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Using Virtual Machine Introspection for Operating Systems Security Education

Published: 21 February 2018 Publication History

Abstract

Historically, hands-on cybersecurity exercises helped reinforce the basic cybersecurity concepts. However, most of them focused on the user level attacks and defenses and did not provide a convenient way of studying the kernel level security. Since OS kernels provide foundations for applications, any compromise to OS kernels will lead to a computer that cannot be trusted. Moreover, there has been a great interest in using virtualization to profile, characterize, and observe kernel events including security incidents. Virtual Machine Introspection (VMI) is a technique that has been deeply investigated in intrusion detection, malware analysis, and memory forensics. Inspired by the great success of VMI, we used it to develop hands-on labs for teaching kernel level security. In this work, we present three VMI-based labs on (1) stack-based buffer over-flow, (2) direct kernel object manipulation (DKOM), and (3) kernel integrity checker which have been made available online. Then, we analyze the differences in approaches taken by VMI-based labs and traditional labs and conclude that VMI-based labs are better as opposed to traditional labs from a teaching standpoint because they provide more visibility than the traditional labs and superior ability to manipulate kernel memory which provides more insight into kernel security concepts.

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cover image ACM Conferences
SIGCSE '18: Proceedings of the 49th ACM Technical Symposium on Computer Science Education
February 2018
1174 pages
ISBN:9781450351034
DOI:10.1145/3159450
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 21 February 2018

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SIGCSE '18 Paper Acceptance Rate 161 of 459 submissions, 35%;
Overall Acceptance Rate 1,595 of 4,542 submissions, 35%

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  • (2021)Introspect Virtual Machines Like It Is the Linux Kernel!Detection of Intrusions and Malware, and Vulnerability Assessment10.1007/978-3-030-80825-9_13(258-277)Online publication date: 9-Jul-2021
  • (2020)SIGITE and SIGCSE SymposiumsProceedings of the 21st Annual Conference on Information Technology Education10.1145/3368308.3415400(132-137)Online publication date: 7-Oct-2020
  • (2019)Topological Scoring of Concept Maps for Cybersecurity EducationProceedings of the 50th ACM Technical Symposium on Computer Science Education10.1145/3287324.3287495(731-737)Online publication date: 22-Feb-2019
  • (2019)Evaluation of Peer Instruction for Cybersecurity EducationProceedings of the 50th ACM Technical Symposium on Computer Science Education10.1145/3287324.3287403(720-725)Online publication date: 22-Feb-2019
  • (2018)Discover and Secure (DaS): An Automated Virtual Machine Security Management Framework2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC)10.1109/PCCC.2018.8711239(1-6)Online publication date: Nov-2018

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