CryptoDB
Hao Cheng
Publications
Year
Venue
Title
2024
TCHES
eLIMInate: a Leakage-focused ISE for Masked Implementation
Abstract
Even given a state-of-the-art masking scheme, masked software implementation of some cryptography functionality can pose significant challenges stemming, e.g., from simultaneous requirements for efficiency and security. In this paper we design an Instruction Set Extension (ISE) to address a specific element of said challenge, namely the elimination of leakage stemming from architectural and microarchitectural overwriting. Conceptually, the ISE allows a leakage-focused behavioural hint to be communicated from software to the micro-architecture: using it informs how computation is realised when applied to masking-specific data, which then offers an opportunity to eliminate associated leakage. We develop prototype, latencyand area-optimised implementations of the ISE design based on the RISC-V Ibex core. Using them, we demonstrate that use of the ISE can close the gap between assumptions about and actual behaviour of a device and thereby deliver an improved security guarantee.
2022
TCHES
Highly Vectorized SIKE for AVX-512
Abstract
It is generally accepted that a large-scale quantum computer would be capable to break any public-key cryptosystem used today, thereby posing a serious threat to the security of the Internet’s public-key infrastructure. The US National Institute of Standards and Technology (NIST) addresses this threat with an open process for the standardization of quantum-safe key establishment and signature schemes, which is now in the final phase of the evaluation of candidates. SIKE (an abbreviation of Supersingular Isogeny Key Encapsulation) is one of the alternate candidates under evaluation and distinguishes itself from other candidates due to relatively short key lengths and relatively high computing costs. In this paper, we analyze how the latest generation of Intel’s Advanced Vector Extensions (AVX), in particular AVX-512IFMA, can be used to minimize the latency (resp. maximize the hroughput) of the SIKE key encapsulation mechanism when executed on Ice Lake CPUs based on the Sunny Cove microarchitecture. We present various techniques to parallelize and speed up the base/extension field arithmetic, point arithmetic, and isogeny computations performed by SIKE. All these parallel processing techniques are combined in AvxSike, a highly optimized implementation of SIKE using Intel AVX-512IFMA instructions. Our experiments indicate that AvxSike instantiated with the SIKEp503 parameter set is approximately 1.5 times faster than the to-date best AVX-512IFMA-based SIKE software from the literature. When executed on an Intel Core i3-1005G1 CPU, AvxSike outperforms the x64 assembly implementation of SIKE contained in Microsoft’s SIDHv3.4 library by a factor of about 2.5 for key generation and decapsulation, while the encapsulation is even 3.2 times faster.
2022
TCHES
RISC-V Instruction Set Extensions for Lightweight Symmetric Cryptography
Abstract
The NIST LightWeight Cryptography (LWC) selection process aims to standardise cryptographic functionality which is suitable for resource-constrained devices. Since the outcome is likely to have significant, long-lived impact, careful evaluation of each submission with respect to metrics explicitly outlined in the call is imperative. Beyond the robustness of submissions against cryptanalytic attack, metrics related to their implementation (e.g., execution latency and memory footprint) form an important example. Aiming to provide evidence allowing richer evaluation with respect to such metrics, this paper presents the design, implementation, and evaluation of one separate Instruction Set Extension (ISE) for each of the 10 LWC final round submissions, namely Ascon, Elephant, GIFT-COFB, Grain-128AEADv2, ISAP, PHOTON-Beetle, Romulus, Sparkle, TinyJAMBU, and Xoodyak; although we base the work on use of RISC-V, we argue that it provides more general insight.
2021
TCHES
Batching CSIDH Group Actions using AVX-512
📺
Abstract
Commutative Supersingular Isogeny Diffie-Hellman (or CSIDH for short) is a recently-proposed post-quantum key establishment scheme that belongs to the family of isogeny-based cryptosystems. The CSIDH protocol is based on the action of an ideal class group on a set of supersingular elliptic curves and comes with some very attractive features, e.g. the ability to serve as a “drop-in” replacement for the standard elliptic curve Diffie-Hellman protocol. Unfortunately, the execution time of CSIDH is prohibitively high for many real-world applications, mainly due to the enormous computational cost of the underlying group action. Consequently, there is a strong demand for optimizations that increase the efficiency of the class group action evaluation, which is not only important for CSIDH, but also for related cryptosystems like the signature schemes CSI-FiSh and SeaSign. In this paper, we explore how the AVX-512 vector extensions (incl. AVX-512F and AVX-512IFMA) can be utilized to optimize constant-time evaluation of the CSIDH-512 class group action with the goal of, respectively, maximizing throughput and minimizing latency. We introduce different approaches for batching group actions and computing them in SIMD fashion on modern Intel processors. In particular, we present a hybrid batching technique that, when combined with optimized (8 × 1)-way prime-field arithmetic, increases the throughput by a factor of 3.64 compared to a state-of-the-art (non-vectorized) x64 implementation. On the other hand, vectorization in a 2-way fashion aimed to reduce latency makes our AVX-512 implementation of the group action evaluation about 1.54 times faster than the state-of-the-art. To the best of our knowledge, this paper is the first to demonstrate the high potential of using vector instructions to increase the throughput (resp. decrease the latency) of constant-time CSIDH.
Coauthors
- Hao Cheng (4)
- Georgios Fotiadis (2)
- Johann Großschädl (3)
- Ben Marshall (1)
- Dan Page (1)
- Daniel Page (1)
- Thinh Pham (1)
- Peter B. Rønne (1)
- Peter Y. A. Ryan (2)
- Weijia Wang (1)