Journal of Management Information and Decision Sciences (Print ISSN: 1524-7252; Online ISSN: 1532-5806)


Big Healthcare Data: Enhancing Security and Privacy

Author(s): Ali Hasan Kamil

Big data refers to the process of collecting, storing, processing, and turning data into something useful by using new tools and techniques. Big data allows businesses to monitor trends and recognize patterns, both of which can assist them in making better decisions for their companies. Large amounts of data are called "big data," Its defining characteristics include colossal velocities, wide variety, extensive ranges, useable value, and veracity. The fields of retail, customer service, healthcare, electronic commerce, marketing, finance, transportation, and logistics are just a few of the significant arenas in which big data can be applied. Big data analytics can provide many organizations, particularly those in the healthcare industry, with valuable new perspectives. Big data has the best potential to enhance consumer experiences, get important insights, predict disease outbreaks, prevent preventable diseases, and save healthcare costs. Despite these challenges, the healthcare business needs to must big data due to a lack of need for staff, IT infrastructure, and data privacy laws. Because health data is always changing, processing and analyzing it can be fraught with various issues on a conceptual, technical, legal, and ethical level. As one of the most pressing issues today, big data in the healthcare industry has assumed an increasingly significant role in recent years. The challenges posed by big data in the healthcare industry are examined in this research. I also provide a comprehensive healthcare data lifecycle that includes protection against breaches and threats. As a consequence of this, i will be able to come up with rules and systems that take into account every security concern. This study also proposes novel methods for authenticating users, encrypting data, maintaining anonymity, controlling access, and maintaining privacy. The most important contribution is a security threat model for the lifecycle of large amounts of healthcare data.

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