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  • 标题:Healthcare Data Breaches: Insights and Implications
  • 本地全文:下载
  • 作者:Adil Hussain Seh ; Mohammad Zarour ; Mamdouh Alenezi
  • 期刊名称:Healthcare
  • 电子版ISSN:2227-9032
  • 出版年度:2020
  • 卷号:8
  • 期号:2
  • 页码:133-150
  • DOI:10.3390/healthcare8020133
  • 出版社:MDPI Publishing
  • 摘要:The Internet of Medical Things, Smart Devices, Information Systems, and Cloud Services have led to a digital transformation of the healthcare industry. Digital healthcare services have paved the way for easier and more accessible treatment, thus making our lives far more comfortable. However, the present day healthcare industry has also become the main victim of external as well as internal attacks. Data breaches are not just a concern and complication for security experts; they also affect clients, stakeholders, organizations, and businesses. Though the data breaches are of different types, their impact is almost always the same. This study provides insights into the various categories of data breaches faced by different organizations. The main objective is to do an in-depth analysis of healthcare data breaches and draw inferences from them, thereby using the findings to improve healthcare data confidentiality. The study found that hacking/IT incidents are the most prevalent forms of attack behind healthcare data breaches, followed by unauthorized internal disclosures. The frequency of healthcare data breaches, magnitude of exposed records, and financial losses due to breached records are increasing rapidly. Data from the healthcare industry is regarded as being highly valuable. This has become a major lure for the misappropriation and pilferage of healthcare data. Addressing this anomaly, the present study employs the simple moving average method and the simple exponential soothing method of time series analysis to examine the trend of healthcare data breaches and their cost. Of the two methods, the simple moving average method provided more reliable forecasting results.
  • 关键词:healthcare data breaches; data confidentiality; data security; cost effectiveness; data analysis; time series analysis; data breach forecasting; cost forecasting healthcare data breaches ; data confidentiality ; data security ; cost effectiveness ; data analysis ; time series analysis ; data breach forecasting ; cost forecasting
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