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Enhancing image steganalysis via integrated reinforcement learning and dilated convolution techniques

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Abstract

In the wake of unparalleled expansion in digital communication platforms, the imperative to bolster security and privacy measures has escalated. Within this landscape, image steganalysis emerges as a pivotal domain committed to detecting concealed information embedded in image files. This academic article unveils a novel image steganalysis model, melding dilated convolutional methodologies with a state-of-the-art mutual learning-based artificial bee colony (ML-ABC) approach and reinforcement learning (RL). The architecture operates a consortium of convolutional neural networks, collaboratively deriving features. After derivation, these features are combined to simplify the subsequent classification task. A reinforcement learning-focused (RL-focused) algorithm is employed to address the challenges posed by uneven datasets. The learning path is conceived as a series of linked decision points, with each instance representing a unique state. The network acts as an agent, earning rewards or suffering consequences according to its ability to distinguish between less frequent and more frequent classes. To commence the initial weight training, a methodology grounded in ML-ABC is implemented. This tactic adeptly adjusts the optimal food source for solution candidates, intertwining elements of mutual learning tied to the initial weights. The efficacy of the model is rigorously evaluated utilizing the BossBase 1.01 and BOWS datasets. Thorough experimentation is conducted on the selected dataset, with the objective of identifying optimal parameter values, including the reward mechanism. Subsequent results prominently highlight the superiority of our proposed solution compared to alternative methods explored within this research.

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Funding

This work was supported by the Higher Vocational Education Reform Project of Henan Province (No 2021SJGLX755).

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  1. School of Mathematics and Information Engineering, Puyang Vocational and Technical College, Puyang, 457000, Henan, China

    Yuan Sun

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Yuan Sun: Writing-Original draft preparation, Conceptualization, Supervision, Project administration.

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Correspondence to Yuan Sun.

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Sun, Y. Enhancing image steganalysis via integrated reinforcement learning and dilated convolution techniques. SIViP (2024). https://doi.org/10.1007/s11760-024-03113-4

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