Approximate Computing for Cryptography

Dur E.Shahwar Kundi; Ayesha Khalid; Song Bian; Weiqiang Liu

doi:10.1007/978-3-030-98347-5_13

Approximate Computing for Cryptography

Dur E.Shahwar Kundi^*
, Ayesha Khalid^*
, Song Bian^*
, Weiqiang Liu^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Scopus citations

Abstract

Approximate computing enables construction of circuits that are faster and more compact and consume less power at the cost of accuracy of computation. Generally, it has been employed in a lot of error-tolerant applications such as image/multimedia signal processing, machine learning, etc., applications that allow accuracy degradation without quality degradation. But, approximation has also the potential being utilized to provide area and power efficient solutions in the domain of information security. This chapter will survey the practicality of deployment of approximate computing for the cryptographic primitives and applications along with the possible consequences on their correctness as well as security-level reduction.

Original language	English
Title of host publication	Approximate Computing
Publisher	Springer International Publishing
Pages	313-331
Number of pages	19
ISBN (Electronic)	9783030983475
ISBN (Print)	9783030983468
DOIs	https://doi.org/10.1007/978-3-030-98347-5_13
State	Published - 1 Jan 2022
Externally published	Yes

Keywords

Approximate computing
Bitcoin
Hash
Homomorphic encryption (HE)
Information security
Learning with errors (LWE)
Random number generator (RNG)

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10.1007/978-3-030-98347-5_13

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KW - Hash

KW - Homomorphic encryption (HE)

KW - Information security

KW - Learning with errors (LWE)

KW - Random number generator (RNG)

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Approximate Computing for Cryptography

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