Big Data Analysis and Perturbation using Data Mining Algorithm

IF 1 4区心理学 Q3 PSYCHOLOGY, CLINICAL

Journal of Social and Clinical Psychology Pub Date : 2021-04-19 DOI:10.36548/JSCP.2021.1.003

W. Haoxiang, S. Smys

引用次数: 69

Abstract

The advancement and introduction of computing technologies has proven to be highly effective and has resulted in the production of large amount of data that is to be analyzed. However, there is much concern on the privacy protection of the gathered data which suffers from the possibility of being exploited or exposed to the public. Hence, there are many methods of preserving this information they are not completely scalable or efficient and also have issues with privacy or data utility. Hence this proposed work provides a solution for such issues with an effective perturbation algorithm that uses big data by means of optimal geometric transformation. The proposed work has been examined and tested for accuracy, attack resistance, scalability and efficiency with the help of 5 classification algorithms and 9 datasets. Experimental analysis indicates that the proposed work is more successful in terms of attack resistance, scalability, execution speed and accuracy when compared with other algorithms that are used for privacy preservation.

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基于数据挖掘算法的大数据分析与扰动

计算技术的进步和引入已被证明是非常有效的，并导致了大量需要分析的数据的产生。然而，收集到的数据有可能被利用或暴露在公众面前，其隐私保护问题备受关注。因此，有许多保存这些信息的方法，它们不是完全可扩展或有效的，并且在隐私或数据实用程序方面也存在问题。因此，本文提出了一种有效的微扰算法，通过最优几何变换利用大数据来解决这些问题。在5种分类算法和9个数据集的帮助下，对所提出的工作进行了准确性、抗攻击性、可扩展性和效率的检验和测试。实验分析表明，与其他用于隐私保护的算法相比，该算法在抗攻击、可扩展性、执行速度和准确性方面取得了更大的成功。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Social and Clinical Psychology Multiple-

CiteScore

2.90

自引率

0.00%

发文量

期刊介绍： This journal is devoted to the application of theory and research from social psychology toward the better understanding of human adaptation and adjustment, including both the alleviation of psychological problems and distress (e.g., psychopathology) and the enhancement of psychological well-being among the psychologically healthy. Topics of interest include (but are not limited to) traditionally defined psychopathology (e.g., depression), common emotional and behavioral problems in living (e.g., conflicts in close relationships), the enhancement of subjective well-being, and the processes of psychological change in everyday life (e.g., self-regulation) and professional settings (e.g., psychotherapy and counseling). Articles reporting the results of theory-driven empirical research are given priority, but theoretical articles, review articles, clinical case studies, and essays on professional issues are also welcome. Articles describing the development of new scales (personality or otherwise) or the revision of existing scales are not appropriate for this journal.