Cited by 35Cryptographic Implementations and SecurityIoT and Edge/Fog ComputingAdvanced Authentication Protocols Security

Clock Frequency Impact on the Performance of High-Security Cryptographic Cipher Suites for Energy-Efficient Resource-Constrained IoT Devices

Open access
Suárez-Albela, Manuel, Fraga-Lamas, Paula, Castedo, Luis, Fernández-Caramés, Tiago M.·2018·Sensors

Abstract

Modern Internet of Things (IoT) systems have to be able to provide high-security levels, but it is difficult to accommodate computationally-intensive cryptographic algorithms on the resource-constrained hardware used to deploy IoT end nodes. Although this scenario brings the opportunity for using advanced security mechanisms such as Transport Layer Security (TLS), several configuration factors impact both the performance and the energy consumption of IoT systems. In this study, two of the most used TLS authentication algorithms (ECDSA and RSA) were compared when executed on a resource-constrained IoT node based on the ESP32 System-on-Chip (SoC), which was tested at different clock frequencies (80, 160 and 240 MHz) when providing different security levels (from 80 to 192 bits). With every tested configuration, energy consumption and average time per transaction were measured. The results show that ECDSA outperforms RSA in all performed tests and that certain software implementations may lead to scenarios where higher security-level alternatives outperform cryptosystems that are theoretically simpler and lighter in terms of energy consumption and data throughput. Moreover, the performed experiments allow for concluding that higher clock frequencies provide better performance in terms of throughput and, in contrast to what may be expected, less energy consumption.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/s19010015

Cites

44 of 44 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Some Industry 4.0 applications store every performed transaction to be able to carry out audits, keep accurate traceability records or make use of Big Data techniques or predictive analytics.

    “Some Industry 4.0 applications follow this approach in a strict way and store every performed transaction to be able to carry out audits, to keep accurate traceability records or to make use of Big Data techniques or predictive analytics [27], [28].”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [29]Lenstra A.K. Key Lengths Contribution to The Handbook of Information Security Wiley Hoboken, NJ, USA 2004

Cited by

Sorted by citations

Authors
Suárez-Albela, M., Fraga-Lamas, P., Castedo, L., & Fernández-Caramés, T. M.
Affiliations
  • Universidade da Coruña (ES)
  • Department of Computer Engineering, Faculty of Computer Science, Universidade da Coruña, 15071 A Coruña, Spain
Venue
Sensors
Publisher
MDPI AG
Published
2018-12-20
Volume
19
Issue
1
Pages
15
ISSN
1424-8220 (ISSN-L)
OpenAlex
W2904270603
Cited by
35
References
44
Citations by year
2025: 2 · 2024: 2 · 2023: 3 · 2022: 6 · 2021: 9 · 2020: 7 · 2019: 5 · 2014: 1
FWCI
2.96
Type
journal article
Language
en
Open access
Locations
  • Sensors (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • RUC (Universidade Da Coruña) (submittedVersion, cc-by)
Funders
  • Xunta de Galicia (ED431C 2016-045, ED341D R2016/012, ED431G/01)
  • Agencia Estatal de Investigación of Spain and ERDF funds of the EU (AEI/FEDER, UE) (TEC2013-47141-C4-1-R, TEC2015-69648-REDC, TEC2016-75067-C4-1-R)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Cryptographic Implementations and Security
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Computer Science › Computer Networks and Communications › Advanced Authentication Protocols Security
Keywords
clock frequency, Internet of Things, resource-constrained devices, Transport Layer Security, ECDSA, energy consumption, cryptographic performance, key size, throughput, Internet of Things security

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review