covert communication by encoding data in the frequency domain of jpeg images.
Personal academic portfolio of Dr. Rakesh Kumar. Specializing in Robust JPEG Steganography, Multimedia Security, and content-adaptive embedding algorithms.
A PyQt6-based desktop application for evaluating robust JPEG steganography (Fixed-Grid QIM + RS ECC) against real-world social network platform (SNP) compression pipelines, featuring pure Python-native engines for MRAS and DRAS.
Official MATLAB implementation of DRAS (Downward Robust Adaptive Steganography), a framework designed to ensure hidden data reliability against JPEG downward recompression (JVCIR 2026).
Official MATLAB implementation of MRAS (Matching Robust Adaptive Steganography), a content-adaptive scheme robust against same QF recompression typical of social networking platforms (Signal Processing 2026).
Offline, client-side steganography and image forensics in one HTML file — encode, analyze and decode locally, with no uploads or server.
Browser-based J-UNIWARD JPEG steganography demo — Daubechies-8 wavelet cost, full STC (h=12, 4096-state Viterbi), PBKDF2+HKDF key schedule, adaptive payload embedding, live steganalysis comparison. No backends. No simulated math.
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