Triplets-Based Steganographic Scheme to Improve the Image Quality in Spatial Domain

• Published in: 2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC) pp. 1 - 5
• Main Authors: Meftah Mafazy, Muhammad, Terri Agustinus, Jeems, Ikhwanul Haq, Thoha, Jean De La Croix, Ntivuguruzwa, Ahmad, Tohari
• Format: Conference Proceeding
• Language: English
• Published: IEEE 04-12-2023
• Subjects: Computer security; data hiding; Digital images; Image quality; Machine learning; National Security; network infrastructure; Payloads; spatial domain; Steganography; Wireless communication
• DOI: 10.1109/ICMNWC60182.2023.10435875

Advances in information and communications technology have changed the way various sectors, from finance to the military, operate. However, this evolution has also increased cybersecurity threats, posing potential risks to user privacy and security. In response to these challenges, data masking methods have emerged as noteworthy solutions. These methods involve hiding information within other data, such as audio and video files, to add an extra layer of security. Retaining the quality of the stego image proves to be a primary challenge in steganography. In addressing the limitations of previous digital image steganography techniques, this research introduces a new algorithm centered on triplets. Our experiments using images from the SIPI dataset, our results showcase a notable improvement in performance, with signal-to-noise ratio (PSNR) results that vary from 43.080 dB to 65.564 dB. These experimental outcomes underscore a substantial enhancement compared to existing methods, affirming the efficacy of the proposed algorithm in bolstering cybersecurity defenses.