Secure authentication framework for IoT applications using a hash-based post-quantum signature scheme

In today’s era, numerous applications are evolving into smart applications by leveraging technologies like the Internet of Things (IoT), Artificial Intelligence (AI), and Big Data. The incorporation of advanced sensors, AI-driven embedded devices, and cloud-based remote control has significantly enh...

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Vydáno v:Service oriented computing and applications Ročník 19; číslo 3; s. 251 - 262
Hlavní autoři: Tandel, Purvi, Nasriwala, Jitendra
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Springer London 01.09.2025
Springer Nature B.V
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ISSN:1863-2386, 1863-2394
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Shrnutí:In today’s era, numerous applications are evolving into smart applications by leveraging technologies like the Internet of Things (IoT), Artificial Intelligence (AI), and Big Data. The incorporation of advanced sensors, AI-driven embedded devices, and cloud-based remote control has significantly enhanced the efficiency and profitability of IoT applications in numerous eras. Ensuring the security of IoT applications is crucial, with authentication emerging as a top priority. Lack of proper authentication may lead to unauthorized and risky activities, potentially causing hazardous situations within IoT applications. The current cryptographic methods employed in IoT devices rely on public-key cryptographic primitives, which, unfortunately, are susceptible to future quantum attacks. Therefore, there is a need to develop an effective signature scheme that can authenticate IoT devices resiliently against potential quantum threats. Hash-based post-quantum signature scheme stood as the best candidate to design quantum-safe authentication mechanisms. This paper presents a practical client–server implementation scenario tailored for IoT applications, showcasing the utilization of hash-based post-quantum digital signatures. Highlighting the complexity and computational demands of these signatures, the model architecture is illustrated using Raspberry Pi 3 and Pi 0 as servers, complemented by the widely used ESP32 as client devices in IoT applications achieving 32.83% optimized memory usage.
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ISSN:1863-2386
1863-2394
DOI:10.1007/s11761-024-00414-x