Revisiting Secure Computation Using Functional Encryption: Opportunities and Research Directions
Runhua Xu, James Joshi

TL;DR
This paper reviews secure computation methods, emphasizing emerging functional encryption techniques, discussing their advantages, challenges, and future research directions for privacy-preserving applications.
Contribution
It provides a comprehensive overview of traditional secure computation methods and explores the potential of functional encryption as a novel foundation, outlining future research avenues.
Findings
Functional encryption offers promising advantages for secure computation.
Traditional methods face efficiency and security challenges in data-intensive applications.
The paper identifies key research directions for functional encryption in privacy-preserving computation.
Abstract
Increasing incidents of security compromises and privacy leakage have raised serious privacy concerns related to cyberspace. Such privacy concerns have been instrumental in the creation of several regulations and acts to restrict the availability and use of privacy-sensitive data. The secure computation problem, initially and formally introduced as secure two-party computation by Andrew Yao in 1986, has been the focus of intense research in academia because of its fundamental role in building many of the existing privacy-preserving approaches. Most of the existing secure computation solutions rely on garbled-circuits and homomorphic encryption techniques to tackle secure computation issues, including efficiency and security guarantees. However, it is still challenging to adopt these secure computation approaches in emerging compute-intensive and data-intensive applications such as…
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Taxonomy
TopicsCryptography and Data Security · Complexity and Algorithms in Graphs · Privacy-Preserving Technologies in Data
