With the rapid expansion of digital communication networks, protecting sensitive information against interception, traffic analysis, and cyber surveillance has become increasingly challenging. While cryptography secures the content of messages, it does not hide the existence of communication, making encrypted traffic vulnerable to detection and blocking. Network steganography addresses this limitation by embedding secret data into legitimate network traffic using covert channels. However, most existing network steganography techniques rely on single layer hiding mechanisms, which suffer from limited bandwidth, low robustness, and high detectability under modern intrusion detection systems. This paper proposes a multi-layer network steganography framework that integrates ICMP-based covert channels with NTFS Alternative Data Streams (ADS) to significantly enhance capacity, security, and stealth. The proposed approach hides secret files and messages inside ADS at the file-system level and then encapsulates the ADS-based payload within ICMP packets at the network level, forming a hierarchical covert communication architecture. This layered model is inspired by multi-layer steganography principles and onion-routing-style security, where each layer provides an additional level of protection. Experimental analysis demonstrates that the proposed multi-layer framework achieves higher hidden data capacity and stronger resistance to detection compared to conventional ICMP-based covert channels, while maintaining normal network behavior. The results confirm that combining file-system-level and network-level steganography offers a powerful mechanism for secure covert communication in modern networks.

This paper presented a multi-layer network steganography framework that integrates NTFS Alternative Data Streams (ADS) with ICMP-based covert channels to provide a secure, high-capacity, and stealthy method for hidden communication. By combining file-system-level hiding and network-level hiding, the proposed architecture introduces two independent layers of protection, making detection, extraction, and forensic reconstruction significantly more difficult than in traditional single-layer covert channels. Even if one layer is compromised, the second layer continues to conceal the hidden information, reflecting a defense-in-depth and onion-style security architecture. The proposed model demonstrated superior performance in terms of capacity, robustness, and resistance to detection. ADS allows large volumes of data to be hidden without altering the observable properties of files, while ICMP provides a legitimate and widely accepted transport mechanism that blends naturally into network traffic. This dual-layer strategy reduces the statistical footprint of the covert channel, increases resilience against packet loss and traffic normalization, and enhances the overall stealth of the communication. As a result, the framework is well suited for applications in secure communications, cyber defense, covert data exchange, and digital forensics research. Future extensions of this work will focus on expanding the multi-layer framework to additional network protocols such as TCP, DNS, and HTTPS, enabling covert communication over encrypted and high-volume application traffic. Furthermore, integrating cryptographic protection within the ADS layer will provide confidentiality and integrity even in the event of partial exposure. Additional research will also explore adaptive and intelligent embedding strategies, using machine learning to dynamically optimize protocol selection and embedding behavior, further strengthening resistance against advanced network steganalysis techniques.

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