Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
6-2023
Abstract
A guest virtual machine in a cloud platform may fall “sick” when its kernel encounters a fatal low-level bug or is subverted by an adversary. The VM owner is hence likely to lose her control over it due to a kernel hang or being denied of remote accesses. While the VM can be rebooted with the assistance from the cloud server, the owner not only faces service disruption but also is left with no opportunity to make an in-depth diagnosis and forensics on the spot, not to mention a live rectification. Currently, the cloud service provider has neither incentive nor the technology to assist owners to resuscitate their falling VMs. In this paper, we propose a new cloud service termed VMCare-As-A-Service (VaaS) with the vision that the owner of a sick VM applies her tools running on a special VM to repair it. VaaS demands innovative cloud technologies for the unique infrastructure support as well as new software security techniques for attacks neutralization and runtime rectification upon a running and corrupted kernel. We examine the ensuing research challenges and present several preliminary approaches to kindle the interests from the community.
Keywords
Cloud computing, Runtime, Forensics, Maintenance engineering, Virtual machining, Software, Servers
Discipline
Information Security
Research Areas
Cybersecurity
Publication
2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks: Supplemental Volume (DSN-S): Porto, June 27-30: Proceedings
First Page
89
Last Page
93
ISBN
9798350325454
Identifier
10.1109/DSN-S58398.2023.00030
Publisher
IEEE Computer Society
City or Country
Los Alamitos, CA
Citation
DING, Xuhua.
How to resuscitate a sick VM in the cloud. (2023). 2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks: Supplemental Volume (DSN-S): Porto, June 27-30: Proceedings. 89-93.
Available at: https://ink.library.smu.edu.sg/sis_research/8098
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/DSN-S58398.2023.00030