Authentication of Exam Papers Using Steganography Techniques and Optimization Using Meta-Heuristic Algorithms
Keywords:
Authentication of exam papers, Stealth technique, Optimization, Meta-heuristic algorithmsAbstract
The primary objective of this study is to design an efficient steganography method for the authentication of exam papers, ensuring that the original image quality is maximally preserved with the least amount of distortion. This study proposes a three-stage image steganography method that combines optimization, steganography, and frequency-domain transforms. To prevent the degradation of sensitive regions, data embedding is avoided in edges and corners. Instead, high-energy regions without edges or corners are extracted and selected. The proposed framework utilizes the Wavelet transform, Discrete Cosine Transform (DCT), Huffman coding, and the African Vultures Optimization Algorithm (AVOA). The simulations were conducted in the MATLAB environment, and the performance of the proposed method was evaluated against three baseline schemes. The evaluation results demonstrated that the proposed method significantly improved image steganography quality by achieving minimum Mean Squared Error (MSE) values. Compared to the three baseline methods, the proposed approach showed an MSE improvement of 3% to 4% for the first test image, 25% to 39% for the second image, and 3% to 25% for the third image. Across all three tested images, the proposed method consistently yielded better MSE outcomes than the baseline schemes. The integration of the Wavelet transform, AVOA optimization, and Huffman coding provides a secure and highly effective steganographic solution for exam paper authentication and intellectual property protection, proving superior to existing approaches by significantly reducing errors and preserving visual quality.
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