DeepStego: Privacy-Preserving Natural Language Steganography Using Large Language Models and Advanced Neural Architectures
Kuznetsov O. Chernov K. Shaikhanova A. Iklassova K. Kozhakhmetova D.
May 2025Multidisciplinary Digital Publishing Institute (MDPI)
Computers
2025#14Issue 5
Modern linguistic steganography faces the fundamental challenge of balancing embedding capacity with detection resistance, particularly against advanced AI-based steganalysis. This paper presents DeepStego, a novel steganographic system leveraging GPT-4-omni’s language modeling capabilities for secure information hiding in text. Our approach combines dynamic synonym generation with semantic-aware embedding to achieve superior detection resistance while maintaining text naturalness. Through comprehensive experimentation, DeepStego demonstrates significantly lower detection rates compared to existing methods across multiple state-of-the-art steganalysis techniques. DeepStego supports higher embedding capacities while maintaining strong detection resistance and semantic coherence. The system shows superior scalability compared to existing methods. Our evaluation demonstrates perfect message recovery accuracy and significant improvements in text quality preservation compared to competing approaches. These results establish DeepStego as a significant advancement in practical steganographic applications, particularly suitable for scenarios requiring secure covert communication with high embedding capacity.
covert communication , cybersecurity , deep learning , GPT models , information hiding , linguistic steganography , natural language processing , semantic embedding , steganalysis resistance , text generation
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Department of Theoretical and Applied Sciences, eCampus University, Via Isimbardi 10, Novedrate, 22060, Italy
Department of Intelligent Software Systems and Technologies, School of Computer Science and Artificial Intelligence, Karazin Kharkiv National University, 4 Svobody Sq., V. N, Kharkiv, 61022, Ukraine
Department of Information Security, L.N. Gumilyov Eurasian National University, Satpayev 2, Astana, 010008, Kazakhstan
Department of Information and Communication Technologies, Manash Kozybayev North Kazakhstan University, Pushkin Str., 86, Petropavlovsk, 150000, Kazakhstan
Higher School of Artificial Intelligence and Construction, Shakarim University, St. Glinka, 20A, Semey, 071412, Kazakhstan
Department of Theoretical and Applied Sciences
Department of Intelligent Software Systems and Technologies
Department of Information Security
Department of Information and Communication Technologies
Higher School of Artificial Intelligence and Construction
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