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An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method

by Victor R. Kebande, Nickson M. Karie
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 140 - Number 1
Year of Publication: 2016
Authors: Victor R. Kebande, Nickson M. Karie
10.5120/ijca2016909211

Victor R. Kebande, Nickson M. Karie . An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method. International Journal of Computer Applications. 140, 1 ( April 2016), 34-39. DOI=10.5120/ijca2016909211

@article{ 10.5120/ijca2016909211,
author = { Victor R. Kebande, Nickson M. Karie },
title = { An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method },
journal = { International Journal of Computer Applications },
issue_date = { April 2016 },
volume = { 140 },
number = { 1 },
month = { April },
year = { 2016 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume140/number1/24562-2016909211/ },
doi = { 10.5120/ijca2016909211 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:41:09.776117+05:30
%A Victor R. Kebande
%A Nickson M. Karie
%T An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 140
%N 1
%P 34-39
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The decline in traditional forensics and the emergence of cloud forensics has made it hard for digital forensic investigators to conduct digital investigations due to inadaptability of the cloud to digital forensic processes. Additionally, data that resides in the cloud is normally scattered across constantly changing data centers, hosts and virtual instances are easily destroyed as they are created. On the same note it is not easy to seize physical devices where a particular crime has occurred and locating the origin of an object in the cloud can be a challenge when we do not know where the actual data resides. Data provenance provides a solution whereby one can trace data based on the tag as it keeps changing directions in the cloud. However, if the distance between two particular tagged data is taken into account then the source and destination of an object can be located easily which can then enable digital forensic investigators to locate the physical devices. The problem that this paper is addressing is that, there is no easy way of locating data provenance in the cloud environment without estimating the distance between tagged data that moves in the cloud. Based on this, the authors have proposed a mechanism for locating the provenance of an object using successive bisection method. Similar test have been carried using different intervals in an experiment and the results are very promising.

References
  1. K. Muniswamy-Reddy and M. Seltzer, “Provenance as First Class Cloud Data,” SIGOPS Operating Systems Review, vol. 43, no. 4, pp. 11–16, 2010.
  2. M. I. M. Saad, K. A. Jalil and M. Manaf, "Achieving trust in cloud computing using secure data provenance," Open Systems (ICOS), 2014 IEEE Conference on, Subang, 2014, pp. 84-88.
  3. Zafarullah, F. Anwar and Z. Anwar, "Digital Forensics for Eucalyptus," Frontiers of Information Technology (FIT), 2011, Islamabad, 2011, pp. 110-116.
  4. Gary L Palmer.(2001). A Road Map for Digital Forensic Research. Technical Report DTR-T0010-01, DFRWS. Report for the First Digital Forensic Research Workshop (DFRWS).
  5. V. M. Katilu, V. N. L. Franqueira and O. Angelopoulou, "Challenges of Data Provenance for Cloud Forensic Investigations," Availability, Reliability and Security (ARES), 2015 10th International Conference on, Toulouse, 2015, pp. 312-317.
  6. Mell, Peter, and Tim Grance. "The NIST definition of cloud computing." (2011): 20-23.
  7. Suen, C. H., Ko, R. K., Tan, Y. S., Jagadpramana, P., & Lee, B. S. (2013, July). S2logger: End-to-end data tracking mechanism for cloud data provenance. In Trust, Security and Privacy in Computing and Communications (TrustCom), 2013 12th IEEE International Conference on(pp. 594-602). IEEE.
  8. Zhang, P., Tian, Y., & Liu, Z. (2009, February). Bisection method for evaluation of attraction region of passive dynamic walking. In Autonomous Robots and Agents, 2009. ICARA 2009. 4th International Conference on (pp. 692-697). IEEE.
  9. K. E. Atkinson, An Introduction to Numerical Analysis, New York: John Wiley and Sons, 1993.
  10. Pendharkar, P. C. (2008). A threshold varying bisection method for cost sensitive learning in neural networks. Expert Systems with Applications,34(2), 1456-1464.
  11. Trenwith, P. M., & Venter, H. S. (2014, August). A digital forensic model for providing better data provenance in the cloud. In Information Security for South Africa (ISSA), 2014 (pp. 1-6). IEEE.
  12. Suen, C. H., Ko, R. K., Tan, Y. S., Jagadpramana, P., & Lee, B. S. (2013, July). S2logger: End-to-end data tracking mechanism for cloud data provenance. In Trust, Security and Privacy in Computing and Communications (TrustCom), 2013 12th IEEE International Conference on(pp. 594-602). IEEE.
  13. Ko, R. K., & Will, M. A. (2014, June). Progger: An Efficient, Tamper-Evident Kernel-Space Logger for Cloud Data Provenance Tracking. In Cloud Computing (CLOUD), 2014 IEEE 7th International Conference on (pp. 881-889). IEEE.
  14. Kebande, V. R., & Venter, H. S. (2015, August). Adding event reconstruction to a Cloud Forensic Readiness model. In Information Security for South Africa (ISSA), 2015 (pp. 1-9). IEEE.
  15. Kebande, V. R., & Venter, H. S. (2014). A Cloud Forensic Readiness Model Using a Botnet as a Service. In The International Conference on Digital Security and Forensics (DigitalSec2014) (pp. 23-32). The Society of Digital Information and Wireless Communication.
  16. Kebande, V. R., & Venter, H. S. (2014, April). A cognitive approach for botnet detection using Artificial Immune System in the cloud. In Cyber Security, Cyber Warfare and Digital Forensic (CyberSec), 2014 Third International Conference on (pp. 52-57). IEEE.
  17. Kebande, V. R., & Venter, H. S. (2015, February). Obfuscating a Cloud-Based Botnet Towards Digital Forensic Readiness. In Iccws 2015-The Proceedings of the 10th International Conference on Cyber Warfare and Security (p. 434). Academic Conferences Limited.
  18. Kebande, V., & Venter, H. S. (2015, July). A Functional Architecture for Cloud Forensic Readiness Large-scale Potential Digital Evidence Analysis. In Proceedings of the 14th European Conference on Cyber Warfare and Security 2015: ECCWS 2015 (p. 373). Academic Conferences Limited.
  19. Kebande, V., & Venter, H. (2015, October). Towards a Model for Characterizing Potential Digital Evidence in the Cloud Environment during Digital Forensic Readiness Process. In ICCSM2015-3rd International Conference on Cloud Security and Management: ICCSM2015 (p. 151). Academic Conferences and publishing limited.
  20. Karie, N. M., & Venter, H. S. (2013, August). Towards a framework for enhancing potential digital evidence presentation. In Information Security for South Africa, 2013 (pp. 1-8). IEEE.
  21. Kebande, V., & Venter, H. Requirements for Achieving Digital Forensic Readiness in the Cloud Environment Using an NMB Solution. In 11th International Conference on Cyber Warfare and Security: ICCWS2016 (p. 399). Academic Conferences and publishing limited.
  22. Kebande, V., Hermann Stephane Ntsamo & Venter, H. Towards a prototype for Achieving Digital Forensic Readiness in the Cloud using a Distributed NMB Solution. In 15th International Conference on Cyber Warfare and Security: ECCWS2016. Academic Conferences and publishing limited.-To Appear.
  23. Frank Tyger)” CS 211 Lesson 10 “Program Design” [online]-Accessed at “http://cse.unl.edu/~sincovec/Matlab/Lesson%2010/CS211%20Lesson%2010%20-%20Program%20Design.htm
Index Terms

Computer Science
Information Sciences

Keywords

Forensic data provenance object cloud bisection method

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