- Sponsor:
- sigsac
It is our great pleasure to welcome you to the 10th annual Workshop on Encrypted Computing and Applied Homomorphic Cryptography - WAHC'22. WAHC was created in 2013 as a forum to organize and foster discussion of a wide variety of aspects of encrypted computing and secure computation.
In a world where distance is no longer an obstacle for cooperation, secure computation is becoming a key feature of current and future information systems. Distributed network applications and cloud architectures are at danger because lots of personal consumer data is aggregated in all kinds of formats and for various purposes. Industry and consumer electronics companies are facing massive threats like theft of intellectual property and industrial espionage. Public infrastructure has to be secured against sabotage and manipulation. A possible solution is encrypted computing: Data can be processed on remote, possibly insecure resources, while program code and data is encrypted all the time. This allows to outsource the computation of confidential information independently from the trustworthiness or the security level of the remote system. The goal of the workshop is to bring together researchers with practitioners and industry to present, discuss and to share the latest progress in the field. We want to exchange ideas that address real-world problems with practical approaches and solutions.
The workshop is typically uniformly attended by academia, government, and industry, with attendees both from prior years with experience in the domain and new attendees learning from the community. Specific encrypted computing technologies focus on homomorphic encryption and secure multiparty computation but also need to interoperate with existing technologies and infrastructures. The technologies and techniques discussed in this workshop are key to extending the range of applications that can be securely and practically outsourced.
Proceeding Downloads
Liberating TFHE: Programmable Bootstrapping with General Quotient Polynomials
All known instantiations for fully homomorphic encryption (FHE) produce noisy ciphertexts and rely on a technique called bootstrapping to reduce the noise so as to enable an arbitrary number of homomorphic operations. Bootstrapping is the main ...
Efficient Homomorphic Evaluation of Arbitrary Bivariate Integer Functions
We propose how to homomorphically evaluate arbitrary bivariate integer functions such as division. A prior work proposed by Okada et al.\ (WISTP'18) uses polynomial evaluations such that the scheme is still compatible with the SIMD operations in BFV and ...
PROBONITE: PRivate One-Branch-Only Non-Interactive decision Tree Evaluation
Decision trees are among the most widespread machine learning models used for data classification, in particular due to their interpretability that makes it easy to explain their prediction. In this paper, we propose a novel protocol for the private ...
Efficient and Accurate Homomorphic Comparisons
We design and implement a new efficient and accurate fully homomorphic argmin/min or argmax/max comparison operator, which finds its application in numerous real-world use cases as a classifier. In particular we propose two versions of our algorithms ...
Acceleration of Homomorphic Unrolled Trace-Type Function using AVX512 instructions
More and more data analysis is being outsourced due to the spread of cloud computing. Therefore, protection of the data from privacy violations and information leaks is required. In particular, homomorphic encryption, which allows computation to be ...
OpenFHE: Open-Source Fully Homomorphic Encryption Library
- Ahmad Al Badawi,
- Jack Bates,
- Flavio Bergamaschi,
- David Bruce Cousins,
- Saroja Erabelli,
- Nicholas Genise,
- Shai Halevi,
- Hamish Hunt,
- Andrey Kim,
- Yongwoo Lee,
- Zeyu Liu,
- Daniele Micciancio,
- Ian Quah,
- Yuriy Polyakov,
- Saraswathy R.V.,
- Kurt Rohloff,
- Jonathan Saylor,
- Dmitriy Suponitsky,
- Matthew Triplett,
- Vinod Vaikuntanathan,
- Vincent Zucca
Fully Homomorphic Encryption (FHE) is a powerful cryptographic primitive that enables performing computations over encrypted data without having access to the secret key. We introduce OpenFHE, a new open-source FHE software library that incorporates ...
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Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
WAHC '18 | 17 | 6 | 35% |
Overall | 17 | 6 | 35% |