Vehicular Ad Hoc Networks (VANETs) provide various benefits and play a crucial role in improving efficiency and ensuring human safety across different applications. However, these advantages also give rise to security challenges and privacy concerns, necessitating a thorough examination of security attacks. Current key generation schemes, particularly those based on the Physical-Layer Model (PLM), face limitations such as low key generation rates and inadequate randomness. This paper introduces an innovative key generation method that utilizes adaptive physical-layer techniques and lossless quantization. The method involves an eight-level quantization process, which enables precise granularity and adaptive selection of quantization thresholds to tailor the computation of Received Signal Strength (RSS) measurements to individual needs. The adaptive approach ensures the retention of information within RSS measurements, resulting in reduced bit disagreement rates and enhanced randomness of the generated keys. Simulated evaluations demonstrate the effectiveness of the proposed method, showing superior performance in terms of bit generation, entropy, and secrecy rates, while also minimizing the occurrence of unnecessary measurements. This advancement holds significant promise for strengthening the security framework within VANETs.

中文翻译：

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基于接收信号强度的车载自组织网络中物理层密钥生成的无损量化方法


车载自组织网络 (VANET) 具有多种优势，在提高不同应用的效率和确保人员安全方面发挥着至关重要的作用。然而，这些优势也带来了安全挑战和隐私问题，需要对安全攻击进行彻底检查。当前的密钥生成方案，特别是基于物理层模型（PLM）的密钥生成方案，面临密钥生成率低和随机性不足等局限性。本文介绍了一种利用自适应物理层技术和无损量化的创新密钥生成方法。该方法涉及八级量化过程，可实现量化阈值的精确粒度和自适应选择，从而根据个人需求定制接收信号强度 (RSS) 测量的计算。自适应方法确保在 RSS 测​​量中保留信息，从而降低比特不一致率并增强生成密钥的随机性。模拟评估证明了所提出方法的有效性，在比特生成、熵和保密率方面显示出优越的性能，同时还最大限度地减少了不必要测量的发生。这一进步为加强 VANET 内的安全框架带来了重大希望。