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Security preservation in industrial medical CPS using Chebyshev map: An AI approach

机译:使用Chebyshev地图的工业医疗CPS安全保存:AI方法

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摘要

Cyber-Physical System (CPS) are widely used in various areas such as industrial manufacturing, telemedicine and energy, etc. Specifically, industrial medical CPS utilizes various medical devices connected to the network to realize real-time management and treatment of patient. However, the underlying wireless channel makes industrial medical CPS vulnerable to external attacks, which may leak patient privacy and even threaten patients' lives. Besides, most of the authentication schemes are not suitable for real-time applications such as medical CPS due to the latency. Hence, the artificial intelligence (AI) techniques can be useful in this environment to cater to the aforementioned challenges. It necessitates constructing a secure and lightweight authentication protocol to prevent the unauthorized access and control of medical devices. Traditional authentication schemes adopt a password-based or smartcard to validate the authenticity of users, which may suffer from password guessing or smartcard lost attack. However, the AI-assisted biometrics technique can effectively resist the aforementioned attacks. Therefore, an AI-assisted lightweight authentication protocol for real-time access using a Chebyshev map in industrial medical CPS is designed in this paper, which is robust and resolve security and privacy issues. The proposed protocol is capable of resisting various known attacks through security analysis. The proposed protocol has less computational overhead with a slight increase in communication overhead. Also, the proposed protocol supports stringent security features and functionalities compared to other existing protocols.
机译:网络物理系统(CPS)广泛用于工业制造,远程医疗和能量等各种领域。具体地,工业医疗CPS利用连接到网络的各种医疗器械来实现患者的实时管理和治疗。然而,底层无线信道使工业医疗CPS容易受到外部攻击的影响,这可能会泄漏患者隐私,甚至威胁患者的生命。此外,大多数认证方案不适用于由于延迟而诸如医疗CP的实时应用。因此,人工智能(AI)技术可以在这种环境中有用,以满足上述挑战。它需要构建安全和轻量级的认证协议,以防止未授权的医疗设备的访问和控制。传统的身份验证方案采用基于密码或智能卡以验证用户的真实性,可能会遭受密码猜测或智能卡丢失攻击。然而,AI辅助生物识别技术可以有效地抵抗上述攻击。因此,在本文中设计了使用工业医疗CP中的Chebyshev地图的实时访问AI辅助的轻量级认证协议,这是强大的,解决安全性和隐私问题。所提出的协议能够通过安全分析来抵抗各种已知的攻击。所提出的协议具有较少的计算开销,略有增加通信开销。此外,与其他现有协议相比,所提出的协议支持严格的安全功能和功能。

著录项

  • 来源
    《Future generation computer systems》 |2021年第9期|52-62|共11页
  • 作者单位

    School of Computer and Software Nanjing University of Information Science & Technology Nanjing 210044 China;

    School of Computer and Software Nanjing University of Information Science & Technology Nanjing 210044 China Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology China Jiangsu Engineering Center of Network Monitoring China;

    School of Computer and Software Nanjing University of Information Science & Technology Nanjing 210044 China Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology China;

    Department of Computer Science and Engineering University College of Engineering Tindivanam Tindivanam Tamil Nadu 604001 India;

    Department of Computer Science and Engineering Thapar University Patiala India Department of Computer Science and Information Engineering Asia University Taichung Taiwan School of Computer Science University of Petroleum and Energy Studies Dehradun Uttarakhand;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Chebyshev map; Medical CPS; Authentication; Security and privacy; Al-assisted;

    机译:Chebyshev地图;医疗CPS;验证;安全和隐私;Al辅助;

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