STEGANIFY
STEGANO ANALYSIS USING CAPSULE NETWORK IN AIML
Created on 7th May 2023
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STEGANIFY
STEGANO ANALYSIS USING CAPSULE NETWORK IN AIML
The problem STEGANIFY solves
The issue of finding hidden or secret messages that are encoded in digital material, such as photographs, videos, or audio files, is solved via steganography analysis.
Using steganalysis techniques for analyzing digital media enables detecting and extracting any hidden information, which can be crucial in identifying criminal activity or cyber-attacks. By finding flaws in current approaches and reinforcing them, steganalysis can also be utilized to create more secure steganographic procedures.
Challenges we ran into
For Capsule Networks to learn the steganography patterns, a substantial amount of labeled training data is needed. However, because steganography is a very secretive technique and there are so few publicly available datasets for steganalysis, there is a restricted availability of labeled data for steganalysis.
We decided to build the Stegano Analysis using capsule networking, which has an inbuilt security system that is challenging to crack due to confusion created within the source data, because the integration of security networking, telegram bot source code, and steganography source code were really difficult to overcome separately.
Tracks Applied (1)