An enhanced security and prediction of image steganography using ANFIS classification

• Published in: Hybrid and Advanced Technologies Vol. 2; pp. 15 - 24
• Main Authors: Patel, Maitri, Shah, Parita V., Oza, Alpa K., Dalvadi, Darshna
• Format: Book Chapter
• Language: English
• Published: United Kingdom CRC Press 2025; Taylor & Francis Group
• Edition: 1
• Subjects: ANFIS classifier and Steganalysis; BOSS database; Steganography; Data Security
• ISBN: 9781032906690; 9781032906720; 1032906693; 1032906723
• DOI: 10.1201/9781003559139-2

Every organization's worth is its information, and as information is now disseminated via digital media including the internet, securing this resource has become crucial for all businesses. The degree and the standard of security are constantly our top concerns, regardless of the security technology we utilize. Steganography is a method that makes it difficult to determine whether a secret message is there. It could be used as a security tool to transfer sensitive data securely. In addition to providing an overview, the significance, and the difficulties of steganography techniques, the goal of this study is to categorize several picture steganography approaches. The information was concealed using three well-known steganographic algorithms: BP-NN, K-NN, Fuzzy based, and ANFIS at two density levels. The data were photos from the BOSS database. The ANFIS algorithm was able to recognize objects with a 99.9% accuracy rate, which is almost flawless. The classification of steganography techniques may offer scholars in this subject not only comprehension and guidance, but also pointers for future study in this field.