René Ndoundam

The exponential growth of cloud storage adoption has introduced new attack surfaces and privacy concerns, necessitating advanced methods for secure and covert communication. Traditional steganographic techniques, particularly in distributed settings, often struggle with balancing undetectability, embedding capacity, and security. Recent indirect methods that avoid file modification have improved undetectability but remain constrained by low capacity and reliance on cryptographic secrecy alone. This paper introduces Contextual Cloud Steganography (CCS), a novel framework that replaces traditional base-based encoding with contextual protocols based on deterministic file ordering within cloud directories. CCS leverages pre-established sorting criteria (e.g., cryptographic hashes, creation dates) to embed secret data by selecting files from sorted lists, achieving a multiplicative increase in capacity of 3.2× to 4.3× over state-of-the-art base-B methods. The framework simultaneously enhances security through protocol-dependent protection, making message extraction computationally infeasible without the precise contextual protocol, even if the stego-folder is discovered. We provide formal security proofs under established steganographic models, detailed algorithms with cryptographic enhancements, and extensive experimental evaluation across major cloud platforms (Google Drive, Dropbox, OneDrive) over a 30-day period. Results demonstrate CCS's practical efficiency and robustness in dynamic environments, establishing it as a significant advancement in cloud-based covert communication that breaks the traditional capacity-security trade-off.

The texts "only boats catch connotes ..." and "in the research area of text steganography ...." were not coloured in section 6 (Experimental Evaluation) as in the original manuscript.This article introduces a paradigm-shifting approach to text steganography that fundamentally redefines the capacity limits of covert communication through the synergistic integration of combinatorial color optimization and Huffman compression. By exploiting the combinatorial richness of the 24-bit RGB color space enhanced with lossless compression, we present a framework that achieves unprecedented embedding capabilities—reaching up to 400% effective capacity, representing a 17.9 × improvement over state-of-the-art permutation-based method (Sadie et al., 2023) for n = 10 colors. Our methodology combines optimal color subset selection from 16.7 million possibilities with hybrid combinatorial–permutational encoding and Huffman compression, creating exponential growth in steganographic potential while maintaining format compatibility with standard communication channels. Theoretical analysis confirms O ( ( 2 24 ) k n ) complexity scaling with only 12% compression overhead, while experimental validation demonstrates practical implementation achieving 350 to 400% capacity with only 5 to 8% cover text modification. The compression-enhanced scheme establishes new benchmarks for high-capacity steganography, offering robust security against statistical detection through dynamic palette selection, adaptive encoding strategies, and compression-induced entropy redistribution. This work represents a significant advancement in digital covert communication, providing a scalable, efficient solution for modern security requirements while enhancing both capacity and undetectability beyond existing text-based steganographic systems.

Text steganography is a mechanism of hiding secret text message inside another text as a covering message. In this paper, we propose a text steganographic scheme based on color coding. This includes two different methods: the first based on permutation, and the second based on numeration systems. Given a secret message and a cover text, the proposed schemes embed the secret message in the cover text by making it colored. The stego-text is then send to the receiver by mail. After experiments, the results obtained show that our models perform a better hiding process in terms of hiding capacity as compared to the scheme of Aruna Malik et al. on which our idea is based. La stéganographie textuelle est un mécanisme permettant de cacher un message secret dans un texte. Dans ce papier, nous proposons un schéma stéganographique basé sur le codage de couleurs. Ce schéma comprend deux méthodes différentes : la première, basée sur les permutations et la seconde, basée sur les systèmes de numération. Etant donné un message secret et un texte de couverture, les méthodes proposées cachent le message secret dans le texte de couverture en le coloriant. Le stégo-texte est ensuite envoyé au destinataire par mail. Après expérimentations, les résultats obtenus montrent que nos modèles proposent un meilleure capacité d'embarquement par rapport au schéma d'Aruna Malik et al. sur laquelle repose notre idée.

Many hierarchical methods for community detection in multicolored networks are capable of finding clusters when there are interslice correlation between layers. However, in general, they aggregate all the links in different layer treating them as being equivalent. Therefore, such aggregation might ignore the information about the relevance of a dimension in which the node is involved. In this paper we fill this gap by proposing a hierarchical classification based-Louvain method for interslice-multicolored networks. In particular we define a new node centrality measure named \textit{Attractivity} to describe the inter-slice correlation that incorporates within and across-dimension topological features in order to identify the relevant dimension. Then, after merging dimensions through a frequential aggregation, we group nodes by their relational and attribute similarity, where attributes correspond to their relevant dimensions. We conduct an extensive experimentation using seven real-world multicolored networks, which also includes comparison with state-of-the-art methods. Results show the significance of our proposed method in discovering relevant communities over multiple dimensions and highlight its ability in producing optimal covers with higher values of the multidimensional version of the modularity function.

Rather than directly embed the secret message in pixels of an image, the new concept of coverless image steganography hides a message in a cover image without modifying it, which significantly increases the resilience to image steganalysis tools. Existing high capacity coverless image steganography methods do not provide an efficient algorithm for rapidly generating the large number of possible hash sequences. Moreover, the sending of additional information generated during the hiding process and essential for extraction is not explicitly defined. In this paper, we propose WYSAWIS, a high capacity coverless image steganography approach. Given an image initially subdivided into blocks of size 4*4, we generate from each block an initial 15-bit hash sequence, then a set of all the combinations of this sequence. The latter constitutes the set of hash sequences of that block.To send a secret message, it is first subdivided into 15-bit segments,and each segment is mapped to a hash sequence of a block, whose position in the block determines the position of the message segment. All these positions called location information are sent using a distributed data hiding technique in a single cloud. Compared to what has been done in the literature before, our hashing algorithm makes it possible to use a single cover image to send a secret message of any size. This definitely overcomes the limits of building a large image data set and sending in order a large number of stego images. Moreover, the popularization of cloud services makes the transfer of location information innocuous and practical