A Cryptographically Secure Image Steganography Scheme Based On Arduino Microcontrollers
Aqib Khan, P. Dhavakumar · 2024
In today’s digitally pervasive environment, safeguarding sensitive information concealed within images has become increasingly critical. Conventional steganographic techniques may prove inadequate against sophisticated detection algorithms and statistical analysis. To address this challenge, integrating a pseudo-random number generator with hardware based entropy sources into the channel selection process offers a dynamic and adaptive solution to enhance information hiding security in images. As machine learning techniques for steganography become more sophisticated, they often introduce significant computational overhead. These ML-based algorithms require extensive computational resources for training, inference, and analysis, leading to increased complexity in terms of both time and computational power. By capitalizing on the inherent randomness introduced by the watchdog timer’s RC oscillator in an arduino embedded microcontroller, we can amplify the unpredictability of channel selection during embedding. This paper proposes a novel hybrid model integrating Hardware Random Number Generators and Pseudo-Random Number Generators to augment entropy in the channel selection process within steganography. An examination of the performance of this hybrid model is presented.