Clock Frequency Impact on the Performance of High-Security Cryptographic Cipher Suites for Energy-Efficient Resource-Constrained IoT Devices
Open accessAbstract
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.
Integrity signals
Registry
Cites
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.
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].”
From A Review on the Application of Blockchain to the Next Generation of Cybersecure Industry 4.0 Smart Factories (2019) · cites this paper as [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
The Transport Layer Security (TLS) Protocol Version 1.1
Dierks, T., & Rescorla, E. (2006) · doi:10.17487/rfc4346 · Cited by 2,287 · see citing works
Comparing Elliptic Curve Cryptography and RSA on 8-bit CPUs
Gura, N., Patel, A. S., Wander, A. S., Eberle, H., & Shantz, S. C. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-28632-5_9 · Cited by 1,212 · see citing works
A Comprehensive Study of Security of Internet-of-Things
Mosenia, A., & Jha, N. K. (2016) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2016.2606384 · Cited by 817 · see citing works
A Survey on the Internet of Things Security
Zhao, K., & Ge, L. (2013) · International Conference on Computational Intelligence and Security (CIS) · doi:10.1109/cis.2013.145 · Cited by 712 · see citing works
A smart home energy management system using IoT and big data analytics approach
Al-Ali, A. R., Zualkernan, I. A., Rashid, M., Gupta, R., & Alikarar, M. (2017) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2017.015014 · Cited by 670 · see citing works
Datagram Transport Layer Security Version 1.2
Rescorla, E., & Modadugu, N. (2012) · doi:10.17487/rfc6347 · Cited by 641 · see citing works
Efficient Energy Management for the Internet of Things in Smart Cities
Ejaz, W., Naeem, M., Shahid, A., Anpalagan, A., & Jo, M. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1600218cm · Cited by 492 · see citing works
Introduction to Hardware Security and Trust
Tehranipoor, M., & Wang, C. (2011) · Springer eBooks · doi:10.1007/978-1-4419-8080-9 · Cited by 479 · see citing works
Security attacks in IoT: A survey
Deogirikar, J., & Vidhate, A. V. (2017) · International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · doi:10.1109/i-smac.2017.8058363 · Cited by 470 · see citing works
Turner, S. (2014) · IEEE Internet Computing · doi:10.1109/mic.2014.126 · Cited by 452 · see citing works
A study of the energy consumption characteristics of cryptographic algorithms and security protocols
Potlapally, N. R., Ravi, S., Raghunathan, A., & Jha, N. K. (2006) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2006.16 · Cited by 428 · see citing works
Fog Computing May Help to Save Energy in Cloud Computing
Jalali, F., Hinton, K., Ayre, R., Alpcan, T., & Tucker, R. S. (2016) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2016.2545559 · Cited by 408 · see citing works
Recommendation for Key Management Part 1: General
Barker, E. B. (2016) · doi:10.6028/nist.sp.800-57pt1r4 · Cited by 396 · see citing works
Cyber and Physical Security Vulnerability Assessment for IoT-Based Smart Homes
Ali, B., & Awad, A. (2018) · Sensors · doi:10.3390/s18030817 · Cited by 344 · see citing works
An energy-efficient architecture for the Internet of Things (IoT)
Kaur, N., & Sood, S. K. (2017) · IEEE Systems Journal · doi:10.1109/jsyst.2015.2469676 · Cited by 282 · see citing works
Management of resource constrained devices in the internet of things
Sehgal, A., Perelman, V., Kuryla, S., & Schönwälder, J. (2012) · IEEE Communications Magazine · doi:10.1109/mcom.2012.6384464 · Cited by 245 · see citing works
A Review on Internet of Things for Defense and Public Safety
Fraga-Lamas, P., Fernández-Caramés, T., Suárez-Albela, M., Castedo, L., & González-López, M. (2016) · Sensors · doi:10.3390/s16101644 · Cited by 242 · see citing works
Self-citationThe Benefits of Self-Awareness and Attention in Fog and Mist Computing
Preden, J., Tammemäe, K., Jantsch, A., Leier, M., Riid, A., & Calis, E. (2015) · Computer · doi:10.1109/mc.2015.207 · Cited by 175 · see citing works
On the Security and Privacy of Internet of Things Architectures and Systems
Vasilomanolakis, E., Daubert, J., Luthra, M., Gazis, V., Wiesmaier, A., & Kikiras, P. K. (2015) · International Workshop Secure Internet Things · doi:10.1109/siot.2015.9 · Cited by 145 · see citing works
A Survey of NFC Sensors Based on Energy Harvesting for IoT Applications
Lázaro, A., Villarino, R., & Girbau, D. (2018) · Sensors · doi:10.3390/s18113746 · Cited by 145 · see citing works
A federated architecture approach for Internet of Things security
Leo, M., Battisti, F., Carli, M., & Neri, A. (2014) · Euro Med Telco Conference (EMTC) · doi:10.1109/emtc.2014.6996632 · Cited by 131 · see citing works
M2M Security: Challenges and Solutions
Barki, A., Bouabdallah, A., Gharout, S., & Traoré, J. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2515516 · Cited by 126 · see citing works
Suárez-Albela, M., Fernández-Caramés, T., Fraga-Lamas, P., & Castedo, L. (2017) · Sensors · doi:10.3390/s17091978 · Cited by 125 · see citing works
Self-citationSuárez-Albela, M., Fraga‐Lamas, P., & Fernández‐Caramés, T. M. (2018) · Sensors · doi:10.3390/s18113868 · Cited by 122 · see citing works
Self-citationRF Energy Harvesting and Transfer for Spectrum Sharing Cellular IoT Communications in 5G Systems
Ercan, A. Ö., Sunay, M. O., & Akyildiz, I. F. (2017) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2017.2740378 · Cited by 102 · see citing works
A Practical Performance Comparison of ECC and RSA for Resource-Constrained IoT Devices
Suárez-Albela, M., Fernández‐Caramés, T. M., Fraga‐Lamas, P., & Castedo, L. (2018) · Global Internet of Things Summit (GIoTS) · doi:10.1109/giots.2018.8534575 · Cited by 102 · see citing works
Self-citationIoT in the Fog: A Roadmap for Data-Centric IoT Development
Oteafy, S., & Hassanein, H. S. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2018.1700299 · Cited by 90 · see citing works
Moving to the Edge-Cloud-of-Things: Recent Advances and Future Research Directions
Bangui, H., Rakrak, S., Raghay, S., & Bühnová, B. (2018) · Electronics · doi:10.3390/electronics7110309 · Cited by 86 · see citing works
Using Raw Public Keys in Transport Layer Security (TLS) and Datagram Transport Layer Security (DTLS)
Gilmore, J., Weiler, S., & Kivinen, T. (2014) · doi:10.17487/rfc7250 · Cited by 56 · see citing works
Modeling energy-efficient secure communications in multi-mode wireless mobile devices
Castiglione, A., Palmieri, F., Fiore, U., et al. (2014) · Journal of Computer and System Sciences · doi:10.1016/j.jcss.2014.12.022 · Cited by 54 · see citing works
A Reference Architecture for Improving Security and Privacy in Internet of Things Applications
Addo, I. D., Ahamed, S. I., Yau, S. S., & Buduru, A. B. (2014) · IEEE International Conference on Mobile Services · doi:10.1109/mobserv.2014.24 · Cited by 54 · see citing works
Provided security measures of enabling technologies in Internet of Things (IoT): A survey
Grabovica, M., Popic, S., Pezer, D., et al. (2016) · doi:10.1109/zinc.2016.7513647 · Cited by 41 · see citing works
Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things
Bagula, A., Abidoye, A. P., & Zodi, G.-A. L. (2015) · Sensors · doi:10.3390/s16010009 · Cited by 38 · see citing works
Comparison of ECC and RSA algorithm in multipurpose smart card application
Savari, M., Montazerolzohour, M., & Thiam, Y. E. (2012) · doi:10.1109/cybersec.2012.6246121 · Cited by 28 · see citing works
A Methodology for Evaluating Security in Commercial RFID Systems
Fernández-Caramés, T. M., Fraga-Lamas, P., Suárez-Albela, M., & Castedo, L. (2017) · Radio Frequency Identification · doi:10.5772/64844 · Cited by 28 · see citing works
Self-citationSecure communication in IP-based wireless sensor networks via a trusted gateway
den Abeele, F. V., Vandewinckele, T., Hoebeke, J., Moerman, I., & Demeester, P. (2015) · International Conference on Intelligent Sensors, Sensor Networks and Information Processing · doi:10.1109/issnip.2015.7106963 · Cited by 19 · see citing works
Energy analysis for wireless sensor networks
Noroozi, E., Kadivar, J., & shafiee, S. H. (2010) · International Conference on Mechanical and Electronics Engineering · doi:10.1109/icmee.2010.5558401 · Cited by 17 · see citing works
Radio Frequency Identification
Crepaldi, P., & Pimenta, T. C. (2017) · InTech eBooks · doi:10.5772/62606 · Cited by 17 · see citing works
Lenstra, A. K., Kleinjung, T., & Thomé, E. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-42001-6_9 · Cited by 13 · see citing works
de Oliveira, P. R., Feltrim, V. D., Martimiano, L. A. F., & Zanoni, G. B. M. (2014) · IEEE Latin America Transactions · doi:10.1109/tla.2014.6894012 · Cited by 13 · see citing works
An analysis of energy consumption under various memory mappings for FRAM-based IoT devices
Kim, M., Lee, J., Kim, Y., et al. (2018) · IEEE World Forum on Internet of Things (WF-IoT) · doi:10.1109/wf-iot.2018.8355212 · Cited by 11 · see citing works
A Resource Efficient Architecture for RSA and Elliptic Curve Cryptosystems
Wu, S., & Zhu, Y. (2006) · International Conference on Communications, Circuits and Systems · doi:10.1109/icccas.2006.285150 · Cited by 5 · see citing works
Standards-based end-to-end IP security for the Internet of Things
Hummen, R., & Wehrle, K. (2013) · Proceedings/Proceedings - International Conference on Network Protocols · doi:10.1109/icnp.2013.6733648 · Cited by 5 · see citing works
Energy-Efficient Scheduling for Hybrid Tasks in Control Devices for the Internet of Things
Gao, Z. P., Wu, Y., Dai, G., et al. (2012) · Sensors · doi:10.3390/s120811334 · Cited by 3 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [29]Lenstra A.K. Key Lengths Contribution to The Handbook of Information Security Wiley Hoboken, NJ, USA 2004
Cited by
Sorted by citations
Fernandez-Carames, T. M., & Fraga-Lamas, P. (2020) · IEEE Access · doi:10.1109/access.2020.2968985 · Cited by 607 · see citing works
Self-citationFernandez-Carames, T. M., & Fraga-Lamas, P. (2019) · IEEE Access · doi:10.1109/access.2019.2908780 · Cited by 321 · see citing works
Self-citation
- 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)
- PMC
- PMC6338922
- 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
- gold
- dx.doi.org
- Licence
- 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