A review on Privacy-Preserving Data Preprocessing

M. Soni, Yashkumar Barot, S. Gomathi
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引用次数: 27

Abstract

Health care information has great potential for improving the health care system and also providing fast and accurate outcomes for patients, predicting disease outbreaks, gaining valuable information for prediction in future, preventing such diseases, reducing healthcare costs, and improving overall health. In any case, deciding the genuine utilization of information while saving the patient's identity protection is an overwhelming task. Regardless of the amount of medical data it can help advance clinical science and it is essential to the accomplishment of all medicinal services associations, at the end information security is vital. To guarantee safe and solid information security and cloud-based conditions, It is critical to consider the constraints of existing arrangements and systems for the social insurance of information security and assurance. Here we talk about the security and privacy challenges of high-quality important data as it is used mainly by the healthcare structure and similar industry to examine how privacy and security issues occur when there is a large amount of healthcare information to protect from all possible threats. We will discuss ways that these can be addressed. The main focus will be on recently analyzed and optimized methods based on anonymity and encryption, and we will compare their strengths and limitations, and this chapter closes at last the privacy and security recommendations for best practices for privacy of preprocessing healthcare data.
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隐私保护数据预处理研究进展
医疗保健信息在改善医疗保健系统,为患者提供快速准确的结果,预测疾病爆发,获得未来预测的有价值信息,预防此类疾病,降低医疗保健成本和改善整体健康方面具有巨大潜力。无论如何,在保护患者身份的同时,决定信息的真正利用是一项艰巨的任务。无论医疗数据的数量如何,它都可以帮助推进临床科学,并且对于所有医疗服务协会的实现至关重要,最终信息安全至关重要。为保障信息安全和云基础条件下的安全、稳固,必须考虑现有信息安全社会保障安排和制度的约束。在这里,我们将讨论高质量重要数据的安全和隐私挑战,因为它主要由医疗保健结构和类似行业使用,以研究当存在大量医疗保健信息以防止所有可能的威胁时,隐私和安全问题是如何发生的。我们将讨论解决这些问题的方法。重点将放在最近分析和优化的基于匿名和加密的方法上,我们将比较它们的优点和局限性,本章最后结束了对预处理医疗数据隐私的最佳实践的隐私和安全建议。
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