Discrete chaos theory for secure key generation in lightweight IoT encryption

In today’s interconnected world, ensuring the security of lightweight Internet of Things (IoT) devices has become a significant challenge due to their limited computational capabilities and growing vulnerability to sophisticated cryptographic attacks. While chaos theory has been extensively explored for enhancing cryptographic systems, most implementations rely on continuous chaos models, which are often computationally intensive and unsuitable for resource-constrained devices. This paper presents an innovative approach to key generation using discrete chaos theory, particularly discrete logistic maps. Unlike traditional methods, discrete chaos offers a lightweight, mathematically efficient solution without compromising on key unpredictability and security. By leveraging the unique properties of discrete chaos such as sensitivity to initial conditions and strong non-linearity our method generates cryptographic keys that are highly secure and integrate seamlessly with existing encryption protocols. Through extensive experimentation, we validated the robustness and effectiveness of our approach. The results demonstrate superior randomness and enhanced resistance to cryptographic attacks, all while maintaining minimal computational overhead, making it ideal for IoT applications. This research opens new doors for scalable and secure cryptographic systems tailored for the unique needs of IoT devices, addressing a critical gap in the current landscape of lightweight encryption technologies.

Authors

Publication Details

Journal
Journal of Discrete Mathematical Sciences and Cryptography
Published
2025-01-01
DOI
https://doi.org/10.47974/jdmsc-2372
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Discrete chaos theory for secure key generation in lightweight IoT encryption

Budesh Kanwer, Gajendra Shrimal, Susheela Vishnoi, Sanwta Ram Dogiwal et al.
Journal of Discrete Mathematical Sciences and Cryptography
Chaos-based Image/Signal Encryption
article

Discrete chaos theory for secure key generation in lightweight IoT encryption

Budesh Kanwer, Gajendra Shrimal, Susheela Vishnoi, Sanwta Ram Dogiwal, Tripti Jain, Manali Pareek
article en

Abstract

In today’s interconnected world, ensuring the security of lightweight Internet of Things (IoT) devices has become a significant challenge due to their limited computational capabilities and growing vulnerability to sophisticated cryptographic attacks. While chaos theory has been extensively explored for enhancing cryptographic systems, most implementations rely on continuous chaos models, which are often computationally intensive and unsuitable for resource-constrained devices. This paper presents an innovative approach to key generation using discrete chaos theory, particularly discrete logistic maps. Unlike traditional methods, discrete chaos offers a lightweight, mathematically efficient solution without compromising on key unpredictability and security. By leveraging the unique properties of discrete chaos such as sensitivity to initial conditions and strong non-linearity our method generates cryptographic keys that are highly secure and integrate seamlessly with existing encryption protocols. Through extensive experimentation, we validated the robustness and effectiveness of our approach. The results demonstrate superior randomness and enhanced resistance to cryptographic attacks, all while maintaining minimal computational overhead, making it ideal for IoT applications. This research opens new doors for scalable and secure cryptographic systems tailored for the unique needs of IoT devices, addressing a critical gap in the current landscape of lightweight encryption technologies.

Journal of Discrete Mathematical Sciences and CryptographyVol. 28(5-B)
Openalex Percentile: Top 78%
Chaos-based Image/Signal Encryption
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.