The security and privacy of healthcare enterprises (HEs) are crucial because they maintain sensitive information. Because of the unique functional requirement of omni-inclusiveness, HEs are expected to monitor patients, allowing for connectivity with vehicular ad hoc networks (VANETs). In the absence of literature on security provisioning frameworks that connect VANETs and HEs, this paper presents a smart zero-knowledge proof and statistical fingerprinting-based trusted secure communication framework for a fog computing environment. A zero-knowledge proof is used for vehicle authentication, and statistical fingerprinting is employed to secure communication between VANETs and HEs. Authenticity verification of the operations is performed at the on-board unit (OBU) fitted in the vehicle based on the service executions at the resident hardware platform. The processor clock cycles are acquired from the service executions in a complete sandboxed environment. The calculated cycles assist in developing the blueprint signature for the particular OBU of the vehicle. Hence, the fingerprint signature helps build trust and plays a key role in authenticating the vehicle’s horizontal movement to everything or to different sections of the HEs. In an environment enabled for fog computing, our novel model can provide efficient remote monitoring.

中文翻译：

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通过零知识证明和统计指纹在车辆到医疗保健一切 (V2HX) 通信中实现数据安全

医疗保健企业 (HE) 的安全和隐私至关重要，因为它们维护敏感信息。由于全方位包容性的独特功能要求，HE 有望监控患者，从而实现与车载自组织网络 (VANET) 的连接。在缺乏连接 VANET 和 HE 的安全供应框架的文献的情况下，本文提出了一种用于雾计算环境的智能零知识证明和基于统计指纹的可信安全通信框架。车辆身份验证使用零知识证明，并使用统计指纹来保护 VANET 和 HE 之间的通信。基于驻留硬件平台上的服务执行，在安装在车辆中的车载单元 (OBU) 上执行操作的真实性验证。处理器时钟周期是从完整沙盒环境中的服务执行中获取的。计算出的周期有助于为车辆的特定 OBU 开发蓝图签名。因此，指纹签名有助于建立信任，并在验证车辆水平移动到所有东西或 HE 的不同部分方面发挥关键作用。在支持雾计算的环境中，我们的新颖模型可以提供高效的远程监控。计算出的周期有助于为车辆的特定 OBU 开发蓝图签名。因此，指纹签名有助于建立信任，并在验证车辆水平移动到所有东西或 HE 的不同部分方面发挥关键作用。在支持雾计算的环境中，我们的新颖模型可以提供高效的远程监控。计算出的周期有助于为车辆的特定 OBU 开发蓝图签名。因此，指纹签名有助于建立信任，并在验证车辆水平移动到所有东西或 HE 的不同部分方面发挥关键作用。在支持雾计算的环境中，我们的新颖模型可以提供高效的远程监控。