CRJun 11, 2016

Egalitarian computing

arXiv:1606.03588v226 citations
Originality Incremental advance
AI Analysis

This addresses security vulnerabilities for users in cryptographic applications by making attacks more costly, though it builds incrementally on existing memory-hard functions.

The paper tackles the problem of adversaries gaining an advantage through specialized hardware in various contexts like password processing and cryptocurrency mining, proposing memory-hard computing as a paradigm to equalize cost-performance ratios between users and attackers, with new schemes such as MTP and MHE.

In this paper we explore several contexts where an adversary has an upper hand over the defender by using special hardware in an attack. These include password processing, hard-drive protection, cryptocurrency mining, resource sharing, code obfuscation, etc. We suggest memory-hard computing as a generic paradigm, where every task is amalgamated with a certain procedure requiring intensive access to RAM both in terms of size and (very importantly) bandwidth, so that transferring the computation to GPU, FPGA, and even ASIC brings little or no cost reduction. Cryptographic schemes that run in this framework become egalitarian in the sense that both users and attackers are equal in the price-performance ratio conditions. Based on existing schemes like {Argon2} and the recent generalized-birthday proof-of-work, we suggest a generic framework and two new schemes: MTP, a memory-hard Proof-of-Work based on the memory-hard function with fast verification and short proofs. It can be also used for memory-hard time-lock puzzles. {MHE}, the concept of memory-hard encryption, which utilizes available RAM to strengthen the encryption for the low-entropy keys (allowing to bring back 6 letter passwords).

Foundations

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