CERIAS Technical Reports

DOI

10.5703/1288284317684

Date of this Version

11-28-2023

Keywords

cryptography, hardware optimization, argon2i, key derivative function, kdf

Abstract

The challenge of providing data privacy and integrity while maintaining efficient performance for honest users is a persistent concern in cryptography. Attackers exploit advances in parallel hardware and custom circuit hardware to gain an advantage over regular users. One such method is the use of Application-Specific Integrated Circuits (ASICs) to optimize key derivation function (KDF) algorithms, giving adversaries a significant advantage in password guessing and recovery attacks. Other examples include using graphical processing units (GPUs) and field programmable gate arrays (FPGAs). We propose a focused approach to close the gap between adversarial advantage and honest user performance by leveraging the hardware optimization AES-NI (Advanced Encryption Standard New Instructions). AES-NI is widely available in modern x86 architecture microprocessors. Honest users can negate the adversary advantage by diminishing the utility of their computational power. We explore the impact of AES-NI on the Argon2i KDF algorithm, a widely-used and recommended password hashing function. Through our analysis, we demonstrate the effectiveness of incorporating AES-NI in reducing the advantage gained by attackers using ASICs. We also discuss the security and performance trade-offs to provide guidelines for practical implementation in deployed cryptosystems.

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