Boosting Verifiable Computation on Encrypted Data

Explore a conference talk from PKC 2020 that delves into boosting verifiable computation on encrypted data. Learn about the challenges and solutions in ensuring integrity of computations on encrypted information, including the use of SNARKs (Succinct Non-interactive ARguments of Knowledge) for lazy clients. Discover how publicly verifiable computation with privacy is achieved through techniques like polynomial commitments and the commit & prove methodology. Gain insights into arithmetic circuits over polynomials, multi-polynomial commitments, and the reuse of commitments for efficiency. Understand the implications of this research for applications such as pandemic biometric surveillance systems and fully homomorphic encryption, ultimately leading to verifiable and private delegation of computation.

Boosting Verifiable Computation on Encrypted Data
Pandemics biometric surveillance systems
(Fully) Homomorphic Encryption
Solution for Integrity of the Computation
SNARKS = Proof Systems for lazy clients
Full Solution: Verifiable Computation on Encrypted Data
Publicly Verifiable Computation with Privacy
Arithmetic Circuit over Polynomials
Compress Circuit over Polynomials
Idea: Commit & Prove Methodology
Polynomial Commitments - hiding inputs
Multi-Polynomial Commitments
Commit & Prove Evaluation
Proof of Arithmetic Circuit over Scalars
Reuse the same commitment
Verifiable and private delegation of computation