Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/28789
Title: Digital Signatures and Signcryption Schemes on Embedded Devices: a Trade-off between Computation and Storage
Authors: Winderickx, Jori
Braeken, An
Singelee, Dave
Peeters, Roel
VANDENRYT, Thijs 
THOELEN, Ronald 
MENTENS, Nele 
Issue Date: 2018
Publisher: ASSOC COMPUTING MACHINERY
Source: 2018 ACM INTERNATIONAL CONFERENCE ON COMPUTING FRONTIERS, ASSOC COMPUTING MACHINERY,p. 342-347
Abstract: This paper targets the efficient implementation of digital signatures and signcryption schemes on typical internet-of-things (IoT) devices, i.e. embedded processors with constrained computation power and storage. Both signcryption schemes (providing digital signatures and encryption simultaneously) and digital signatures rely on computation-intensive public-key cryptography. When the number of signatures or encrypted messages the device needs to generate after deployment is limited, a trade-off can be made between performing the entire computation on the embedded device or moving part of the computation to a precomputation phase. The latter results in the storage of the precomputed values in the memory of the processor. We examine this trade-off on a health sensor platform and we additionally apply storage encryption, resulting in five implementation variants of the considered schemes.
Notes: [Winderickx, Jori; Singelee, Dave; Peeters, Roel; Mentens, Nele] Katholieke Univ Leuven, IMEC, COSIC, Leuven, Belgium. [Winderickx, Jori; Mentens, Nele] Katholieke Univ Leuven, ES&S, Leuven, Belgium. [Braeken, An] Vrije Univ Brussel, Ind Engn INDI, Brussels, Belgium. [Vandenryt, Thijs; Thoelen, Ronald] Hasselt Univ, IMO, IMOMEC, Hasselt, Belgium.
Keywords: Internet of Things; Digital signature; Public-key cryptography; Signcryption; Schnorr; Health sensor platform; Storage encryption; Precomputation;Internet of Things; Digital signature; Public-key cryptography; Signcryption; Schnorr; Health sensor platform; Storage encryption; Precomputation
Document URI: http://hdl.handle.net/1942/28789
ISBN: 9781450357616
DOI: 10.1145/3203217.3206426
ISI #: 000455156500054
Rights: 2018 ACM.
Category: C1
Type: Proceedings Paper
Validations: ecoom 2020
Appears in Collections:Research publications

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