Abstract
Nowadays, data stream processing is one of the basic requirements of many enterprises. In addition, many organizations can’t develop data stream management systems internally and must outsource this service. Such organizations should assure about the accuracy and the honesty of the outsourced server. In this setting, the data stream is generated and sent to the server by the owner. The users have no access to the data stream and they should to verify the integrity of the results. In this paper, we present a probabilistic auditing model for the integrity control of an outsourced data stream server. In our architecture, the server is considered as a black box and the auditing process is fulfilled by contribution between the data stream owner and the users. We exploit existing Data Stream Management Systems (DSMS) without any modification. Our method has no significant cost on users’ side and tolerates server load shedding accurately. Correctness and convergence of our probabilistic algorithm is proved. Our evaluation shows very good results.
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References
Arasu, A., et al.: STREAM: The Stanford Stream Data Manager. In: International Conference on Management of Data, Proceedings of the 2003 ACM SIGMOD, San Diego, California (2003)
Chandrasekaran, S., et al.: TelegraphCQ: Continuous Dataflow Processing for an Uncertain World. In: CIDR (2003)
Schmidt, et al.: Robust real-time query processing with QStream. In: Proceedings of the 31st International Conference on Very Large Data Bases, VLDB, Trondheim, Norway (2005)
Abadi, D., et al.: The Design of the Borealis Stream Processing Engine. In: 2nd Biennial Conference on Innovative Data Systems Research, CIDR 2005 (2005)
Abadi, D.J., et al.: Aurora: a new model and architecture for data stream management. The VLDB Journal 12(2), 120–139 (2003)
Xie, M., et al.: Providing freshness guarantees for outsourced databases. In: Proceedings of the 11th International Conference on Extending Database Technology: Advances in Database Technology, pp. 323–332. ACM, Nantes (2008)
Li, F., et al.: Proof-Infused Streams: Enabling Authentication of Sliding Window Queries On Streams. In: VLDB Endowment, Very Large Data Bases, Vienna (2007)
Merkle, R.C.: A certified digital signature. In: Brassard, G. (ed.) CRYPTO 1989. LNCS, vol. 435, pp. 218–238. Springer, Heidelberg (1990)
Papadopoulos, S., Yang, Y., Papadias, D.: Continuous authentication on relational streams. The VLDB Journal 19(2), 161–180 (2010)
Yi, K., et al.: Randomized Synopses for Query Assurance on Data Streams. In: Proceedings of the 2008 IEEE 24th International Conference on Data Engineering, pp. 416–425. IEEE Computer Society, Los Alamitos (2008)
Yi, K., et al.: Small synopses for group-by query verification on outsourced data streams. ACM Trans. Database Systems 34(3), 1–42 (2009)
Fiorini, P.M.: Modeling telecommunication systems with self-similar data traffic, p. 56. Department of Computer Science, The University of Connecticut (1998)
Dill, S., et al.: Self-similarity in the web. ACM Trans. Internet Technology 2(3), 205–223 (2002)
Wang, X., Liu, H., Er, D.: HIDS: a multifunctional generator of hierarchical data streams. SIGMIS Database 40(2), 29–36 (2009)
Xie, M., et al.: Integrity Auditing of Outsourced Data. In: VLDB Endowment. Very Large Data Bases, Vienna (2007)
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Ghayoori, M., Salmani, K., Haghjoo, M.S. (2011). Detecting changes in Stream Query Results. In: Nguyen, N.T., Trawiński, B., Jung, J.J. (eds) New Challenges for Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19953-0_2
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DOI: https://doi.org/10.1007/978-3-642-19953-0_2
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