AI Based Framework for Bridging the Cyber Security Techniques with Digital Steganography
Anurag Shrivastava, RVS Praveen, Layth Hussein, Saloni Bansal, P. William, Apurv Verma
Abstract
In the digital era, safeguarding information has become paramount due to the growing sophistication of cyber threats. Traditional encryption methods sometimes fall short, necessitating innovative approaches like steganography, which conceals the existence of the data itself. This paper analyzes existing cybersecurity techniques used in steganography, including both steganographic methods and steganalysis. It explores spatial domain techniques like Least Significant Bit (LSB) insertion, transform domain techniques such as Discrete Cosine Transform (DCT), and adaptive methods, alongside steganalysis methods involving statistical analysis and machine learning. The research methodology includes evaluating embedding efficiency, security levels, and resilience against detection. The findings highlight the strengths and weaknesses of various techniques, emphasizing the need for a balanced approach tailored to specific security requirements. This comprehensive analysis aims to enhance the understanding and effectiveness of steganography in protecting sensitive information in the digital landscape.