Open Access

REVIEW

Steganography in IoT Applications: A Survey on Methods, Current Emerging Challenges, and Future Directions

Rafif Aydin Ahmad¹, Ntivuguruzwa Jean De La Croix^2,3, Reynandriel Pramas Thandya¹, Tohari Ahmad^1,*, Kambombo Mtonga⁴, Mungwarakarama Irenee²

1 Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
2 Faculty of Computing and Information Sciences, University of Lay Adventists of Kigali (UNILAK), Kigali, Rwanda
3 Department of Technology and Innovation, SecureAI Labs, Kigali, Rwanda
4 School of Science and Technology, Malawi University of Business and Applied Sciences, Blantyre, Malawi

* Corresponding Author: Tohari Ahmad. Email:

Computers, Materials & Continua 2026, 89(2), 7 https://doi.org/10.32604/cmc.2026.083445

Received 03 April 2026; Accepted 15 July 2026; Issue published 15 September 2026

Abstract

The Internet of Things (IoT) enables seamless interconnectivity among billions of smart devices, transforming industries through real-time sensing, data processing, and intelligent decision-making. As IoT systems manage large volumes of sensitive data, ensuring secure and covert communication has become critical. Steganography, which conceals confidential information within ordinary transmissions, has emerged as a promising approach to strengthen security and privacy in IoT environments. However, despite the growing body of work, existing surveys often address steganography in general contexts without systematically analyzing its adaptation to the unique constraints of IoT systems. This article addresses this gap by providing a comprehensive study of steganographic techniques specifically designed for IoT, covering foundational principles, recent advancements, and performance metrics across diverse application domains. The review finds that image-based steganography remains the dominant paradigm, with hybrid cryptographic-steganographic methods accounting for the majority of recent proposals, while coverless and lightweight cryptographic approaches demonstrate the strongest potential for resource-constrained deployments. A recurring finding across the surveyed literature is the critical lack of standardized evaluation benchmarks and publicly available IoT-specific datasets, which significantly hinders reproducibility and cross-study comparison. This article also examines device constraints and their implications for steganographic design, while highlighting key research trends, unresolved challenges, and future directions toward efficient, adaptive, secure, and scalable steganography in next-generation IoT networks.

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Keywords

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