Post-Quantum Secure Authentication for Constrained Iot Devices Using NTRU Lattice Cryptographic Techniques

The purpose of this study is to evaluate the suitability of the lattice-based NTRU post-quantum cryptography algorithm for securing Internet of Things (IoT) environments, which face increasing risks from quantum-enabled attacks and require long-term, efficient cryptographic protection resource-constrained IoT devices. The study analyzes the performance, computational demands, and scalability of NTRU within resource-constrained IoT devices. It examines NTRU in comparison with traditional public-key systems such as RSA-2048, considering factors such as key encapsulation mechanism (KEM) efficiency, where KEM refers to secure key exchange through encapsulation and decapsulation, memory usage, and processing overhead. Findings show that NTRU achieves more than 90% faster computation compared to RSA-2048, demonstrating significant improvements in speed and resource efficiency. These characteristics make NTRU a capable option for embedded and low-power IoT devices, where computational and energy constraints are critical. NTRU presents a promising solution for implementing post-quantum authentication in IoT systems. While some optimization challenges remain, its strong performance and suitability for resource-constrained environments position it as a viable candidate for future secure IoT deployments in the post-quantum era.

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Publication Details

Journal
Communications in Statistics Case Studies Data Analysis and Applications
Published
2026-09-27
DOI
https://doi.org/10.1080/23737484.2026.2730609
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
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Post-Quantum Secure Authentication for Constrained Iot Devices Using NTRU Lattice Cryptographic Techniques

N. Anil Kumar, B. Krishnakanth, V. Suryanarayana Reddy, M. Asia Rafiq et al.
Communications in Statistics Case Studies Data Analysis and Applications
Cryptography and Data Security
article

Post-Quantum Secure Authentication for Constrained Iot Devices Using NTRU Lattice Cryptographic Techniques

N. Anil Kumar, B. Krishnakanth, V. Suryanarayana Reddy, M. Asia Rafiq, P. Rajyalakshmi, Annam Venkata Padmavathi
article en

Abstract

The purpose of this study is to evaluate the suitability of the lattice-based NTRU post-quantum cryptography algorithm for securing Internet of Things (IoT) environments, which face increasing risks from quantum-enabled attacks and require long-term, efficient cryptographic protection resource-constrained IoT devices. The study analyzes the performance, computational demands, and scalability of NTRU within resource-constrained IoT devices. It examines NTRU in comparison with traditional public-key systems such as RSA-2048, considering factors such as key encapsulation mechanism (KEM) efficiency, where KEM refers to secure key exchange through encapsulation and decapsulation, memory usage, and processing overhead. Findings show that NTRU achieves more than 90% faster computation compared to RSA-2048, demonstrating significant improvements in speed and resource efficiency. These characteristics make NTRU a capable option for embedded and low-power IoT devices, where computational and energy constraints are critical. NTRU presents a promising solution for implementing post-quantum authentication in IoT systems. While some optimization challenges remain, its strong performance and suitability for resource-constrained environments position it as a viable candidate for future secure IoT deployments in the post-quantum era.

Communications in Statistics Case Studies Data Analysis and Applications
Vignan's Foundation for Science, Technology & Research (IN), The University of Agriculture, Peshawar (PK), Mohan Babu University (IN), Koneru Lakshmaiah Education Foundation (IN)
Decent work and economic growth
Openalex Percentile: Top 9%
Cryptography and Data Security
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Post-Quantum Secure Authentication for Constrained Iot Devices Using NTRU Lattice Cryptographic Techniques — N. Anil Kumar, B. Krishnakanth, et al. · Communications in Statistics Case Studies Data Analysis and Applications (2026) | TGRS Research Map | TGRS