A Systematic Literature Review on Modern Cryptographic and Authentication Schemes for Securing the Internet of Things

The rapid integration of the Internet of Things (IoT) into healthcare ecosystems has revolutionized patient monitoring and data accessibility; however, it has simultaneously expanded the cyber-attack surface, leaving sensitive medical data vulnerable to sophisticated breaches. This systematic literature review (SLR) addresses the critical challenge of balancing high-level security with the severe resource constraints of medical sensors and edge devices. By synthesizing evidence from 80 high-impact studies including 18 primary research articles published between 2022 and 2025 this paper evaluates the quality and efficacy of emerging cryptographic frameworks. The methodology utilizes a rigorous quality assessment framework to categorize research into "Strong," "Moderate," and "Weak" tiers. Key findings reveal a significant paradigm shift toward lightweight symmetric ciphers, such as GIFT and PRESENT, and certificateless authentication protocols like ELWSCAS, which reduce communication overhead in narrow-band environments. The analysis further explores the role of blockchain-assisted decentralization and DNA-based encryption in mitigating Single Point of Failure risks and providing high entropy. While decentralized models significantly enhance data integrity, they frequently encounter a scalability wall regarding transaction latency. Furthermore, the review assesses quantum readiness, noting that while lattice-based standards are being ported to microcontrollers, memory footprints remain a barrier for simpler sensors. Ultimately, this SLR maps the current technical frontiers and provides a strategic roadmap for future research, emphasizing the transition toward lightweight, quantum-resistant architectures as the next essential step in securing the global healthcare IoT infrastructure. Conflict of InterestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. FundingThe research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Data Fabrication/Falsification StatementThe author(s) declare that no data has been fabricated, falsified, or manipulated in this study. Participant ConsentThe authors confirm that Informed consent was obtained from all participants, and confidentiality was duly maintained. Copyright and LicensingFor all articles published in the NIJEC journal, Copyright (c) of this study is with author(s).