Abstract
When it comes to cloud computing, people get concerned not only of privacy and integrity of their data but its location as well. This is particularly important due to the existence of variations of laws and regulations governing data storage and access mechanisms in different geographical regions. We will consider a distributed environment such as the cloud and try to verify whether the client-requested servers are holding the file they actually claim to hold. We make some plausible assumptions on the adversarial model and propose a scheme called CLVI for finding out geographical location of servers. Our scheme uses a challenge-response protocol instead of traditional pinging mechanism to accomplish its task. CLVI is able to detect location forgery and identify the adversary involved in the forgery. We validated our technique of detecting location forgery and approximating the adversary’s location using measurements from PlanetLab.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gill, P., Ganjali, Y., Wong, B., Lie, D.: Dude, where’s that ip?: circumventing measurement-based ip geolocation. In: Proceedings of the 19th USENIX conference on Security, p. 16. USENIX Association (2010)
Gueye, B., Ziviani, A., Crovella, M., Fdida, S.: Constraint-based geolocation of internet hosts. IEEE/ACM Transactions on Networking 14(6), 1219–1232 (2006)
Katz-Bassett, E., John, J.P., Krishnamurthy, A., Wetherall, D., Anderson, T., Chawathe, Y.: Towards ip geolocation using delay and topology measurements. In: Proceedings of the 6th ACM SIGCOMM Conference on Internet Measurement, pp. 71–84. ACM (2006)
Shacham, H., Waters, B.: Compact proofs of retrievability. In: Pieprzyk, J. (ed.) ASIACRYPT 2008. LNCS, vol. 5350, pp. 90–107. Springer, Heidelberg (2008)
Juels, A., Kaliski Jr, B.S.: Pors: Proofs of retrievability for large files. In: Proceedings of the 14th ACM Conference on Computer and Communications Security, pp. 584–597. ACM Press, New York (2007)
Tibshirani, R., Walther, G.: Cluster validation by prediction strength. Journal of Computational and Graphical Statistics 14(3), 511–528 (2005)
Planet-lab, http://www.planet-lab.org/ (last accessed June 29, 2014)
Needle, C.L., Catarino, R.: Evaluating the effect of real-time closures on cod targeting. ICES Journal of Marine Science: Journal du Conseil, fsr092 (2011)
Box plot rule, http://www.itl.nist.gov/div898/handbook/ (last accessed 29 June 2014)
Youn, I., Mark, B.L., Richards, D.: Statistical geolocation of internet hosts. In: Proceedings of 18th Internatonal Conference on Computer Communications and Networks, ICCCN 2009, pp. 1–6. IEEE (2009)
Eriksson, B., Barford, P., Sommers, J., Nowak, R.: A learning-based approach for IP geolocation. In: Krishnamurthy, A., Plattner, B. (eds.) PAM 2010. LNCS, vol. 6032, pp. 171–180. Springer, Heidelberg (2010)
Muir, J.A., Oorschot, P.C.V.: Internet geolocation: Evasion and counterevasion. ACM Computing Surveys (CSUR) 42(1), 4 (2009)
Benson, K., Dowsley, R., Shacham, H.: Do you know where your cloud files are? In: Proceedings of the 3rd ACM Workshop on Cloud Computing Security Workshop, pp. 73–82. ACM (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Galib, A.A., Rahman, R.M. (2015). Cloud Location Verification and Adversary Identification. In: Phon-Amnuaisuk, S., Au, T. (eds) Computational Intelligence in Information Systems. Advances in Intelligent Systems and Computing, vol 331. Springer, Cham. https://doi.org/10.1007/978-3-319-13153-5_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-13153-5_33
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13152-8
Online ISBN: 978-3-319-13153-5
eBook Packages: EngineeringEngineering (R0)