This is a dataset consisting of 8 features extracted from 70,000 monochromatic still images adapted from the Genome Project Standford's database, that are labeled in two classes: LSB steganography (1) and without LSB Steganography (0). These features are Kurtosis, Skewness, Standard Deviation, Range, Median, Geometric Mean, Hjorth Mobility, and Hjorth Complexity, all extracted from the histograms of the still images, including random spatial transformations. The steganographic function embeds five types of payloads, from 0.1 to 0.5.

Dataset Files

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[1] Julian Miranda, "Steganalysis for still images with LSB Steganography - Features dataset", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/gs67-yn65. Accessed: Apr. 24, 2024.
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doi = {10.21227/gs67-yn65},
url = {http://dx.doi.org/10.21227/gs67-yn65},
author = {Julian Miranda },
publisher = {IEEE Dataport},
title = {Steganalysis for still images with LSB Steganography - Features dataset},
year = {2019} }
TY - DATA
T1 - Steganalysis for still images with LSB Steganography - Features dataset
AU - Julian Miranda
PY - 2019
PB - IEEE Dataport
UR - 10.21227/gs67-yn65
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Julian Miranda. (2019). Steganalysis for still images with LSB Steganography - Features dataset. IEEE Dataport. http://dx.doi.org/10.21227/gs67-yn65
Julian Miranda, 2019. Steganalysis for still images with LSB Steganography - Features dataset. Available at: http://dx.doi.org/10.21227/gs67-yn65.
Julian Miranda. (2019). "Steganalysis for still images with LSB Steganography - Features dataset." Web.
1. Julian Miranda. Steganalysis for still images with LSB Steganography - Features dataset [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/gs67-yn65
Julian Miranda. "Steganalysis for still images with LSB Steganography - Features dataset." doi: 10.21227/gs67-yn65