Integrated monitoring algorithms for software data security situation on private cloud computing platform Online publication date: Thu, 01-Apr-2021
by Ying Liu; Hai Tao Liu
International Journal of Internet Protocol Technology (IJIPT), Vol. 14, No. 1, 2021
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.
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