Abstract
Steganalysis Algorithm for PNG Images Based on Fuzzy Logic Technique
Highlights
In recent years, the rapid advancements in technologies and communication have generated an increase in the number of cyber-crimes cases
The proposed system for detection is depend on extracting a set of image features from stego and clean images and using fuzzy logic and neural network techniques to distinguish between clean an stego images
As it known about fuzzy logic that it is more accurate methods of artificial intelligence techniques, successive tests have proved that the detection ratio of the clean images and the stego images increased respectively to the increased in the number of images and features
Summary
The rapid advancements in technologies and communication have generated an increase in the number of cyber-crimes cases. The biggest obstacle facing digital forensic examiners is the analysis and identification of hidden data in digital media (images, audio and video). Hiding information refers to the process of inserting and embedding information in digital content, such as, image, audio or video, without drawing attention to the change. This process is called Steganography, while trying to detect the hidden information is called steganalysis. Every day there is a new steganography tool to hide data; steganalysis algorithms have difficulty in detecting the hidden data because the majority of it is based on rule-based techniques. We conclude that the fuzzy logic system accomplished high performance in terms of classifying the clean and stego images in PNG images
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