[1] Al-onazi, B.B., Alotaib, S.S., Alshahrani, S.M., Alotaibi, N., Alnfiai, M.M., Salama, A.S., Hamza, M.A. (2023). Automated Arabic text classification using hyperparameter tuned hybrid deep learning model. Computers, Materials & Continua, 74(3): 5447-5465. https://doi.org/10.32604/cmc.2023.033564
[2] Petitcolas, F.A.P., Anderson, R.J., Kuhn, M.G. (1998). Attacks on copyright marking systems. Information Hiding, 218-238. https://doi.org/10.1007/3-540-49380-8_16
[3] Wolfgang, R.B., Podilchuck, C.I., Delp, E.J. (1999). Perceptual watermarks for digital images and video. Proceedings of the IEEE, 87(7): 1108-1126. https://doi.org/10.1109/5.771067
[4] Ghosal, S.K., Mandal, J.K. (2013). Stirling transform based color image authentication. Procedia Technology, 10: 95-104. https://doi.org/10.1016/j.protcy.2013.12.341
[5] Gola, K.K., Gupta, B., Iqbal, Z. (2014). Modified RSA digital signature scheme for data confidentiality. International Journal of Computer Applications, 106(13). https://doi.org/10.5120/18579-9848
[6] Yong, P.E.N.G., Wei, Z.H.A.O., Feng, X.I.E., Dai, Z.H., Yang, G.A.O., Chen, D.Q. (2012). Secure cloud storage based on cryptographic techniques. The Journal of China Universities of Posts and Telecommunications, 19: 182-189. https://doi.org/10.1016/S1005-8885(11)60424-X
[7] Salavi, R.R., Math, M.M., Kulkarni, U.P. (2019). A survey of various cryptographic techniques: From traditional cryptography to fully hom*omorphic encryption. Innovations in Computer Science and Engineering, 295-305. https://doi.org/10.1007/978-981-13-7082-3_34
[8] Sultan, K., Aldhafferi, N., Alqahtani, A., Mahmud, M. (2018). Reversible and fragile watermarking for medical images. Computational and Mathematical Methods in Medicine, 2018: 3461382. https://doi.org/10.1155/2018/3461382
[9] Balasamy, K., Shamia, D. (2023). Feature extraction-based medical image watermarking using fuzzy-based median filter. IETE Journal of Research, 69(1): 83-91. https://doi.org/10.1080/03772063.2021.1893231
[10] Chen, C.C., Chang, C.C., Lin, C.C., Su, G.D. (2019). TSIA: A novel image authentication scheme for AMBTC-based compressed images using turtle shell based reference matrix. IEEE Access, 7: 149515-149526. https://doi.org/10.1109/ACCESS.2019.2944833
[11] Dhole, V.S., Patil, N.N. (2015). Self embedding fragile watermarking for image tampering detection and image recovery using self recovery blocks. In 2015 International Conference on Computing Communication Control and Automation, Pune, India, pp. 752-757. https://doi.org/10.1109/ICCUBEA.2015.150
[12] Fridrich, J., Goljan, M. (1999). Images with self-correcting capabilities. In Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348), Kobe, Japan, pp. 792-796. https://doi.org/10.1109/ICIP.1999.817228
[13] Ghosal, S.K., Mandal, J.K. (2014). Binomial transform based fragile watermarking for image authentication. Journal of Information Security and Applications, 19(4-5): 272-281. https://doi.org/10.1016/j.jisa.2014.07.004
[14] Gul, E., Ozturk, S. (2019). A novel hash function based fragile watermarking method for image integrity. Multimedia Tools and Applications, 78: 17701-17718. https://doi.org/10.1007/s11042-018-7084-0
[15] Lee, T.Y., Lin, S.D. (2008). Dual watermark for image tamper detection and recovery. Pattern Recognition, 41(11): 3497-3506. https://doi.org/10.1016/j.patcog.2008.05.003
[16] Li, W., Lin, C.C., Pan, J.S. (2016). Novel image authentication scheme with fine image quality for BTC-based compressed images. Multimedia Tools and Applications, 75: 4771-4793. https://doi.org/10.1007/s11042-015-2502-z
[17] Lin, C.C., Huang, Y.H., Tai, W.L. (2014). A high-quality image authentication scheme for AMBTC-compressed images. KSII Transactions on Internet and Information Systems (TIIS), 8(12): 4588-4603. https://doi.org/10.3837/tiis.2014.12.020
[18] Lin, C.C., Huang, Y.H., Tai, W.L. (2017). A novel hybrid image authentication scheme based on absolute moment block truncation coding. Multimedia Tools and Applications, 76: 463-488. https://doi.org/10.1007/s11042-015-3059-6
[19] Ramakrishnan, S., Gopalakrishnan, T., Balasamy, K. (2011). A wavelet based hybrid SVD algorithm for digital image watermarking. Signal & Image Processing, 2(3): 157-174. https://doi.org/10.5121/sipij.2011.2313
[20] Qin, C., Wang, H.L., Zhang, X.P., Sun, X.M. (2016). Self-embedding fragile watermarking based on reference-data interleaving and adaptive selection of embedding mode. Information Sciences, 373: 233-250. https://doi.org/10.1016/j.ins.2016.09.001
[21] Qin, C., Ji, P., Zhang, X.P., Dong, J., Wang, J.W. (2017). Fragile image watermarking with pixel-wise recovery based on overlapping embedding strategy. Signal Processing, 138: 280-293. https://doi.org/10.1016/j.sigpro.2017.03.033
[22] Singh, D., Shivani, S., Agarwal, S. (2013). Self-embedding pixel wise fragile watermarking scheme for image authentication. Intelligent Interactive Technologies and Multimedia, 111-122. https://doi.org/10.1007/978-3-642-37463-0_10
[23] Su, G.D., Chang, C.C., Lin, C.C. (2019). High-precision authentication scheme based on matrix encoding for AMBTC-compressed images. Symmetry, 11(8): 996. https://doi.org/10.3390/sym11080996
[24] Yang, C.W., Shen, J.J. (2010). Recover the tampered image based on VQ indexing. Signal Processing, 90(1): 331-343. https://doi.org/10.1016/j.sigpro.2009.07.007
[25] Zhang, X.P., Wang, S.Z. (2008). Fragile watermarking with error-free restoration capability. IEEE Transactions on Multimedia, 10(8): 1490-1499. https://doi.org/10.1109/TMM.2008.2007334
[26] Zhang, X.P., Wang, S.Z., Feng, G.R. (2009). Fragile watermarking scheme with extensive content restoration capability. Digital Watermarking: 268-278. https://doi.org/10.1007/978-3-642-03688-0_24
[27] Zhang, X.P., Wang, S.Z., Qian, Z.X., Feng, G.R. (2010). Reference sharing mechanism for watermark self-embedding. IEEE Transactions on Image Processing, 20(2): 485-495. https://doi.org/10.1109/TIP.2010.2066981
[28] Zhang, H., Wang, C., Zhou, X. (2017). Fragile watermarking for image authentication using the characteristic of SVD. Algorithms, 10(1): 27. https://doi.org/10.3390/a10010027
[29] Zhu, X.Z., Ho, A.T., Marziliano, P. (2007). A new semi-fragile image watermarking with robust tampering restoration using irregular sampling. Signal Processing: Image Communication, 22(5): 515-528. https://doi.org/10.1016/j.image.2007.03.004
[30] Ahvanooey, M.T., Li, Q., Zhu, X.F., Alazab, M., Zhang, J. (2020). ANiTW: A novel intelligent text watermarking technique for forensic identification of spurious information on social media. Computers & Security, 90: 101702. https://doi.org/10.1016/j.cose.2019.101702
[31] Chen, T.H., Horng, G., Lee, W.B. (2005). A publicly verifiable copyright-proving scheme resistant to malicious attacks. IEEE Transactions on Industrial Electronics, 52(1): 327-334. https://doi.org/10.1109/TIE.2004.841083
[32] Chang, C.C., Lin, P.Y. (2008). Adaptive watermark mechanism for rightful ownership protection. Journal of Systems and Software, 81(7): 1118-1129. https://doi.org/10.1016/j.jss.2007.07.036
[33] Szyller, S., Atli, B.G., Marchal, S., Asokan, N. (2021). Dawn: Dynamic adversarial watermarking of neural networks. In Proceedings of the 29th ACM International Conference on Multimedia, pp. 4417-4425. https://doi.org/10.1145/3474085.3475591
[34] Lu, Z.M., Guo, S.Z. (2016). Lossless Information Hiding in Images. Syngress.
[35] Abdallah, M.S. Cho, Y.I. (2022). Virtual hairstyle service using GANs & segmentation mask (hairstyle transfer system). Electronics, 11(20): 3299. https://doi.org/10.3390/electronics11203299
[36] Hosny, K.M., Darwish, M.M., Fouda, M.M. (2021). New color image zero-watermarking using orthogonal multi-channel fractional-order legendre-fourier moments. IEEE Access, 9: 91209-91219. https://doi.org/10.1109/ACCESS.2021.3091614
[37] Farfoura, M.E., Horng, S.J., Wang, X. (2013). A novel blind reversible method for watermarking relational databases. Journal of the Chinese Institute of Engineers, 36(1): 87-97. https://doi.org/10.1080/02533839.2012.726041
[38] Mishra, A., Jain, A., Narwaria, M., Agarwal, C. (2011). An experimental study into objective quality assessment of watermarked images. In International Journal of Image Processing, 5(2): 199-219.
[39] Abdel-Aziz, B., Chouinard, J.Y. (2004). On perceptual quality of watermarked images – an experimental approach. Digital Watermarking, 277-288. https://doi.org/10.1007/978-3-540-24624-4_21
[40] Kutter, M., Petitcolas, F. (1999). Fair benchmark for image watermarking systems. In Proceedings of SPIE Conference on Security and Watermaking of Multimedia Contents, SPIE, 3657: 226-239. https://doi.org/10.1117/12.344672
[41] Cox, I.J., Miller, M.L. (2002). The first 50 years of electronic watermarking. EURASIP Journal on Advances in Signal Processing, 2002: 820936. https://doi.org/10.1155/S1110865702000525
[42] Abdallah, M.S., Cho, Y.I. (2022). Virtual hairstyle service using GANs & segmentation mask (hairstyle transfer system). Electronics, 11(20): 3299. https://doi.org/10.3390/electronics11203299
[43] Poonam, Arora, S.M. (2018). A DWT-SVD based robust digital watermarking for digital images. Procedia Computer Science, 132(C): 1441-1448. https://doi.org/10.1016/j.procs.2018.05.076
[44] Kadian, P., Arora, N., Arora, S.M. (2019). March. Performance evaluation of robust watermarking using DWT-SVD and RDWT-SVD. In 2019 6th International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, pp. 987-991. https://doi.org/10.1109/SPIN.2019.8711681
[45] Alattar, A.M. (2004). Reversible watermark using the difference expansion of a generalized integer transform. In IEEE Transactions on Image Processing, 13(8): 1147-1156. https://doi.org/10.1109/TIP.2004.828418
[46] Shih, F.Y., Wu, Y.T. (2005). Robust watermarking and compression for medical images based on genetic algorithms. Information Sciences, 175(3): 200-216. https://doi.org/10.1016/j.ins.2005.01.013
[47] Tai, W.L., Yeh, C.M., Chang, C.C. (2009). Reversible data hiding based on histogram modification of pixel differences. IEEE Transactions on Circuits and Systems for Video Technology, 19(6): 906-910. https://doi.org/10.1109/TCSVT.2009.2017409
[48] Yang, B., Schmucker, M., Funk, W., Busch, C., Sun, S. (2004). Integer DCT-based reversible watermarking for images using companding technique. In Security, Steganography, and Watermarking of Multimedia Contents VI, San Jose, California, USA, pp. 405-415. https://doi.org/10.1117/12.527216
[49] Wang, J.X., Ni, J.Q., Zhang, X., Shi, Y.Q. (2016). Rate and distortion optimization for reversible data hiding using multiple histogram shifting. IEEE Transactions on Cybernetics, 47(2): 315-326. https://doi.org/10.1109/TCYB.2015.2514110
[50] Shih, F.Y., Zhong, X. (2016). High-capacity multiple regions of interest watermarking for medical images. Information Sciences: An International Journal, 367(C): 648-659. https://doi.org/10.1016/j.ins.2016.07.015
