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LWLCM: A novel lightweight stream cipher using logistic chaos function and multiplexer for IoT communications.

作者信息

Afzal Shahnwaz, Bokhari Mohammad Ubaidullah, Alam Mahfooz, Husain Mohd Shahid, Khan Mohammad Zunnun, Ashraf Zubair

机构信息

Department of Computer Science, Aligarh Muslim University, Aligarh, India.

Department of MCA, G.L. Bajaj Institute of Technology and Management, Greater Noida, India.

出版信息

PLoS One. 2025 Sep 4;20(9):e0330976. doi: 10.1371/journal.pone.0330976. eCollection 2025.

Abstract

The Internet of Things (IoT) includes vehicles, homes, and integrated sensors and many interconnected physical devices that gather and share data to interact with their environment. Data moving across multiple levels is vulnerable to various security threats, including leaks and unauthorized access. IoT faces significant challenges in balancing strict security with optimal performance metrics such as energy efficiency, throughput, and memory. We present a novel lightweight stream cipher designed to secure IoT communication and address these challenges. The proposed architecture features four main components: a logistic round module that produces 32-bit chaotic outputs; two 80-bit shift registers, LFSR and NLFSR, for key expansion; and multiplexer units to enhance confusion and diffusion. This model improves the randomness and robustness of the keystream, strengthening the cipher against cryptanalytic attacks. An ablation research is performed by methodically eliminating the chaotic map, NLFSR, and multiplexer components to assess their individual effects on encryption/decryption duration, throughput, entropy, and avalanche analysis. Experimental results demonstrate that each component significantly improves the cipher's overall performance and security, hence confirming the architecture's design and also demonstrate that the proposed cipher exceeds the performance of current algorithms, including Grain-128 and RSA-1024, in terms of encryption/decryption time, throughput, and energy efficiency, while maintaining comparable statistical randomness to AES and Trivium. This method achieves an average Shannon entropy of 7.9996, and successfully passing all 15 NIST statistical randomness tests. A subsequent study analyzing the avalanche effect and correlation coefficients reinforces the strength of the encryption. The proposed encryption method, designed for resource-constrained environments, provides efficient and robust cryptographic security to protect IoT data effectively.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32e0/12410779/f22b6ad3c50f/pone.0330976.g001.jpg

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