Abstract
This paper introduces a novel steganography method for embedding and extracting a secret message from an image file using three stages. In the first stage, Binary Robust Invariant Scalable Keypoints (BRISK) and Good Features to Track are utilized to identify keypoints in the image. In the second stage, the k-means clustering algorithm is applied to these identified keypoints. The keypoints derived from the good features to track algorithm serve as cluster centers while the keypoints from the BRISK algorithm are distributed around these centers. In the last stage, the logistic map algorithm is employed to add more randomness to the obtained keypoints. This is done by distributing the points using the random list property. The results obtained indicate that the proposed method surpasses comparable techniques in terms of PSNR (Peak Signal-to-Noise Ratio), SSIM (Structural Similarity Index), and BER (Bit Error Rate) values metrics. Thus, the proposed scheme offers a performance advantage over existing methodologies.
Contributing authors—K.B. Salah, M. Kherallah and M.S. Naceur.
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References
Laimeche, L., Meraoumia, A., Bendjenna, H.: Enhancing LSB embedding schemes using chaotic maps systems. Neural Comput. Appl. 32, 16605–16623 (2020)
Jayapandiyan, J.R., Kavitha, C., Sakthivel, K.: Enhanced least significant bit replacement algorithm in spatial domain of steganography using character sequence optimization. IEEE Access 8, 136537–136545 (2020)
Leutenegger, S., Chli, M., Siegwart, R.Y.: BRISK: binary robust invariant scalable keypoints. In: 2011 International Conference on Computer Vision. IEEE (2011)
Mukherjee (Ganguly), N., Paul, G., Saha, S.K.: An efficient multi-bit steganography algorithm in spatial domain with two-layer security. Multimedia Tools Appl. 77(14), 18451–18481 (2018). https://doi.org/10.1007/s11042-018-5720-3
Ahmed, A., Ahmed, A.: A secure image steganography using LSB and double XOR operations. Int. J. Comput. Sci. Netw. Secur. 20(5), 139–144 (2020)
Prasad, S., Pal, A.K.: Logistic map-based image steganography scheme using combined LSB and PVD for security enhancement. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds.) Emerging Technologies in Data Mining and Information Security, pp. 203–214. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-1501-5_17
Hureib, E.S.B., Gutub, A.A.: Enhancing medical data security via combining elliptic curve cryptography with 1-LSB and 2-LSB image steganography. Int. J. Comput. Sci. Netw. Secur. (IJCSNS) 20(12), 232–241 (2020)
Swain, G.: Very high capacity image steganography technique using quotient value differencing and LSB substitution. Arab. J. Sci. Eng. 44(4), 2995–3004 (2019)
Pak, C., et al.: A novel color image LSB steganography using improved 1D chaotic map. Multimedia Tools Appl. 79(1), 1409–1425 (2020)
Nazari, M., Mehrabian, M.: A novel chaotic IWT-LSB blind watermarking approach with flexible capacity for secure transmission of authenticated medical images. Multimedia Tools and Appl. 80(7), 10615–10655 (2021)
Nevriyanto, A., et al.: Image steganography using combine of discrete wavelet transform and singular value decomposition for more robustness and higher peak signal noise ratio. In: 2018 International Conference on Electrical Engineering and Computer Science (ICECOS). IEEE (2018)
Yi, X., Yang, K., Zhao, X., Wang, Y., Yu, H.: AHCM: adaptive Huffman code mapping for audio steganography based on psychoacoustic model. IEEE Trans. Inf. Forensics Secur. 14(8), 2217–2231 (2019). https://doi.org/10.1109/TIFS.2019.2895200
Bikku, T., Paturi, R.: Frequency domain steganography with reversible texture combination. Traitement du Signal 36(1), 109–117 (2019)
Burie, J.-C., Ogier, J.-M., Loc, C.V.: A spatial domain steganography for grayscale documents using pattern recognition techniques. In: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), vol. 9, p. 100. IEEE (2017)
Soleymani, S.H., Taherinia, A.H.: High capacity image steganography on sparse message of scanned document image (SMSDI). Multimedia Tools Appl. 76, 20847–20867 (2017)
Lin, I.-C., Lin, Y.-B., Wang, C.-M.: Hiding data in spatial domain images with distortion tolerance. Comput. Stand. Interfaces 31(2), 458–464 (2009)
Fourati, J., Othmani, M., Ltifi, H.: A hybrid model based on bidirectional long-short term memory and support vector machine for rest tremor classification. SIViP 16, 2175–2182 (2022). https://doi.org/10.1007/s11760-022-02180-9
Ben Salah, K., Othmani, M., Kherallah, M.: Long short-term memory based photoplethysmography biometric authentication. In: Badica, C., Treur, J., Benslimane, D., Hnatkowska, B., Krotkiewicz, M. (eds.) ICCCI 2022. CCIS, vol. 1653, pp. 554–563. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-16210-7_45
Ben Salah, K., Othmani, M., Kherallah, M.: Contactless heart rate estimation from facial video using skin detection and multi-resolution analysis. In: WSCG (2021). http://dx.doi.org/10.24132/CSRN.2021.3002.31
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Azooz, H.J., Ben Salah, K., Kherallah, M., Naceur, M.S. (2024). A Novel Steganography Scheme Using Logistic Map, BRISK Descriptor, and K-Means Clustering. In: Yan, W.Q., Nguyen, M., Nand, P., Li, X. (eds) Image and Video Technology. PSIVT 2023. Lecture Notes in Computer Science, vol 14403. Springer, Singapore. https://doi.org/10.1007/978-981-97-0376-0_28
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