Abstract: The application discloses a load evaluation system for virtual machines in a cloud environment, comprising: a monitored data collecting module which is configured to collect monitored data from one or more virtual machines in a cloud data center; a monitored data processing module which is coupled with the monitored data collecting module and is configured to: perform aggregated grouping on the monitored data by using a first KMeans algorithm for each of the one or more virtual machines, each group having a center point coordinate, and calculate a performance characteristic of each virtual machine of the one or more virtual machines according to the grouping and the center point coordinates of individual groups, i.e.

Abstract: The invention provides a compliance detecting method of payment applications in a virtualized environment, and pertains to the field of security technology of payment applications. The detecting method is used for compliance detection for PCI DSS isolation demands. The detecting method can determine whether it is a compliance state by analyzing the current virtual machine domain and its connection from data stream, and can also determine whether it is a compliance state by analyzing the purity of network flow of virtual machines. The detecting method is suitable for a virtualized environment and makes the detection of compliance accurate in the virtualized environment, thus being advantageous for guaranteeing the security of payment applications.

Abstract: The present invention proposes a method for offline upgrading virtual machine mirror images. The method comprises: an mirror image security server collecting virtual machine mirror images, and extracting and storing the information of the collected virtual machine mirror images; and the mirror image security server executing an upgrade operation of virtual machine mirror images in an offline way based on the information of the collected virtual machine mirror images. The method for offline upgrading virtual machine mirror images disclosed in the present invention has higher upgrade efficiency and is capable of upgrading the virtual machine mirror images in an offline way.

Abstract: The application discloses a load evaluation system for virtual machines in a cloud environment, comprising: a monitored data collecting module which is configured to collect monitored data from one or more virtual machines in a cloud data center; a monitored data processing module which is coupled with the monitored data collecting module and is configured to: perform aggregated grouping on the monitored data by using a first KMeans algorithm for each of the one or more virtual machines, each group having a center point coordinate, and calculate a performance characteristic of each virtual machine of the one or more virtual machines according to the grouping and the center point coordinates of individual groups, i.e.

Abstract: The present invention proposes a method for offline upgrading virtual machine mirror images. The method comprises: an mirror image security server collecting virtual machine mirror images, and extracting and storing the information of the collected virtual machine mirror images; and the mirror image security server executing an upgrade operation of virtual machine mirror images in an offline way based on the information of the collected virtual machine mirror images. The method for offline upgrading virtual machine mirror images disclosed in the present invention has higher upgrade efficiency and is capable of upgrading the virtual machine mirror images in an offline way.

Abstract: The invention provides a compliance detecting method of payment applications in a virtualized environment, and pertains to the field of security technology of payment applications. The detecting method is used for compliance detection for PCI DSS isolation demands. The detecting method can determine whether it is a compliance state by analyzing the current virtual machine domain and its connection from data stream, and can also determine whether it is a compliance state by analyzing the purity of network flow of virtual machines. The detecting method is suitable for a virtualized environment and makes the detection of compliance accurate in the virtualized environment, thus being advantageous for guaranteeing the security of payment applications.