IMPLEMENTASI PASSWORD-BASED SCRAMBLING DAN METODE LEAST SIGNIFICANT BIT (LSB) UNTUK AUTENTIKASI KEASLIAN CITRA DIGITAL
DOI:
https://doi.org/10.70248/jrsit.v4i1.4565Keywords:
Citra digital, Digital Watermarking, Password-Based Scrambling, Least Significant Bit, Fragile WatermarkingAbstract
Kemudahan distribusi citra dokumentasi melalui kanal digital meningkatkan risiko pengunggahan ulang tanpa identitas sumber serta manipulasi yang sulit dikenali secara visual. Kondisi tersebut menyebabkan penerima sulit memastikan apakah citra masih sama dengan citra yang pertama kali diterbitkan. Penelitian ini bertujuan menerapkan kombinasi Password-Based Scrambling dan Least Significant Bit (LSB) dengan pendekatan fragile watermarking untuk membantu autentikasi citra digital. Password diproses menggunakan SHA-256 untuk menghasilkan seed bagi pseudo-random number generator (PRNG). Urutan deterministik yang dihasilkan PRNG digunakan pada Fisher-Yates Shuffle untuk mengacak piksel watermark dan menentukan lokasi penyisipan pada kanal LSB. Pengujian dilakukan menggunakan 12 citra sampul RGB dan satu watermark grayscale berukuran 320 × 320 piksel pada kondisi tanpa manipulasi serta setelah kompresi JPEG, cropping, dan resizing. Proses penyisipan menghasilkan rata-rata MSE 0,0635, PSNR 62,78 dB, dan SSIM 0,9995, yang menunjukkan perubahan visual sangat kecil. Tanpa manipulasi, watermark berhasil direkonstruksi dengan BER 0 dan NC 1. Setelah manipulasi, rata-rata BER meningkat menjadi 0,4974 dan NC menurun menjadi 0,5941 sehingga watermark tidak dapat dikenali. Pada kompresi, PSNR tetap lebih dari 40 dB meskipun ekstraksi watermark gagal. Hasil tersebut menunjukkan bahwa sistem sensitif terhadap seluruh manipulasi yang diuji, tetapi belum dapat menentukan jenis dan lokasi manipulasi secara otomatis.
References
Aberna, P., & Agilandeeswari, L. (2024). Optimal semi-fragile watermarking based on maximum entropy random walk and Swin Transformer for tamper localization. IEEE Access, 12. https://doi.org/10.1109/ACCESS.2024.3370411
Aberna, P., & Agilandeeswari, L. (2025). PoWBWM: Proof of work consensus cryptographic blockchain-based adaptive watermarking system for tamper detection applications. Alexandria Engineering Journal, 112, 510–537. https://doi.org/10.1016/j.aej.2024.10.016
Aberna, P., & Agilandeeswari, L. (2026). A comprehensive review on fragile and semi-fragile based watermarking systems for content authentication and tamper detection applications: Open issues, challenges and future directions. Multimedia Tools and Applications, 85, 200. https://doi.org/10.1007/s11042-026-21290-x
Adi, P. W., Wibowo, A., Aryotejo, G., & Ernawan, F. (2023). Fragile watermarking for image authentication using dyadic Walsh ordering. International Journal of Advances in Intelligent Informatics, 9(3). https://doi.org/10.26555/ijain.v9i3.1017
Al Najjar, Y. (2024). Comparative analysis of image quality assessment metrics: MSE, PSNR, SSIM, and FSIM. International Journal of Science and Research, 13(3), 110–114. https://doi.org/10.21275/SR24302013533
Al-Otum, H. M., & Ellubani, A. A. A. (2022). Secure and effective color image tampering detection and self restoration using a dual watermarking approach. Optik, 262, 169280. https://doi.org/10.1016/j.ijleo.2022.169280
Alveda, A., Rakhmawati, L., Tjahyaningtijas, R. H. P. A., & Kartini, U. T. (2024). Penyisipan watermark menggunakan metode LSB untuk autentikasi citra medis. Jurnal Teknik Elektro, 13, 273–280. https://doi.org/10.26740/jte.v13n3.p273-280
Aminuddin, A., & Ernawan, F. (2022a). AuSR1: Authentication and self-recovery using a new image inpainting technique with LSB shifting in fragile image watermarking. Journal of King Saud University - Computer and Information Sciences, 34(8), 5822–5840. https://doi.org/10.1016/j.jksuci.2022.02.009
Aminuddin, A., & Ernawan, F. (2022b). AuSR2: Image watermarking technique for authentication and self-recovery with image texture preservation. Computers & Electrical Engineering, 102, 108207. https://doi.org/10.1016/j.compeleceng.2022.108207
Durstenfeld, R. (1964). Algorithm 235: Random permutation. Communications of the ACM, 7(7), 420. https://doi.org/10.1145/364520.364540
Ernawan, F., Adi, P. W., Liew, S. C., Sarwoko, E. A., & Winarno, E. (2022). Fast image watermarking based on signum of cosine matrix. Indonesian Journal of Electrical Engineering and Computer Science, 25(3), 1383–1391. https://doi.org/10.11591/ijeecs.v25.i3.pp1383-1391
Faheem, Z. B., Hanif, D., Arslan, F., Ali, M., Hussain, A., Ali, J., & Baz, A. (2023). An edge inspired image watermarking approach using compass edge detector and LSB in cybersecurity. Computers & Electrical Engineering, 111, 108979. https://doi.org/10.1016/j.compeleceng.2023.108979
Fauzi, I., & Khairani, M. (2025). Analisis perbandingan kapasitas penyisipan data dan kualitas citra dalam teknik steganografi LSB dan MSB. Jurnal Ilmu Komputer dan Sistem Informasi, 4, 344–355. https://doi.org/10.70340/jirsi.v4i3.236
Firmansyah, M. A., & Tahir, M. (2026). Integrasi algoritma SHA-256 dan AES untuk pengamanan kredensial dan data sensitif. Jurnal Komputer Teknologi Informasi Sistem Informasi, 5(1), 462–468. https://doi.org/10.62712/juktisi.v5i1.1032
Jana, M., Jana, B., & Joardar, S. (2022). Local feature based self-embedding fragile watermarking scheme for tampered detection and recovery utilizing AMBTC with fuzzy logic. Journal of King Saud University - Computer and Information Sciences, 34. https://doi.org/10.1016/j.jksuci.2021.12.011
Kosuru, S. N. V. J. D., Swain, G., Kumar, N., & Pradhan, A. (2022). Image tamper detection and correction using Merkle tree and remainder value differencing. Optik, 261, 169212. https://doi.org/10.1016/j.ijleo.2022.169212
Makhrib, Z. F., & Karim, A. A. (2022). A hybrid digital image watermarking by using DWT and LSB method. Iraqi Journal of Computers, Communications, Control and Systems Engineering, 22(4), 115–126. https://doi.org/10.33103/uot.ijccce.22.4.9
Ma, K., Teng, L., Wang, X., & Meng, J. (2021). Color image encryption scheme based on the combination of the Fisher-Yates scrambling algorithm and chaos theory. Multimedia Tools and Applications, 80, 24737–24757. https://doi.org/10.1007/s11042-021-10847-7
Maulid, E., Pradana, A. N., & Kurniawan, R. (2026). Perbandingan metode watermarking Singular Value Decomposition dan Discrete Wavelet Transform untuk perlindungan hak cipta. Jurnal Sentinel, 6(1), 648–654. https://doi.org/10.56622/sentineljournal.v6i1.64
Neena Raj, N. R., & Shreelekshmi, R. (2022). Fragile watermarking scheme for tamper localization in images using logistic map and singular value decomposition. Journal of Visual Communication and Image Representation, 85, 103500. https://doi.org/10.1016/j.jvcir.2022.103500
Ouyang, J., Huang, J., & Wen, X. (2023). A semi-fragile reversible watermarking method based on QDFT and tamper ranking. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-023-16963-w
Permana, F. R., Setiyanto, R. F., & Fauzi, A. R. (2023). Image steganography dengan menggunakan metode LSB pada Python. Jurnal Pendidikan Teknologi Informasi, 2(1), 1–7.
Purba, B., Dalimunthe, Y. A., Hasnita, U., & Putra, P. H. (2025). Teknik keamanan multimedia menerapkan metode Least Significant Bit untuk watermarking citra digital. Journal Global Tecnology Computer, 4(2), 139–149. https://doi.org/10.47065/jogtc.v4i2.7325
Putra, I. P. K., & Supriana, I. W. (2024). Analisis perbandingan kualitas citra hasil steganografi DCT dan LSB berdasarkan parameter RMSE dan PSNR. Jurnal Nasional Teknologi Informasi dan Aplikasinya, 2, 609–616. https://doi.org/10.24843/JNATIA.2024.v02.i03.p20
Rezaei, M., & Taheri, H. (2022). Digital image self-recovery using CNN networks. Optik, 264, 169345. https://doi.org/10.1016/j.ijleo.2022.169345
Senol, A., Elbasi, E., Topcu, A. E., & Mostafa, N. (2023). A semi-fragile, inner-outer block-based watermarking method using scrambling and frequency domain algorithms. Electronics, 12(4), 1065. https://doi.org/10.3390/electronics12041065
Setiawati, I., Hermanto, M. T., & Ujianto, E. I. H. (2023). Implementation of digital watermarking on images using the Least Significant Bit method. International Journal of Engineering, Technology and Natural Sciences, 5(1), 10–18. https://doi.org/10.46923/ijets.v5i1.191
Sharma, S., Zou, J. J., & Fang, G. (2022). A novel multipurpose watermarking scheme capable of protecting and authenticating images with tamper detection and localisation abilities. IEEE Access, 10, 85677–85700. https://doi.org/10.1109/ACCESS.2022.3198963
Sharma, S., Zou, J. J., Fang, G., Shukla, P., & Cai, W. (2024). A review of image watermarking for identity protection and verification. Multimedia Tools and Applications, 83, 31829–31891. https://doi.org/10.1007/s11042-023-16843-3
Simangunsong, V., Hutasoit, Y. R., & Siallagan, D. (2025). Analisis terhadap keamanan password menggunakan hash SHA-256. Jurnal Quancom, 3(1). https://doi.org/10.62375/jqc.v3i1.431
Singh, B., & Kasana, G. (2024). A review of digital watermarking techniques: Current trends, challenges and opportunities. Web Intelligence, 22. https://doi.org/10.3233/WEB-230280
Tran, D. N., Zepernick, H.-J., & Chu, T. M. C. (2022). LSB data hiding in digital media: A survey. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 9(30). https://doi.org/10.4108/eai.5-4-2022.173783
Vaidya, S. P., Kandala, R. N. V. P. S., Mouli, P. V. S. S. R. C., Zaini, H. G., Jaffar, A., Paramasivam, P., & Ghoneim, S. S. M. (2025). A robust fragile watermarking approach for image tampering detection and restoration utilizing hybrid transforms. Scientific Reports, 15, 17645. https://doi.org/10.1038/s41598-025-01297-4
Wan, W., Wang, J., Zhang, Y., Li, J., Yu, H., & Sun, J. (2022). A comprehensive survey on robust image watermarking. Neurocomputing, 488, 226–247. https://doi.org/10.1016/j.neucom.2022.02.083
Yacoub, M. H., Fetteha, M. A., Sharobim, B. K., & Zayed, H. H. (2023). Semi-fragile watermark for the authentication and recovery of tampered images. Proceedings of the 5th Novel Intelligent and Leading Emerging Sciences Conference, 194–199. https://doi.org/10.1109/NILES59815.2023.10296710
Yuan, Z., Zhang, X., Wang, Z., & Yin, Z. (2024). Semi-fragile neural network watermarking for content authentication and tampering localization. Expert Systems with Applications, 238, 121315. https://doi.org/10.1016/j.eswa.2023.121315
