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
To seek for lower-dimensional chaotic systems that have complex topological attractor structure with simple algebraic system structure, a new chaotic system of three-dimensional autonomous ordinary differential equati...To seek for lower-dimensional chaotic systems that have complex topological attractor structure with simple algebraic system structure, a new chaotic system of three-dimensional autonomous ordinary differential equations is presented. The new system has simple algebraic structure, and can display a 2-scroll attractor with complex topological structure, which is different from the Lorenz＇s, Chen＇s and Lu¨＇s attractors. By introducing a linear state feedback controller, the system can be controlled to generate a hyperchaotic attractor. The novel chaotic attractor, hyperchaotic attractor and dynamical behaviors of corresponding systems are further investigated by employing Lyapunov exponent spectrum, bifurcation diagram, Poincar′e mapping and phase portrait, etc., and then verified by simulating an experimental circuit.展开更多
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。
基金supported by the National Natural Science Foundation of China (60971090)the Natural Science Foundation of Jiangsu Province (BK 2009105)
文摘To seek for lower-dimensional chaotic systems that have complex topological attractor structure with simple algebraic system structure, a new chaotic system of three-dimensional autonomous ordinary differential equations is presented. The new system has simple algebraic structure, and can display a 2-scroll attractor with complex topological structure, which is different from the Lorenz＇s, Chen＇s and Lu¨＇s attractors. By introducing a linear state feedback controller, the system can be controlled to generate a hyperchaotic attractor. The novel chaotic attractor, hyperchaotic attractor and dynamical behaviors of corresponding systems are further investigated by employing Lyapunov exponent spectrum, bifurcation diagram, Poincar′e mapping and phase portrait, etc., and then verified by simulating an experimental circuit.
