Abstract
Internet-of-Things (IoT) offers a novel intelligent ecosystem that consists of various physical objects interconnected via the internet, which draws the attention of researchers, academicians, and industrialists. Various physical objects are embedded systems that perform dedicated operations that include sensing, monitoring, and controls. Such connectivity of embedded system devices over the internet creates an intelligent mesh worldwide and makes city, industry, and human life entirely automated and intelligent. However, the existing embedded system with radio modules is battery operated, referred to as a low-resourced device. Further, it is expected that the device should consume less operational power. Tiny size devices are offering less memory which creates a resource-constrained environment. An efficient hardware implementation of security algorithms is challenging in a constrained environment that satisfies all performance metrics. Standard internet connectivity of all devices with new wireless paradigms (e.g. ZigBee, LoRa, Wi-Fi, SigFox, etc.) essentially needs to be scrutinized for secured data communication and other security flaws. The universal connection allows an adversary to access secured technology via vulnerable systems. Many researchers are analyzing IoT technologies in every possible aspect to provide an economically secured solution. Importing software-tested encryption standards on hardware with efficient results can produce reliable IoT nodes. In this paper, we present the overview of IoT infrastructure with supporting data communication protocols. Also, we discussed essential cryptographic design rationale to minimize overall structure with the importance of metrics. Environmental and implementation based challenges, trade-off, and importance of cryptography towards the development of secured IoT node with Light-Weight Cipher (LWC) ANU and PRESENT proof-of-concept for generic application is provided in this research.
Publisher
Perpetual Innovation Media Pvt. Ltd.
Cited by
1 articles.
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1. Analysis of Machine Learning (ML) and Internet of Things (IoT): A Scientometric Review;2024 20th IEEE International Colloquium on Signal Processing & Its Applications (CSPA);2024-03-01