Hiding Sound in Image by K-LSB Mutation
Ankur Gupta, Ankit Chaudhary

TL;DR
This paper introduces a method for embedding sound data into images using k-LSB mutation, minimizing visual distortion and employing Cuckoo Search for efficient optimization.
Contribution
It presents a novel sound hiding technique in images utilizing k-LSB mutation combined with Cuckoo Search for optimal embedding, enhancing concealment and efficiency.
Findings
Effective sound hiding with minimal image distortion
Cuckoo Search accelerates the optimization process
Embedding process remains covert and robust
Abstract
In this paper a novel approach to hide sound files in a digital image is proposed and implemented such that it becomes difficult to conclude about the existence of the hidden data inside the image. In this approach, we utilize the rightmost k-LSB of pixels in an image to embed MP3 sound bits into a pixel. The pixels are so chosen that the distortion in image would be minimized due to embedding. This requires comparing all the possible permutations of pixel values, which may would lead to exponential time computation. To speed up this, Cuckoo Search (CS) could be used to find the most optimal solution. The advantage of using proposed CS is that it is easy to implement and is very effective at converging in relatively less iterations/generations.
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Taxonomy
TopicsAdvanced Steganography and Watermarking Techniques · Digital Media Forensic Detection · Chaos-based Image/Signal Encryption
