Zawawi, NourHamdy, MohamedEl-Gohary, RaniaFahmy Tolba, Mohamed2019-10-262019-10-2611/28/2014Zawawi, N., El-Gohary, R., Hamdy, M., Tolba, M.F.: A novel watermarking approach for data integrity and non-repudiation in rational databases. In: Hassanien, A.E., Salem, A.-B.M., Ramadan, R., Kim, T.-h. (eds.) AMLTA 2012. CCIS, vol. 322, pp. 532–542. Springer, Heidelberg (2012) CrossRefGoogle Scholar 2. Bodden, E., Clasen, M., Kneis, J.: Arithmetic coding revealed a guided tour from theory to praxis. Technical report. McGill University (2007) Google Scholar 3. Brandt, J.: Transform coding for fast approximate nearest neighbor search in high dimensions. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1815–1822 (2010) Google Scholar 4. El-Zawawi, N., Hamdy, M., El-Gohary, R., Tolba, M.F.: A database watermarking service with a trusted authority architecture for cloud environment. International Journal of Computer Applications 69(13), 1–9 (2013) CrossRefGoogle Scholar 5. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: A view of cloud computing. Commun. ACM 53, 50–58 (2010) CrossRefGoogle Scholar 6. Agrawal, R., Kiernan, J.: Watermarking relational databases. In: Very Large DataBase, VLDB, pp. 155–166. Morgan Kaufmann (2002) Google Scholar 7. Li, Y., Swarup, V., Jajodia, S.: Constructing a virtual primary key for fingerprinting relational data. In: Digital Rights Management Workshop 2003 (2003) Google Scholar 8. Zhang, Y., Niu, X., Zhao, D., Li, J., Liu, S.: Relational databases watermark technique based on content characteristic. In: International Conference on Innovative Computing, Information and Control (ICICIC 2006) (2006) Google Scholar 9. Sion, R., Atallah, M., Prabhakar, S.: Rights protection for relational data. IEEE Transactions on Knowledge and Data Engineering 16(12), 1509–1525 (2004) CrossRefGoogle Scholar 10. Sion, R., Atallah, M., Prabhakar, S.: Rights protection for categorical data. IEEE Transactions on Knowledge and Data Engineering 17(7), 912–926 (2005) CrossRefGoogle Scholar 11. Li, Y., Guo, H., Jajodia, S.: Tamper detection and localization for categorical data using fragile watermarks. ACM (2004) Google Scholar 12. Li, Y., Deng, R.H.: Publicly verifiable ownership protection for relational databases. In: ACM Symposium on Information, Computer and Communications Security, ASIACCS (2006) Google Scholar 13. Kamel, I.: A schema for protecting the integrity of databases. Computers & Security 28, 698–709 (2009) CrossRefGoogle Scholar 14. Bhattacharya, S., Cortesi, A.: A distortion free watermark framework for relational databases. In: International Conference on Software and Data Technologies, ICSOFT (2009) Google Scholar 15. Bhattacharya, S., Cortesi, A.: A generic distortion free watermarking technique for relational databases. In: Prakash, A., Sen Gupta, I. (eds.) ICISS 2009. LNCS, vol. 5905, pp. 252–264. Springer, Heidelberg (2009) CrossRefGoogle Scholar 16. Bhattacharya, S., Cortesi, A.: Database authentication by distortion freewatermarking. In: International Conference on Software and Data Technologies. ICSOFT, vol. 5, pp. 219–226 (2010) Google Scholar 17. Pournaghshband, V.: A new watermarking approach for relational data. In: ACM Southeast Regional Conference, pp. 127–131 (2008) Google Scholar 18. Prasannakumari, V.: A roubust tamper proof watermarking for data integrity in relational database. Research Journal of Information Technology 1, 115–121 (2009) CrossRefGoogle Scholar 19. Gamal, G.H., Rashad, M.Z., Mohamed, M.A.: A simple watermark technique for relational database. Mansoura Journal for Computer Science and Information System (2008) Google Scholar 20. El-Bakry, H., Hamada, M.: A novel watermark technique for relational databases. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds.) AICI 2010, Part II. LNCS, vol. 6320, pp. 226–232. Springer, Heidelberg (2010) CrossRefGoogle Scholar 21. Sako, K.: Digital signature schemes. In: Encyclopedia of Cryptography and Security, 2nd edn., pp. 343–344. Springer (2011) Google Scholar 22. Sayood, K.: Introduction to Data Compression. Elsevier (2012) Google Scholar 23. Sayood, K.: Lossless Compression Handbook, ch. 5, pp. 101–152. Academic Press (2004) Google Scholar 24. Mohammed, A.A., Hussein, J.A.: Hybrid transform coding scheme for medical image application. In: IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pp. 237–240 (2010) Google Scholar 25. Han, J., Kamber, M., Pei, J.: Data Mining Concepts & Techniques, ch. 3, 3rd edn. Elsevier, Morgan Kaufmann (2011)https://doi.org/10.1007/978-3-319-13461-1_10https://cutt.ly/TyTKlxbMSA Google ScholarPreventing data abuses in cloud remains an essential point of the research. Proving the integrity and non-repudiation for large datasets over the cloud has an increasing attention of database community. Having security services based on watermarking techniques that enable permanent preservation for data tuples in terms of integrity and recovery for cloud environments presents the milestone of establishing trust between the data owners and the database cloud services. In this paper, an enhanced secure database service for Cloud environments (EWRDN) is proposed. It based over enhancements on WRDN as a data watermarking approach. The proposed service guarantees data integrity, privacy, and non-repudiation recovering data to its origin. Moreover, it gives data owner more controlling capabilities for their data by enabling tracing users’ activities. Two compression categories to recover data to its origin introduced for the proposed service. Two compression technique (the arithmetic encoding and the transform encoding) chosen to represent each type. For large data sets, it has been proven that, the arithmetic encoding has a fixed recovery ratio equal to one. At the same time, the transform encoding saves space and consumed less time to recover data. Moreover, testing the performance is done of the proposed service versus a large number of tuples, large data set. The performance quantified in terms of processing time and the required memory resources. The enhanced EWRDN service has shown a good performance in our experiments.en-USCopyright protectionDigital WatermarkingSecurity ServiceData CompressionLarge datasetArticlehttps://doi.org/10.1007/978-3-319-13461-1_10