通过关联分析分析大数据在安全和一般隐私问题中的作用

Sachin Gupta, Harsimran Jeet Singh
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引用次数: 0

摘要

大数据刚刚被广泛应用于多个行业,这大大增加了不同信息系统的数量。许多分析技术,如标准信息挖掘或定量测试技术,正在推动大数据行业的持续增长。通过评估、综合和使用现有数据获得新信息的潜力是big number的主要特征之一。另一个观点是,许多来源的内容确实有一个从采购到浪费的生命周期。但是,在产品生命周期的每个阶段都会出现对信息安全和可靠性的关注,这使得可以用于精确识别人员的数据的安全性成为整个过程中的关键目标。许多大数据分析方法可以用来评估用户活动,但是收集这些数据是违反用户隐私的。通过审查国际标准化组织发布的现行指导方针,并完成对研究分析的审查,本文探讨了大量数据交付所产生的风险和保密问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Analyzing of Role of Big Data in Security and General Privacy Problems through Correlation Analysis
Big data has just been extensively used across several businesses, which has significantly increased the number of different information systems. Numerous analysis techniques, such standard information mining or quantitative test techniques, are propelling the big data sector's continued growth. The potential to get new information via the evaluation, synthesis, and the use of existing data is one of big number's key features. Another is the idea that content from many sources does indeed have a life cycle that spans procurement through waste. But, concerns with infosec and dependability arise at every stage of a product's lifecycle, rendering the safety of data that can be used to precisely identify a people a key goal across the entire process. Numerous big data analysis approaches may be used to evaluate user activity, however collecting that data is against users' privacy. By examining current guidelines issued by international standardization groups and completing a review of research analysis, this paper explores risks and confidentiality issues that arise with delivery of enormous amounts of data.
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