This study investigated the integration readiness of four predominant cybersecurity Governance, Risk and Compliance (GRC) frameworks – NIST CSF 2.0, COBIT 2019, ISO 27001:2022, and the latest ISO 42001:2023 – for the opportunities, risks, and ...

• Evaluated Large Language Model (LLM) readiness in key cybersecurity frameworks.
• Found LLM integration opportunities and risk oversight gaps.
• Assessed readiness of current cybersecurity frameworks for EU AI Act.
• Urged expert ...

Building a secure and privacy-preserving health data sharing framework is a topic of great interest in the healthcare sector, but its success is subject to ensuring the privacy of user data. We clarified the definitions of privacy, confidentiality and ...

This study investigated the potential of Generative Pre-trained Transformers (GPTs), a state-of-the-art large language model, in generating cybersecurity policies to deter and mitigate ransomware attacks that perform data exfiltration. We ...

This study explores the implications of integrating Health Information System (HIS) on the security and privacy of sensitive patient information. It identifies existing gaps in research and proposes a novel security ontology model aimed at ...

Artificial intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (or Industry 4.0), which can be used for the protection of Internet-connected systems from cyber threats, attacks, damage, or unauthorized access. To ...

In this paper, we mainly formulate the problem of predicting smartphone usage based on contextual information, which involves both the user-centric and device-centric contexts. In the area of mobile analytics, traditional machine learning ...

Heart disease, alternatively known as cardiovascular disease, is the primary basis of death worldwide over the past few decades. To make an early diagnosis, a data-driven prediction model considering the associate risk factors in heart disease can ...