A Novel Distributed Image Steganography Method Based on Block-DCT

Koikara, Rosemary; Deka, Dip Jyoti; Gogoi, Mitali; Das, Rig

doi:10.1007/978-3-319-07674-4_42

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Distributed steganography [32,33] is an improvement of classical steganography which aims at fragmenting a secret and then hidden in several covert media, which makes it more difficult to detect the whole secret message. This is applied when there are various independent senders and only one recipient.…”

Section: Distributed Steganographymentioning

confidence: 99%

Distributed data hiding in multi-cloud storage environment

Metcheka

Ndoundam

2020

J Cloud Comp

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Classical or traditional steganography aims at hiding a secret in cover media such as text, image, audio, video or even in network protocols. Recent research has improved this approach called distributed steganography by fragmenting the secret message and embedding each secret piece into a distinct cover media. The major interest of this approach is to make the secret message detection extremely difficult. However, these file modifications leave fingerprints which can reveal a secret channel to an attacker. Our contribution is a new steganography paradigm transparent to any attacker and resistant to the detection and the secret extraction. Two properties contribute to achieve these goals: the files do not undergo any modification while the distribution of the secret in the multi-cloud storage environment allows us to hide the existence of the covert channel between the communicating parties. Information’s are usually hidden inside the cover media. In this work, the covert media is a pointer to information. Therefore the file carries the information without being modified and the only way to access it is to have the key. Experiments show interesting comparison results with remarkable security contributions. The work can be seen as a new open direction for further research in the field.

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Section: Distributed Steganographymentioning

confidence: 99%

Distributed data hiding in multi-cloud storage environment

Metcheka

Ndoundam

2020

J Cloud Comp

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“…Multi-cloud is a multiple public or private cloud service where data is stored and processed. Advantages: A single file fragmented and stored in multiple clouds, difficult to identify a single file, difficult to integrate all the blocks without key, It generates multiple stego-message of one secret code to make it difficult for an attacker and disadvantages: Monitoring multiple clouds for a single file, take high execution time [9,10]. In a recent survey, a public algorithm was proposed [11], where the receiver is one and communication channels are many to transfer the data.…”

Section: Introductionmentioning

confidence: 99%

Brute Force Attack on Distributed data Hiding in the Multi-Cloud Storage Environment More Diminutive than the Exponential Computations

Abdul¹,

Mohammad²,

Sastry³

et al. 2022

ISI

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Classical steganography is designed to hide data by cover media. Recent approaches fragmented the data and hide them in a distributed manner by embedding each fragmented data into a distinct cover media. This approach makes a secret message extremely difficult for an attacker to detect. However, cover media modification leaves fingerprints that could expose a secret channel to an attacker. To overcome the problem, a novel steganography concept designed by two technical contributions. I). cover media does not undergo any modification, i.e., the cover media act as a pointer to fragmented data. II). A secret message is stored in the multi-cloud storage environment. The approach claimed that it is computationally infeasible for an attacker to detect and extract the hidden message despite of having fully access to the accounts of the different clouds. In this paper, we analysed the security strength of the novel steganography concept and concluded that, attacker can get the secret value stored in multi-cloud storage environment using the brute force attacks more diminutive than exponential computations.

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