{'fraction_non_alphanumeric': 0.01303538175046555, 'fraction_numerical': 0.0, 'mean_word_length': 5.398809523809524, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Steganalysis of overlapping images

We examine whether steganographic images can be detected more reliably when there exist other images, taken with the same camera under the same conditions, of the same scene. We argue that such a circumstance is realistic and likely in practice. In `laboratory conditions' mimicking circumstances favourable to the analyst, and with a custom set of digital images which capture the same scenes with controlled amounts of overlap, we use an overlapping reference image to calibrate steganographic features of the image under analysis. Experimental results show that the analysed image can be classified as cover or stego with much greater reliability than traditional steganalysis not exploiting overlapping content, and the improvement in reliability depends on the amount of overlap. These results are curious because two different photographs of exactly the same scene, taken only a few seconds apart with a fixed camera and settings, typically have steganographic features that differ by considerably more than a cover and stego image.