Title: Integrated monitoring algorithms for software data security situation on private cloud computing platform

Authors: Ying Liu; Hai Tao Liu

Addresses: Department of Information Technology and Management Engineering, Inner Mongolia Technical College of Mechanics and Electrics, Hohhot 010010, China ' Department of Information Technology and Management Engineering, Inner Mongolia Technical College of Mechanics and Electrics, Hohhot 010010, China

Abstract: Aiming at the problems of large monitoring error, poor real-time performance, serious missing detection of abnormal data and high energy consumption in current data security monitoring methods, a comprehensive monitoring algorithm of software data security situation for private cloud computing platform based on scenario entropy is proposed. Based on data redundancy clearance and data security mechanism, data security situation monitoring indicators are selected, and the scenario entropy difference of each index calculated is taken as monitoring target. The experimental results show that the detection error of this method is between 1% and 3%, and it has high monitoring accuracy. The anomalous response delay is between 0.5 and 1 µs, which has high response efficiency. The loss rate of abnormal data is between 0.2% and 0.5%, and the rate of missing abnormal data is low. The monitoring energy consumption is between 60 NJ and 75 NJ, and the monitoring energy consumption is low.

Keywords: private cloud; data; security situation; monitoring.

DOI: 10.1504/IJIPT.2021.113897

International Journal of Internet Protocol Technology, 2021 Vol.14 No.1, pp.1 - 9

Received: 14 Jan 2019
Accepted: 05 Apr 2019

Published online: 01 Apr 2021 *

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