Securing electronic health records against insider-threats: A supervised machine learning approach

Hurst, William; Teki̇nerdoğan, Bedir; AlSkaif, Tarek; Boddy, Aaron; Shone, Nathan

doi:10.1016/j.smhl.2022.100354

Cited by 7 publications

(3 citation statements)

References 45 publications

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“…• Detecting internal data breaches Sometimes data breaches can also arise from insiders who have prior authorised access to the MDS [26]. Detection of internal data breaches is an extremely challenging task as the insiders may know how to bypass detection without leaving any suspicious evidence [26]. Hence, there should be strict monitoring processes implemented which requires more effort and cost [22].…”

Section: • Complexity Diversity and Volume Of Healthcare Datamentioning

confidence: 99%

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Data Security Challenges in AI-Enabled Medical Device Software

Jayaneththi,

McCaffery,

Regan

2023

2023 31st Irish Conference on Artificial Intelligence and Cognitive Science (AICS)

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The potential of AI to develop innovative applications that can benefit healthcare professionals and patients has created interest, especially in Medical Device Software (MDS) domain. However, the adoption of AI in MDS domain has created several challenges which include: making AI transparent; gaps in clarifying accountability; risk associated with the adaptive nature of AI algorithms; mitigating bias in data; lack of regulatory guidelines specific for AI; and assuring data security. Assuring data security is crucial for AIenabled MDS, as compromising sensitive personal health data can create privacy and ethical concerns and sometimes lead to life threatening issues. In this paper, we discuss the importance of adopting AI in the healthcare domain, the importance of data security in AI-enabled MDS, and the data security challenges that AI has brought to the healthcare industry. Additionally, we consider the reasons for the existence of these challenges. The challenges discussed in this paper are in relation to (1) preventing data breaches; (2) preventing adversarial attacks; (3) preventing cyberattacks; (4) preventing insider threats; (5) lack of skilled and trained staff in data security; and (6) complexity of existing standards and lack of security control implementation details.

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Section: • Complexity Diversity and Volume Of Healthcare Datamentioning

confidence: 99%

“…An insider attack refers to any negative action that is performed by a malicious actor who has prior knowledge, access and authorisation to the system [26]. Insider threats can compromise data security, making it essential to implement strict access controls and monitor user activities [22].…”

Section: Preventing Insider Threatsmentioning

confidence: 99%

Data Security Challenges in AI-Enabled Medical Device Software

Jayaneththi,

McCaffery,

Regan

2023

2023 31st Irish Conference on Artificial Intelligence and Cognitive Science (AICS)

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“…Furthermore, the benefits of efficient data sharing extend to patients, who can access their information, including laboratory and imaging results, with the ability to port these data to other healthcare providers or organizations. Facilitating efficient and automated communication between patients and medical teams [4] enables universal access to data, promoting transparency and ultimately enhancing patient satisfaction.…”

Section: Introductionmentioning

confidence: 99%

Storage Standards and Solutions, Data Storage, Sharing, and Structuring in Digital Health: A Brazilian Case Study

Oliveira,

Santos,

Mendes

et al. 2023

Information

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The COVID-19 pandemic has highlighted the necessity for agile health services that enable reliable and secure information exchange, but achieving proper, private, and secure sharing of EMRs remains a challenge due to diverse data formats and fragmented records across multiple data silos, resulting in hindered coordination between healthcare teams, potential medical errors, and delays in patient care. While centralized EMR systems pose privacy risks and data format diversity complicates interoperability, blockchain technology offers a promising solution by providing decentralized storage, ensuring data integrity, enhancing access control, eliminating intermediaries, and increasing efficiency in healthcare. By focusing on a Brazilian case study, this paper explores the significance of EMR standards, security challenges, and blockchain-based approaches to promote interoperability and secure data sharing in the healthcare industry.

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