Title: Research on the detection of privacy information sharing behaviour of e-commerce users based on big data
Authors: Dongmei Xia; Wei Chen; Yingji Li; Xuan Fu
Addresses: ChongQing Institute of Engineering, ChongQing, 400056, China ' ChongQing Institute of Engineering, ChongQing, 400056, China ' ChongQing Institute of Engineering, ChongQing, 400056, China ' ChongQing Institute of Engineering, ChongQing, 400056, China
Abstract: In order to solve the problems of behaviour data dimensionality reduction and confidence skewness in the detection process of traditional e-commerce users' privacy information sharing, an e-commerce users' information behaviour detection method based on big data technology was proposed-Big data technology is used to complete the data storage activities in combination with MYSQL text. According to the storage big database, the storage format is divided, and the big data reduction activities are carried out. The big data reduction and dimensionality reduction operations are used to realise the big data reduction. Based on the low-dimensional data, the density point comparison of shared information is carried out, and the abnormal IP is queried according to the comparison results to realise the detection of data behaviour. Experimental results show that the detection method has better effect and higher confidence in reducing the dimension of privacy big data of e-commerce users.
Keywords: big data; e-commerce users; privacy information; sharing behaviour; information density point; data storage activities; storage big database; low-dimensional data.
International Journal of Autonomous and Adaptive Communications Systems, 2022 Vol.15 No.3, pp.249 - 265
Received: 28 Nov 2019
Accepted: 15 May 2020
Published online: 09 Sep 2022 *