Develop security scripts to create vulnerable virtual machines and learn penetration testing techniques

The article demonstrates the concept of building a laboratory for penetration testing using a special pro-gram. The program is a set of scripts that configure the system in accordance with a user-defined script. Thanks to the elements of script randomization, this solution allows you to deploy several educational tasks at once to a group of students using only one virtual machine image. The basic idea is that the set-up and creation of a vulnerable target occurs just before the execution of the learning task itself. Those, the virtual machine is initially a basic Ubuntu Linux image that does not have any set of vulnerabilities. The main feature of the proposed solution is that the content of the scripts describes not one variant of the system configuration, but several at once, forming scripts with elements of randomization. In other words, having a basic Ubuntu Linux image and a set of the scripts, you can create different tasks for a dozen students.

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Toward Virtual Machine Image Management for Persistent Memory

ACM Transactions on Storage ◽

10.1145/3450976 ◽

2021 ◽

Vol 17 (3) ◽

pp. 1-24

Author(s):

Jiachen Zhang ◽

Lixiao Cui ◽

Peng Li ◽

Xiaoguang Liu ◽

Gang Wang

Keyword(s):

Virtual Machine ◽

Virtual Machines ◽

High Capacity ◽

Image Management ◽

Address Translation ◽

Persistent Memory ◽

Memory Virtualization ◽

Image Format ◽

Machine Image ◽

Virtual Machine Image

Persistent memory’s (PM) byte-addressability and high capacity will also make it emerging for virtualized environment. Modern virtual machine monitors virtualize PM using either I/O virtualization or memory virtualization. However, I/O virtualization will sacrifice PM’s byte-addressability, and memory virtualization does not get the chance of PM image management. In this article, we enhance QEMU’s memory virtualization mechanism. The enhanced system can achieve both PM’s byte-addressability inside virtual machines and PM image management outside the virtual machines. We also design pcow , a virtual machine image format for PM, which is compatible with our enhanced memory virtualization and supports storage virtualization features including thin-provisioning, base image, snapshot, and striping. Address translation is performed with the help of the Extended Page Table, thus much faster than image formats implemented in I/O virtualization. We also optimize pcow considering PM’s characteristics. We perform exhaustive performance evaluations on an x86 server equipping with Intel’s Optane DC persistent memory. The evaluation demonstrates that our scheme boosts the overall performance by up to 50× compared with qcow2, an image format implemented in I/O virtualization, and brings almost no performance overhead compared with the native memory virtualization. The striping feature can also scale-out the virtual PM’s bandwidth performance.

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VDN: Virtual machine image distribution network for cloud data centers

2012 Proceedings IEEE INFOCOM ◽

10.1109/infcom.2012.6195556 ◽

2012 ◽

Cited By ~ 81

Author(s):

Chunyi Peng ◽

Minkyong Kim ◽

Zhe Zhang ◽

Hui Lei

Keyword(s):

Virtual Machine ◽

Data Centers ◽

Distribution Network ◽

Image Distribution ◽

Cloud Data ◽

Cloud Data Centers ◽

Machine Image ◽

Virtual Machine Image

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Virtual Machines Scheduling Algorithm Based on Multi-Objective Optimization in Cloud Computing

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1046.508 ◽

2014 ◽

Vol 1046 ◽

pp. 508-511

Author(s):

Jian Rong Zhu ◽

Yi Zhuang ◽

Jing Li ◽

Wei Zhu

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Virtual Machine ◽

Virtual Machines ◽

Scheduling Algorithm ◽

Machine Scheduling ◽

Multi Objective Optimization ◽

Multi Objective ◽

Virtual Machine Scheduling ◽

Set Up

How to reduce energy consumption while improving utility of datacenter is one of the key technologies in the cloud computing environment. In this paper, we use energy consumption and utility of data center as objective functions to set up a virtual machine scheduling model based on multi-objective optimization VMSA-MOP, and design a virtual machine scheduling algorithm based on NSGA-2 to solve the model. Experimental results show that compared with other virtual machine scheduling algorithms, our algorithm can obtain relatively optimal scheduling results.

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