Security importance of edge-IoT ecosystem: An ECC-based authentication scheme
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| Publicado en: | PLoS One vol. 20, no. 6 (Jun 2025), p. e0322131 |
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Public Library of Science
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 022 | |a 1932-6203 | ||
| 024 | 7 | |a 10.1371/journal.pone.0322131 |2 doi | |
| 035 | |a 3215950174 | ||
| 045 | 2 | |b d20250601 |b d20250630 | |
| 084 | |a 174835 |2 nlm | ||
| 100 | 1 | |a Alzahrani, Naif | |
| 245 | 1 | |a Security importance of edge-IoT ecosystem: An ECC-based authentication scheme | |
| 260 | |b Public Library of Science |c Jun 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Despite the many outstanding benefits of cloud computing, such as flexibility, accessibility, efficiency, and cost savings, it still suffers from potential data loss, security concerns, limited control, and availability issues. The experts introduced the edge computing paradigm to perform better than cloud computing for the mentioned issues and challenges because it is directly connected to the Internet-of-Things (IoT), sensors, and wearables in a decentralized manner to distribute processing power closer to the data source, rather than relying on a central cloud server to handle all computations; this allows for faster data processing and reduced latency by processing data locally at the ‘edge’ of the network where it’s generated. However, due to the resource-constrained nature of IoT, sensors, or wearable devices, the edge computing paradigm endured numerous data breaches due to sensitive data proximity, physical tampering vulnerabilities, and privacy concerns related to user-near data collection, and challenges in managing security across a large number of edge devices. Existing authentication schemes didn’t fulfill the security needs of the edge computing paradigm; they either have design flaws, are susceptible to various known threats—such as impersonation, insider attacks, denial of service (DoS), and replay attacks—or experience inadequate performance due to reliance on resource-intensive cryptographic algorithms, like modular exponentiations. Given the pressing need for robust security mechanisms in such a dynamic and vulnerable edge-IoT ecosystem, this article proposes an ECC-based robust authentication scheme for such a resource-constrained IoT to address all known vulnerabilities and counter each identified threat. The proof of correctness of the proposed protocol has been scrutinized through a well-known and widely used Real-Or-Random (RoR) model, ProVerif validation, and attacks’ discussion, demonstrating the thoroughness of the proposed protocol. The performance metrics have been measured by considering computational time complexity, communication cost, and storage overheads, further reinforcing the confidence in the proposed solution. The comparative analysis results demonstrated that the proposed ECC-based authentication protocol is 90.05% better in terms of computation cost, 62.41% communication cost, and consumes 67.42% less energy compared to state-of-the-art schemes. Therefore, the proposed protocol can be recommended for practical implementation in the real-world edge-IoT ecosystem. | |
| 653 | |a Comparative analysis | ||
| 653 | |a Data processing | ||
| 653 | |a Internet of Things | ||
| 653 | |a Sensors | ||
| 653 | |a Protocol | ||
| 653 | |a Data collection | ||
| 653 | |a Communication | ||
| 653 | |a Bandwidths | ||
| 653 | |a Edge computing | ||
| 653 | |a Wearable technology | ||
| 653 | |a Automation | ||
| 653 | |a Privacy | ||
| 653 | |a Performance evaluation | ||
| 653 | |a Energy consumption | ||
| 653 | |a Performance measurement | ||
| 653 | |a Data loss | ||
| 653 | |a Cloud computing | ||
| 653 | |a Ecosystems | ||
| 653 | |a Network latency | ||
| 653 | |a Algorithms | ||
| 653 | |a Smart houses | ||
| 653 | |a Denial of service attacks | ||
| 653 | |a Robustness (mathematics) | ||
| 653 | |a Latency | ||
| 653 | |a Constraints | ||
| 653 | |a Authentication | ||
| 653 | |a Design defects | ||
| 653 | |a Cybersecurity | ||
| 653 | |a Computing time | ||
| 653 | |a Economic | ||
| 773 | 0 | |t PLoS One |g vol. 20, no. 6 (Jun 2025), p. e0322131 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3215950174/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3215950174/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3215950174/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |