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The results captured in this study have been limited to the VMware cloud; however
ongoing work explores further testing on the Citrix Xen-Kernel host, as well as
VCentre newer infrastructure 4, to demonstrate further schematic mapping constraints
by our log auditor. Also, we use static snapshot analysis of the log events to perform
this system study.
5 Conclusion and Future Work
In this paper the authors have presented formal structural properties for auditing a
synchronized VM cloud environment. We used schematic associative mapping
formalisms to link these properties. We substantiated our formalisms by a preliminary
experimental study. Further work explores associative mining rules that not only
correlate log frequency on a synchronized event but also classifies the behavior of
these events as forensic concern for this virtual machine log auditor.
References
1. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In:
VLDB Conference, pp. 487-499 (1994)
2. Dehaspe, L., Toivonen, H.: Discovery of frequent, datalog patterns. Data Mining.
Knowledge. Discovery 3(1), 7-36
3. Ordonez, C.: Models for association rules based on clustering and correlation. Intelligent
Data Analysis 13(2), 337-358 (2009)
4. Yan, X., Cheng, H., Han, J., Yu, P.S.: Mining significant graph patterns by leap search. In:
SIGMOD, Conference, pp. 433-444 (2008)
5. http://www.usenix.org/events/osdi99/full_papers/wang/wang_html/
node8.html
6. Arenas, et.al.: Inverting Schema Mappings: Bridging the Gap between Theory and Practice.
PVLDB 2(1), 1018-1029 (2009)
7. Grandison, T., Maximillen, E.M., Thorpe, S., Alba, A.: Towards a formal definition of
Cloud Computing. In: Proceedings of IEEE Services (2010)
8. Mahavan, J., Harvey, A.: Composing Mappings among Data Sources. In: VLDB, pp. 251-
262 (1996)
9. ten Cate, B., Kolaitis, P.: Structural Characterizations of Schema Mapping Languages.
In: ICDT, pp. 63-72 (2009)
 
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