Cyber Forensics and Investigation on Smart Devices

Machine Learning Approach to Detect Ransomware Threats in Health Care Systems

Author(s): Varun Sapra*, Ankit Vishnoi and Luxmi Sapra

Pp: 118-132 (15)

DOI: 10.2174/9789815179576124010009

* (Excluding Mailing and Handling)

Abstract

With the advancement in healthcare technology, the industry is moving from conventional diagnosis methods to digital health platforms. These digital health platforms are useful for patients in different ways like from initial disease diagnosis to drug prescription and maintaining electronic health records. These health records contain a lot of personal information of patients that has high monetary and intelligence value, so such healthcare systems are more vulnerable and targeted by cyber thieves. Several techniques have been implemented by healthcare organizations for the early detection of such cyber threats and for securing the medical records of patients. One such method is machine learning (ML) for the detection of threats or adulterated data due to some payload ransomware. This chapter highlights different healthcare data breaches and the impact of cyber-attacks on medical data using artificial neural networks.

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