{"title":"Navigating the landscape: Safeguarding privacy and security in the era of ambient intelligence within healthcare settings","authors":"Tarun Vats , Sudhakar Kumar , Sunil K. Singh , Uday Madan , Mehak Preet , Varsha Arya , Ritika Bansal , Ammar Almomani","doi":"10.1016/j.csa.2024.100046","DOIUrl":null,"url":null,"abstract":"<div><p>Ambient intelligence technologies have the potential to transform healthcare by providing personalized, context-aware, and proactive support for patients and healthcare providers. However, the use of these technologies in healthcare settings raises important privacy and security concerns that must be addressed to ensure patient trust and acceptance. This paper explores the privacy and security considerations related to the utilization of ambient intelligence in healthcare, aiming to address the associated risks and establish a robust security infrastructure. By reviewing the inherent privacy and security risks in healthcare settings employing ambient intelligence, discussing the ethical and legal considerations, and proposing mitigation strategies, the focus is on ensuring patient trust and acceptance.The architecture that is being presented is a comprehensive one with interconnected layers that guarantees data confidentiality, integrity, and privacy in the ambient intelligence healthcare system. This protects sensitive data and maintains its continuous availability. This research helps to establish a safe environment that supports the transformational potential of ambient intelligence in healthcare while putting patient privacy and data protection first by thoroughly addressing privacy and security concerns.</p></div>","PeriodicalId":100351,"journal":{"name":"Cyber Security and Applications","volume":"2 ","pages":"Article 100046"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772918424000122/pdfft?md5=efe7200683f294a4dc27ed3363c6368a&pid=1-s2.0-S2772918424000122-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cyber Security and Applications","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772918424000122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Ambient intelligence technologies have the potential to transform healthcare by providing personalized, context-aware, and proactive support for patients and healthcare providers. However, the use of these technologies in healthcare settings raises important privacy and security concerns that must be addressed to ensure patient trust and acceptance. This paper explores the privacy and security considerations related to the utilization of ambient intelligence in healthcare, aiming to address the associated risks and establish a robust security infrastructure. By reviewing the inherent privacy and security risks in healthcare settings employing ambient intelligence, discussing the ethical and legal considerations, and proposing mitigation strategies, the focus is on ensuring patient trust and acceptance.The architecture that is being presented is a comprehensive one with interconnected layers that guarantees data confidentiality, integrity, and privacy in the ambient intelligence healthcare system. This protects sensitive data and maintains its continuous availability. This research helps to establish a safe environment that supports the transformational potential of ambient intelligence in healthcare while putting patient privacy and data protection first by thoroughly addressing privacy and security concerns.