Comparative Stratification of Steganalysis Techniques to Interpret & Target Anomalies
Dhiren Dommeti, Siva Ramakrishna Nallapati, Venkata Vara Prasad Padyala, Venkata Naresh Mandhala · 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) · 2022
The art of detecting hidden messages in media is known as steganalysis. Statistically and visually data is hidden in the media. Using deep learning techniques is evidently favorable as they are efficient in learning hierarchical data. Through this research, we tend to investigate and compare various steganalysis techniques and implement classifiers to compare the results achieved. Neural networks, Clustering Algorithms, and other Tools are used to design a model for the investigation of Experimental Findings. Classifiers like the SVM classifier, K-NN classifier, Random Forests classifier, MLP NN classifier, and Naive Bayes classifier are trained and tested to detect images undergoing steganography. The results acquired are compared and analyzed.