Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Natarajan, Arul Kumar; Upreti, Kamal; Kshirsagar, Pravin R.; Tak, Tan Kuan Title A name given to the resource Generative AI for Healthcare Security: Addressing Privacy Challenges through Anomaly Detection in Healthcare Communications Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Advances in Artificial Intelligence for Healthcare Applications;pp.60-71 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003503385-5" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003503385-5</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105005686847?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105005686847?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Natarajan A.K., Samarkand International University of Technology, Samarkand, Uzbekistan; Upreti K., Christ (Deemed to be University), Delhi NCR, India; Kshirsagar P.R., J D College of Engineering &amp; Management, Maharashtra, Nagpur, India; Tak T.K., Singapore Institute of Technology, Punggol, Singapore Description An account of the resource Cybersecurity within the healthcare sector is paramount due to the sensitive nature of patient data and critical healthcare services. This chapter explores the role of Generative AI (GAI), particularly using BERT embeddings and the Isolation Forest algorithm, in enhancing cybersecurity measures. It begins by discussing the significance of cybersecurity in healthcare and the potential threats healthcare organizations face, emphasizing the need for robust security measures to protect patient data and ensure uninterrupted healthcare services. The chapter provides an overview of GAI and its applications in cybersecurity, focusing on its ability to detect anomalies in healthcare communications. A detailed case study demonstrates the practical implementation of GAI techniques for anomaly detection in healthcare emails, highlighting the effectiveness of BERT embeddings and Isolation Forest in identifying potential security breaches. Furthermore, the chapter discusses the broader implications of generative AI in healthcare cybersecurity, addressing privacy concerns and ethical considerations. The findings underscore the importance of integrating advanced AI technologies with robust privacy-preserving measures to safeguard patient data while promoting technological innovation in healthcare cybersecurity. 2025 selection and editorial matter, Anoop V.S., Suhasini Verma, Usharani Hareesh Govindarajan. Publisher An entity responsible for making the resource available CRC Press Relation A related resource ISBN: 978-104035486-5; 978-103282187-0; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online