Trustworthy Intrusion Detection in E-Healthcare Systems

Frontiers in Public Health

Sidra Abbas¹  Muhammad Rizwan²  Natalia Kryvinska³  Faiza Akram⁴  Peibiao Zhao⁴  Dongsheng Liu⁴ 

[1] Department of Computer Science, COMSATS University, Islamabad, Pakistan;Department of Computer Science, Kinnaird College for Women, Lahore, Pakistan;Department of Information Systems, Faculty of Management, Comenius University in Bratislava, Bratislava, Slovakia;Department of Mathematics, School of Science, Nanjing University of Science and Technology, Nanjing, China;

关键词: network security;    privacy;    ANFIS;    intrusion detection;    IoT based networks;   

DOI  :  10.3389/fpubh.2021.788347

来源: DOAJ

【 摘 要 】

In Internet of Things (IoT)-based network systems (IoT-net), intrusion detection systems (IDS) play a significant role to maintain patient health records (PHR) in e-healthcare. IoT-net is a massive technology with security threats on the network layer, as it is considered the most common source for communication and data storage platforms. The security of data servers in all sectors (mainly healthcare) has become one of the most crucial challenges for researchers. This paper proposes an approach for effective intrusion detection in the e-healthcare environment to maintain PHR in a safe IoT-net using an adaptive neuro-fuzzy inference system (ANFIS). In the proposed security model, the experiments present a security tool that helps to detect malicious network traffic. The practical implementation of the ANFIS model on the MATLAB framework with testing and training results compares the accuracy rate from the previous research in security.

【 授权许可】

Unknown