ABSTRACT
Machine learning has provided potential solutions to many real-world problems. In healthcare, machine-learning algorithms analyze patient's health information and predict diseases. For this, healthcare industries require to maintain databases that hold patients’ critical information, such as patient information, contact information, billing information, and health records. Due to such valuable insights and health information, healthcare sector is vulnerable to cyber-attacks. Cyber criminals can cause financial loss to the healthcare by accessing sensitive information through ransomware or phishing links. With machine-learning algorithms, resistance to cyber-attacks can be provided by automating network defences, learning hacker behaviour, and improving antivirus software available in the organization. In this chapter, we have analyzed various research advances in the field of machine learning and their application for healthcare cybersecurity. We have reviewed the recent machine-learning algorithms in smart healthcare to analyze their accuracy and efficiency to predict cyber-attacks in the healthcare industry. In addition, we have summarized the application and challenges of 6G deployment in healthcare industry.
