Smart City Gnosys

Smart city article details

Title A Systematic Review On Lightweight Security Algorithms For A Sustainable Iot Infrastructure
ID_Doc 5489
Authors Sarker K.U.
Year 2025
Published Discover Internet of Things, 5, 1
DOI http://dx.doi.org/10.1007/s43926-025-00150-4
Abstract Operational technology, industrial automation, advanced healthcare systems, and smart city infrastructures are common forms of IoT integrated distributed networks. Numerous IoT components require vast amounts of power for sensing, data extraction, processing, and sharing over the internet. Moreover, IoT devices are in operation with a lack of standards that poses a severe security threat. Intrusion detection systems and cryptographic algorithms are two important components in the security posture of a cyberspace. IoT applications provide real-time services, so security measures are active 24/7/365. Hence, these algorithms are also related to energy consumption. It is a study of security algorithms based on their hardware and software implementations. This review systematically searches for and selects the latest research documents, conducting an analysis of sustainability and security. It depicts the lightweight features of cryptographic algorithms; the relationship of gate density, chip area and power consumption in CMOS technology; and the importance of Machine Learning (MA) applications for IDS and cryptographic solutions in Next Generation IoT (NGIoT). © The Author(s) 2025.
Author Keywords Cryptography; Intrusion detection system; Machine learning; NGIoT; Security; Sustainability


Similar Articles


Id Similarity Authors Title Published
35244 View0.89Khalique A.; Siddiqui F.; Ahad M.A.; Hussain I.Lightweight Authentication For Iot Devices (Laid) In Sustainable Smart CitiesScientific Reports, 15, 1 (2025)
47934 View0.884Padmavathi V.; Saminathan R.Security For The Internet Of ThingsComputer and Information Security Handbook, Fourth Edition: Volumes 1-2, 1 (2024)
36064 View0.883Alfahaid A.; Alalwany E.; Almars A.M.; Alharbi F.; Atlam E.; Mahgoub I.Machine Learning-Based Security Solutions For Iot Networks: A Comprehensive SurveySensors, 25, 11 (2025)
1173 View0.881Mustafa R.; Sarkar N.I.; Mohaghegh M.; Pervez S.A Cross-Layer Secure And Energy-Efficient Framework For The Internet Of Things: A Comprehensive SurveySensors, 24, 22 (2024)
36080 View0.88Ahanger T.A.; Ullah I.; Algamdi S.A.; Tariq U.Machine Learning-Inspired Intrusion Detection System For Iot: Security Issues And Future ChallengesComputers and Electrical Engineering, 123 (2025)
35256 View0.88Rana M.; Mamun Q.; Islam R.Lightweight Cryptography In Iot Networks: A SurveyFuture Generation Computer Systems, 129 (2022)
32899 View0.879Sarker I.H.; Khan A.I.; Abushark Y.B.; Alsolami F.Internet Of Things (Iot) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions And Research DirectionsMobile Networks and Applications, 28, 1 (2023)
1448 View0.879Muniswamy A.; Rathi R.A Detailed Review On Enhancing The Security In Internet Of Things-Based Smart City Environment Using Machine Learning AlgorithmsIEEE Access, 12 (2024)
58001 View0.878Rangelov D.; Lämmel P.; Brunzel L.; Borgert S.; Darius P.; Tcholtchev N.; Boerger M.Towards An Integrated Methodology And Toolchain For Machine Learning-Based Intrusion Detection In Urban Iot Networks And PlatformsFuture Internet, 15, 3 (2023)
46467 View0.878Chiba Z.; Abghour N.; Moussaid K.; Lifandali O.; Kinta R.Review Of Recent Intrusion Detection Systems And Intrusion Prevention Systems In Iot Networks2022 30th International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2022 (2022)