moved to the cloud. In this work, we undertake the task of designing a secure cryptographic protocol based on HHE. In particular, we show how HHE can be used as the main building block of a protocol that allows an analyst to collect data from multiple sources and compute specific functions over them, in a privacy-preserving way. To the best of our knowledge, this is the first work that aims at demonstrating how HHE can be utilized in realistic scenarios, through the design of a secure protocol.

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