Saad Khan, Pedro Afonso Ferreira Lopes Martins, Bruno Sousa, Vasco Pereira
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A Comprehensive Review on Lightweight Cryptographic Mechanisms for Industrial Internet of Things Systems
The integration of Industrial Internet of Things (IIoT) devices within Industrial Control Systems (ICS) presents significant cybersecurity challenges, primarily due to the limited resources of these devices. Traditional cryptographic algorithms are often unsuitable for IIoT environments due to their high computational, memory, and energy requirements. Lightweight Cryptographic Algorithms have emerged as efficient and secure alternatives, specifically designed for resource-constrained environments. This paper systematically reviews lightweight symmetric cryptographic mechanisms, specifically Block and Stream ciphers, and evaluates their critical attributes from an IIoT perspective. In addition, the security strengths and vulnerabilities of these algorithms against known cryptanalytic attacks, including Differential, Linear, Related Key, and others, are discussed. The paper also discusses current standardization efforts by organizations such as the National Institute of Standards and Technology (NIST), International Organization for Standardisation (ISO)/International Electro-technical Commission (IEC), highlighting their applicability in ICS environments. Finally, it identifies open research issues and future directions for improving lightweight cryptographic security in ICS, providing valuable insights for security practitioners and researchers seeking to robustly secure IIoT deployments.
期刊介绍:
ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods.
ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.