DOI: https://doi.org/10.14710/jtsiskom.2021.13931

Alternatif otentikasi menggunakan metode steganografi histogram shifting

An authentication alternative using histogram shifting steganography method

1Department of Information System, Faculty of Computer Science, Universitas Jember, Jl. Kalimantan No. 37, Kampus Tegalboto, Jember 68121, Indonesia

2Department of Information Technology, Faculty of Computer Science, Universitas Jember, Jl. Kalimantan No. 37, Kampus Tegalboto, Jember 68121, Indonesia

3Department of Informatics, Faculty of Computer Science, Universitas Jember, Jl. Kalimantan No. 37, Kampus Tegalboto, Jember 68121, Indonesia

Received: 29 Sep 2020; Revised: 24 Jan 2021; Accepted: 26 Feb 2021; Available online: 20 Apr 2021; Published: 30 Apr 2021.
Open Access Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract
This study aims to develop an authentication alternative by applying the Histogram shifting steganography method. The media used for authentication is image media. Histogram shifting utilizes the histogram of an image to insert a secret message. The developed authentication has implemented the Histogram shifting to insert user credentials into the carrier image. Users can use the steganographic image to log into their accounts. The method extracts the credentials from the image during the login. PSNR test of the steganographic images produces an average value of 52.52 dB. The extraction capability test shows that the method can extract all test images correctly. In addition, this authentication method is also more resistant to attacks common to password authentication.
Fulltext View|Download Email colleagues
Keywords: authentication; steganography; histogram shifting; user credentials
Funding: Universitas Jember

Article Metrics:

Article Info
Section: Original Research Articles
Language : ID
Related articles
Carotid Artery Detection in B-Mode Ultrasound Images Based on Convolution Neural Network Single Shot Multibox Detector Flood Prediction with Ensemble Machine Learning using BP-NN and SVM Comparison of Document Plagiarism Detection Results by Jaro-Winkler Distance and Latent Semantic Analysis Methods Edge detection comparative analysis using Roberts, Sobel, Prewitt, and Canny methods Comparison analysis of Euclidean and Gower distance measures on k-medoids cluster More related articles
Most cited articles
Identification of Herbal Medicinal Plants Based on Leaf Image Using Gray Level Co-occurence Matrix and K-Nearest Neighbor Algorithms Parallel Spatial Pyramid Convolutional Neural Network for Kinship Verification from Face Images Location Based Service Panduan Pencarian Rumah Sakit dengan Platform Android di Kota Semarang Pengembangan Sistem Informasi Rekam Medis untuk Dinas Kabupaten Grobogan Parameter tuning in KNN for software defect prediction: an empirical analysis More cited articles
  1. S. W. Shah and S. S. Kanhere, “Recent trends in user authentication – A survey,” IEEE Access, vol. 7, no. 1, pp. 112505–112519, 2019. doi: 10.1109/ACCESS.2019.2932400
  2. S. Zulkarnain, S. Idrus, E. Cherrier, C. Rosenberger, and J.-J. Schwartzmann, “A review on authentication methods adaptive biometrics view project biblio view project,” Australian Journal of Basic and Applied Sciences, vol. 7, no. 5, pp. 95–107, 2013
  3. R. Wash, E. Rader, R. Berman, and Z. Wellmer, “Understanding password choices: how frequently entered passwords are re-used across websites,” in Twelfth Symposium on Usable Privacy and Security, Denver, USA, Jun. 2016, pp. 175–188
  4. D. Florencio and C. Herley, “A large-scale study of web password habits,” in International Conference on World Wide Web, New York, USA, May 2007, pp. 657–666. doi: 10.1145/1242572.1242661
  5. I. Cox, M. Miller, J. Bloom, J. Fridrich, and T. Kalker, Digital watermarking and steganography, 2nd Ed. New York: Morgan Kaufmann, 2008. doi: 10.1016/B978-012372585-1.50015-2
  6. S. Darmawan and I. Imelda, “Pengamanan dokumen menggunakan kriptografi rc4 dan steganografi eof dengan media video mp4 pada CV. Synergy Selaras,” Jurnal Teknologi Elektro, vol. 8, no. 2, pp. 117–122, 2017
  7. Y. Nurdiansyah and A. L. F. Riftana, “Implementasi steganografi citra digital pemberkasan arsip menggunakan metode least significant bit,” in Seminar Nasional Informatika dan Aplikasinya, Bandung, Indonesia, Sep. 2017, pp. 2–7
  8. M. K. Ridwan, W. F. Pattipeilohy, and S. Sanwani, “Aplikasi keamanan document digital menggunakan algoritma steganografi discrete cosine transform (DCT) pada perusahan alat berat,” JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer), vol. 5, no. 2, pp. 177–182, Feb. 2020. doi: 10.33480/jitk.v5i2.1033
  9. M. Syahril and H. Jaya, “Aplikasi steganografi pengamanan data nasabah di Standard Chartered Bank menggunakan metode Least Significant Bit dan RC4,” in Seminar Nasional Sains dan Teknologi Informasi, Medan, Indonesia, Jul. 2019, pp. 505–509
  10. M. Fikri and G. Guntoro, “Perancangan aplikasi single sign-on (SSO) menggunakan otentikasi gambar,” Jurnal Teknologi Informasi & Komunikasi Digital Zone, vol. 9, no. 1, pp. 12–21, 2018. doi: 10.31849/digitalzone.v9i1.648
  11. E. S. I. Harba, “Advanced password authentication protection by hybrid cryptography & audio steganography,” Iraqi Journal of Science, vol. 59, no. 1c, pp. 600–606, 2018. doi: 10.24996/ijs.2018.59.1C.17
  12. S. K. Sonker, S. Kumar, A. Kumar, and P. Singh, “Image based authentication using steganography technique,” International Journal of Advanced Research in Computer Science, vol. 4, no. 8, pp. 277–282, 2013
  13. Z. Ni, Y. Q. Shi, N. Ansari, and W. Su, “Reversible data hiding,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 16, no. 3, pp. 354–361, 2006. doi: 10.1109/TCSVT.2006.869964
  14. P. N. Andono, T. Sutojo, and M. Muljono, Pengolahan citra digital. Yogyakarta: Penerbit Andi, 2017
  15. A. Cheddad, J. Condell, K. Curran, and P. Mc Kevitt, “Digital image steganography: Survey and analysis of current methods,” Signal Processing, vol. 90, no. 3, pp. 727–752, 2010. doi: 10.1016/j.sigpro.2009.08.010
  16. X. Zhou, W. Gong, W. Fu, and L. Jin, “An improved method for LSB based color image steganography combined with cryptography,” in 15th International Conference on Computer and Information Science, Okayama, Japan, Jun. 2016, pp. 1–4. doi: 10.1109/ICIS.2016.7550955
  17. D. Gupta and M. Ahmad, “An efficient method to get improved peak signal to noise ratio (PSNR), using Support Vector Machine,” International Journal of Emerging Technology and Advanced Engineering, vol. 7, no. 9, pp. 49–53, 2017

Last update:

No citation recorded.

Last update: 2024-12-19 18:15:13

No citation recorded.