Efficient discovery of malicious symptoms in clouds via monitoring virtual machines

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

In this new era of life, where technology covers our life from the early morning to late night, cybercrime is becoming more developed and challenging for the systems designers. The reason is reflected in the increased number of ways used by criminals. Cloud computing systems are natural goals due to their complexity and increasing popularity. The Cloud system provides an environment with a big number of Virtual Machines (VMs) that available to many users accessing this system via the Internet. This way of access makes cloud systems weaker than physical networks. In order to reduce the number of attacks and secure data storage, any malicious behaviour should be discovered and halted if possible. In this paper, we focus on discovery of malicious behaviour via determining unwanted symptoms rather than via targeting particular malicious behaviour of the system directly. The main motivation for our approach is that malicious behaviour (e.g., a new form of threat) is very often hard to specify directly, but it can be characterized by a set of undesired symptoms. The main contribution of this paper refers to several new mechanisms for monitoring Virtual Machines and further experimental work targeting efficient ways of visiting VMs in order to discover malicious symptoms.

Original languageEnglish (US)
Title of host publicationProceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
EditorsLuigi Atzori, Xiaolong Jin, Stephen Jarvis, Lei Liu, Ramon Aguero Calvo, Jia Hu, Geyong Min, Nektarios Georgalas, Yulei Wu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1703-1710
Number of pages8
ISBN (Electronic)9781509001545
DOIs
StatePublished - Dec 22 2015
Externally publishedYes
Event15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 - Liverpool, United Kingdom
Duration: Oct 26 2015Oct 28 2015

Publication series

NameProceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015

Conference

Conference15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
CountryUnited Kingdom
CityLiverpool
Period10/26/1510/28/15

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Keywords

  • Cloud computing, Reduce-Max
  • Cloud monitoring
  • Malicious behaviour
  • Network patrolling
  • Virtual Machines

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence
  • Computer Networks and Communications

Cite this

Alshamrani, S. S., Kowalski, D. R., & Gasieniec, L. A. (2015). Efficient discovery of malicious symptoms in clouds via monitoring virtual machines. In L. Atzori, X. Jin, S. Jarvis, L. Liu, R. A. Calvo, J. Hu, G. Min, N. Georgalas, & Y. Wu (Eds.), Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 (pp. 1703-1710). [7363303] (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.257