The Internet of Vehicles(IoV)operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms.Existing methods often suffer from com...The Internet of Vehicles(IoV)operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms.Existing methods often suffer from complex certificate management,inefficient consensus protocols,and poor resilience in high-frequency communication,resulting in high latency,poor scalability,and unstable network performance.To address these issues,this paper proposes a secure and efficient distributed authentication scheme for IoV with reputation-driven consensus and SM9.First,this paper proposes a decentralized authentication architecture that utilizes the certificate-free feature of SM9,enabling lightweight authentication and key negotiation,thereby reducing the complexity of key management.To ensure the traceability and global consistency of authentication data,this scheme also integrates blockchain technology,applying its inherent invariance.Then,this paper introduces a reputation-driven dynamic node grouping mechanism that transparently evaluates and groups’node behavior using smart contracts to enhance network stability.Furthermore,a new RBSFT(Reputation-Based SM9 Friendly-Tolerant)consensus mechanism is proposed for the first time to enhance consensus efficiency by optimizing the PBFT algorithm.RBSFT aims to write authentication information into the blockchain ledger to achieve multi-level optimization of trust management and decision-making efficiency,thereby significantly improving the responsiveness and robustness in high-frequency IoV scenarios.Experimental results show that it excels in authentication,communication efficiency,and computational cost control,making it a feasible solution for achieving IoV security and real-time performance.展开更多
针对正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)通信系统中存在的信息安全传输问题,提出了一种双重混沌加密安全传输方案。第一重加密为利用混沌加密矩阵对信号星座图进行置乱,其中混沌加密矩阵由复合离散混沌序...针对正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)通信系统中存在的信息安全传输问题,提出了一种双重混沌加密安全传输方案。第一重加密为利用混沌加密矩阵对信号星座图进行置乱,其中混沌加密矩阵由复合离散混沌序列作用到三层神经网络得到;第二重加密为利用复合离散混沌序列控制相位旋转因子对经过离散傅里叶逆变换后的信号进行相位旋转。仿真结果表明,采用所提出的双重加密方案进行传输,合作接收方的误码率低于不采用加密的OFDM系统和只采用第一重加密方案的OFDM系统,非合作方的误码率始终保持在0.5左右,密钥空间为2^(311),使系统具有较好的安全性能。展开更多
近年来,医疗数据泄露频发,严重威胁患者隐私与健康安全,亟需有效的解决方案以保护医疗数据在传输过程中的隐私与安全性。该文提出了一种基于双忆阻类脑混沌神经网络的医疗物联网(Internet of Medical Things,IoMT)数据隐私保护方法,以...近年来,医疗数据泄露频发,严重威胁患者隐私与健康安全,亟需有效的解决方案以保护医疗数据在传输过程中的隐私与安全性。该文提出了一种基于双忆阻类脑混沌神经网络的医疗物联网(Internet of Medical Things,IoMT)数据隐私保护方法,以应对这一挑战。首先,利用忆阻器的突触仿生特性,构建了一种基于Hopfield神经网络的双忆阻类脑混沌神经网络模型,并通过分岔图、Lyapunov指数谱、相图、时域图及吸引盆等非线性动力学工具,深入揭示了模型的复杂混沌动力学特性。研究结果表明,该网络不仅展现出复杂的网格多结构混沌吸引子特性,还具有平面初值位移调控能力,从而显著增强了其密码学应用潜力。为了验证其实用性与可靠性,基于微控制器单元(MCU)搭建了硬件平台,并通过硬件实验进一步确认了模型的复杂动力学行为。基于此模型,该文设计了一种结合双忆阻类脑混沌神经网络复杂混沌特性的高效IoMT数据隐私保护方法。在此基础上,对彩色医疗图像数据的加密效果进行了全面的安全性分析。实验结果表明,该方法在关键性能指标上表现优异,包括大密钥空间、低像素相关性、高密钥敏感性,以及对噪声与数据丢失攻击的强鲁棒性。该研究为IoMT环境下的医疗数据隐私保护提供了一种创新且有效的解决方案,为未来的智能医疗安全技术发展奠定了坚实基础。展开更多
基金supported by the National Natural Science Foundation of China(Grant No.61762071,Grant No.61163025).
文摘The Internet of Vehicles(IoV)operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms.Existing methods often suffer from complex certificate management,inefficient consensus protocols,and poor resilience in high-frequency communication,resulting in high latency,poor scalability,and unstable network performance.To address these issues,this paper proposes a secure and efficient distributed authentication scheme for IoV with reputation-driven consensus and SM9.First,this paper proposes a decentralized authentication architecture that utilizes the certificate-free feature of SM9,enabling lightweight authentication and key negotiation,thereby reducing the complexity of key management.To ensure the traceability and global consistency of authentication data,this scheme also integrates blockchain technology,applying its inherent invariance.Then,this paper introduces a reputation-driven dynamic node grouping mechanism that transparently evaluates and groups’node behavior using smart contracts to enhance network stability.Furthermore,a new RBSFT(Reputation-Based SM9 Friendly-Tolerant)consensus mechanism is proposed for the first time to enhance consensus efficiency by optimizing the PBFT algorithm.RBSFT aims to write authentication information into the blockchain ledger to achieve multi-level optimization of trust management and decision-making efficiency,thereby significantly improving the responsiveness and robustness in high-frequency IoV scenarios.Experimental results show that it excels in authentication,communication efficiency,and computational cost control,making it a feasible solution for achieving IoV security and real-time performance.
文摘针对正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)通信系统中存在的信息安全传输问题,提出了一种双重混沌加密安全传输方案。第一重加密为利用混沌加密矩阵对信号星座图进行置乱,其中混沌加密矩阵由复合离散混沌序列作用到三层神经网络得到;第二重加密为利用复合离散混沌序列控制相位旋转因子对经过离散傅里叶逆变换后的信号进行相位旋转。仿真结果表明,采用所提出的双重加密方案进行传输,合作接收方的误码率低于不采用加密的OFDM系统和只采用第一重加密方案的OFDM系统,非合作方的误码率始终保持在0.5左右,密钥空间为2^(311),使系统具有较好的安全性能。
文摘近年来,医疗数据泄露频发,严重威胁患者隐私与健康安全,亟需有效的解决方案以保护医疗数据在传输过程中的隐私与安全性。该文提出了一种基于双忆阻类脑混沌神经网络的医疗物联网(Internet of Medical Things,IoMT)数据隐私保护方法,以应对这一挑战。首先,利用忆阻器的突触仿生特性,构建了一种基于Hopfield神经网络的双忆阻类脑混沌神经网络模型,并通过分岔图、Lyapunov指数谱、相图、时域图及吸引盆等非线性动力学工具,深入揭示了模型的复杂混沌动力学特性。研究结果表明,该网络不仅展现出复杂的网格多结构混沌吸引子特性,还具有平面初值位移调控能力,从而显著增强了其密码学应用潜力。为了验证其实用性与可靠性,基于微控制器单元(MCU)搭建了硬件平台,并通过硬件实验进一步确认了模型的复杂动力学行为。基于此模型,该文设计了一种结合双忆阻类脑混沌神经网络复杂混沌特性的高效IoMT数据隐私保护方法。在此基础上,对彩色医疗图像数据的加密效果进行了全面的安全性分析。实验结果表明,该方法在关键性能指标上表现优异,包括大密钥空间、低像素相关性、高密钥敏感性,以及对噪声与数据丢失攻击的强鲁棒性。该研究为IoMT环境下的医疗数据隐私保护提供了一种创新且有效的解决方案,为未来的智能医疗安全技术发展奠定了坚实基础。
