Overview of Personal Privacy Protection Technology in Big Data

Mao-Qiang, Yang; Fan, Li-Lve

doi:10.12783/dtetr/ssme-ist2016/4005

Cited by 1 publication

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The storage providers and holders of big data are separated, and the cloud storage service providers cannot guarantee that it is fully credible. Users' data is at risk of being peeping or tampered with by untrusted third parties [12] .…”

Section: Medical Big Data Management Riskmentioning

confidence: 99%

Research on the Influencing Factors and Improvement Strategies of Doctor-Patient Trust Under the Privacy and Security Perspective of Medical Big Data

Chen¹,

He²

2023

Proceedings of the 2nd International Conference on Information, Control and Automation, ICICA 2022, December 2-4, 2022, Chongqi

View full text Add to dashboard Cite

Both doctors and patients are the main bodies of medical activities. Therefore, mutual trust between doctors and patients is the basis of medical activities. Previous studies have shown that patient privacy leakage is one of the important influencing factors causing doctor-patient distrust. However, there are few studies on the influencing factors and promotion strategies for doctor-patient trust based on the perspective of medical big data privacy and security. The influencing factors and strategies to improve doctor-patient trust are discussed in this study from the perspective of medical big data privacy and security. This study combed 158 articles related to medical big data privacy and security. The research results show that the risk of medical big data leakage is mainly manifested in the risk of medical big data collection and application and the risk of medical big data management. Finally, effective methods and suggestions to prevent medical data leakage are further proposed. Moreover, it provides a new research perspective for alleviating doctor-patient conflict, improving doctor-patient relationship and enhancing doctor-patient trust in this study.

show abstract

Section: Medical Big Data Management Riskmentioning

confidence: 99%