Abstract
Knowledge extraction from sensitive data often needs collaborative work. Statistical databases are generated from such data and shared among various stakeholders. In this context, the ownership protection of shared data becomes important. Watermarking is emerging to be a very effective tool for imposing ownership rights on various digital data formats. Watermarking of such datasets may bring distortions in the data. Consequently, the extracted knowledge may be inaccurate. These distortions are controlled by the usability constraints, which in turn limit the available bandwidth for watermarking. Large bandwidth ensures robustness; however, it may degrade the quality of the data. Such a situation can be resolved by optimizing the available bandwidth subject to the usability constraints. Optimization techniques, particularly bioinspired techniques, have become a preferred choice for solving such issues during the past few years. In this paper, we investigate the usability of various optimization schemes for identifying the maximum available bandwidth to achieve two objectives: (1) preserving the knowledge stored in the data; (2) maximizing the available bandwidth subject to the usability constraints to achieve maximum robustness. The first objective is achieved with a usability constraint model, which ensures that the knowledge is not compromised as a result of watermark embedding. The second objective is achieved by finding the maximum bandwidth subject to the usability constraints specified in the first objective. The performance of optimization schemes is evaluated using different metrics.
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References
Agrawal R, Kiernan J, 2002. Watermarking relational data-bases. Proc 28th Int Conf on Very Large Databases, p.155–166. https://doi.org/10.1016/B978-155860869-6/50022-6
Atallah MJ, Raskin V, Hempelmann CF, et al., 2002. Natural language watermarking and tamper-proofing. Int Work-shop on Information Hiding, p.196–212. https://doi.org/10.1007/3-540-36415-3_13
Bertino E, Ooi BC, Yang Y, et al., 2005. Privacy and ownership preserving of outsourced medical data. Proc 21st Int Conf on Data Engineering, p.521–532. https://doi.org/10.1109/ICDE.2005.111
Duran MA, Grossmann IE, 1986. An outer-approximation algorithm for a class of mixed-integer nonlinear programs. Math Programm, 36(3):307–339. https://doi.org/10.1007/BF02592064
Elbeltagi E, Hegazy T, Grierson D, 2005. Comparison among five evolutionary-based optimization algorithms. Adv Eng Inform, 19(1):43–53. https://doi.org/10.1016/j.aei.2005.01.004
Engelbrecht AP, 2007. Computational Intelligence: an Intro-duction (2nd Ed.). Wiley, New York.
Franco-Contreras J, Coatrieux G, 2015. Robust watermarking of relational databases with ontology-guided distortion control. IEEE Trans Inform Forens Secur, 10(9):1939–1952. https://doi.org/10.1109/TIFS.2015.2439962
Franco-Contreras J, Coatrieux G, Cuppens F, et al., 2014. Robust lossless watermarking of relational databases based on circular histogram modulation. IEEE Trans In-form Forens Secur, 9(3):397–410. https://doi.org/10.1109/TIFS.2013.2294240
Grossmann IE, Kravanja Z, 1997. Mixed-integer nonlinear programming: a survey of algorithms and applications. In: Biegler LT, Coleman TF, Conn AR, et al. (Eds.), Large-Scale Optimization with Applications. Part II: Op-timal Design and Control. Springer, New York, NY, p.73–100. https://doi.org/10.1007/978-1-4612-1960-6_5
Hartung F, Kutter M, 1999. Multimedia watermarking tech-niques. Proc IEEE, 87(7):1079–1107. https://doi.org/10.1109/5.771066
Holland, JH, 1992. Adaptation in Natural and Artificial Sys-tems: an Introductory Analysis with Applications to Bi-ology, Control, and Artificial Intelligence. MIT Press, Cambridge, MA.
Iqbal S, Rauf A, Mahfooz S, et al., 2012. Self-constructing fragile watermark algorithm for relational database in-tegrity proof. World Appl Sci J, 19(9):1273–1277. https://doi.org/10.5829/idosi.wasj.2012.19.09.1865
Kamran M, Farooq M, 2012. An information-preserving wa-termarking scheme for right protection of EMR systems. IEEE Trans Knowl Data Eng, 24(11):1950–1962. https://doi.org/10.1109/TKDE.2011.223
Kamran M, Farooq M, 2013. A formal usability constraints model for watermarking of outsourced datasets. IEEE Trans Inform Forens Secur, 8(6):1061–1072. https://doi.org/10.1109/TIFS.2013.2259234
Kamran M, Suhail S, Farooq M, 2013. A robust, distortion minimizing technique for watermarking relational data-bases using once-for-all usability constraints. IEEE Trans Knowl Data Eng, 25(12):2694–2707. https://doi.org/10.1109/TKDE.2012.227
Kennedy J, Eberhart R, 1995. Particle swarm optimization. Proc IEEE Int Conf on Neural Networks, p.1942–1948. https://doi.org/10.1109/ICNN.1995.488968
Khanduja V, Verma OP, 2012. Identification and proof of ownership by watermarking relational databases. Int J Inform Electron Eng, 2(2):274–277. https://doi.org/10.7763/IJIEE.2012.V2.97
Khanduja V, Chakraverty S, Verma OP, 2015. Watermarking categorical data: algorithm and robustness analysis. Def Sci J, 65(3):226–232. https://doi.org/10.14429/dsj.65.8444
Rani S, Kachhap P, Haider R, 2016. Dataflow analysis-based approach of database watermarking. In: Chaki R, Cortesi A, Saeed K (Eds.), Advanced Computing and Systems for Security, Volume 2. Springer, New Delhi, p.153–171. https://doi.org/10.1007/978-81-322-2653-6_11
Rao UP, Patel DR, Vikani PM, 2012. Relational database watermarking for ownership protection. Proc Technol, 6:988–995. https://doi.org/10.1016/j.protcy.2012.10.120
Schrage LE, 1991. LINDO: an Optimization Modeling System (4th Ed.). Scientific Press, South San Francisco, CA.
Shehab M, Bertino E, Ghafoor A, 2008. Watermarking rela-tional databases using optimization-based techniques. IEEE Trans Knowl Data Eng, 20(1):116–129. https://doi.org/10.1109/TKDE.2007.190668
Sion R, Atallah M, Prabhakar S, 2004. Rights protection for relational data. IEEE Trans Knowl Data Eng, 16(12): 1509–1525. https://doi.org/10.1109/TKDE.2004.94
Wang YM, Gao YX, 2012. The digital watermarking algorithm of the relational database based on the effective bits of numerical field. World Automation Congress, p.1–4.
Wolfgang RB, Delp EJ, 1996. A watermark for digital images. Proc 3rd IEEE Int Conf on Image Processing, p.219–222. https://doi.org/10.1109/ICIP.1996.560423
Wylie JE, Mineau GP, 2003. Biomedical databases: protecting privacy and promoting research. Trends Biotechnol, 21(3):113–116. https://doi.org/10.1016/S0167-7799(02)00039-2
Zhang LZ, Gao W, Jiang N, et al., 2011. Relational databases watermarking for textual and numerical data. Int Conf on Mechatronic Science, Electric Engineering and Computer, p.1633–1636. https://doi.org/10.1109/MEC.2011.6025791
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Kamran, M., Munir, E.U. On the role of optimization algorithms in ownership-preserving data mining. Frontiers Inf Technol Electronic Eng 19, 151–164 (2018). https://doi.org/10.1631/FITEE.1601479
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DOI: https://doi.org/10.1631/FITEE.1601479