Avalanche Effect (%) of Key- Keystream.

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.物联网（Internet of Things, IoT）涵盖车辆、家居、集成传感器与大量互联物理设备，这些设备可采集并共享数据以与周遭环境进行交互。跨多层级传输的数据易遭受各类安全威胁，包括数据泄露与未授权访问。物联网在兼顾严苛安全要求与能效、吞吐量、内存占用等最优性能指标方面面临重大挑战。我们提出了一种专为物联网通信安全设计的新型轻量级流密码，以应对上述挑战。所提出的架构包含四大核心组件：一是可生成32位混沌输出的逻辑斯蒂循环模块；二是用于密钥扩展的两个80位移位寄存器——线性反馈移位寄存器（Linear Feedback Shift Register, LFSR）与非线性反馈移位寄存器（Non-Linear Feedback Shift Register, NLFSR）；以及用于增强混淆与扩散特性的多路复用器单元。该模型提升了密钥流的随机性与鲁棒性，增强了该密码算法对抗密码分析攻击的能力。我们通过系统性移除混沌映射、NLFSR与多路复用器组件开展消融实验，以评估各组件对加解密时长、吞吐量、熵值以及雪崩效应分析的独立影响。实验结果表明，各组件均能显著提升该密码算法的整体性能与安全性，从而验证了本架构的设计合理性；同时实验还证实，所提密码在加解密时长、吞吐量与能效方面均优于现有算法，包括Grain-128与RSA-1024，且其统计随机性与高级加密标准（Advanced Encryption Standard, AES）及Trivium相当。该方法的平均香农熵可达7.9996，且顺利通过了美国国家标准与技术研究院（National Institute of Standards and Technology, NIST）的全部15项统计随机性测试。后续针对雪崩效应与相关系数的分析进一步验证了该加密算法的强度。本加密方案专为资源受限环境设计，可提供高效且鲁棒的密码学安全防护，有效保障物联网数据安全。