Lightweight Noise Resilient Steganography Scheme for Internet of Things

Djebbar, Fatiha; Ali, Najah Abu

doi:10.1109/glocom.2017.8255039

Cited by 12 publications

(22 citation statements)

References 11 publications

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“…A key observation of this method is the high Bit Error Rate (BER), which reached 21% when 25 bins were modified per frame. In contrast, the methods proposed in [16], [17], [22] and [31] achieved high embedding rates. These methods used thresholding criteria that avoided embedding at low frequencies, while in the selected frequencies, explicit layers of the Least Significant Bit (LSB) in each phase were exploited to hide the secret message.…”

Section: Related Workmentioning

confidence: 85%

“…In [16] and [17], the BER was not measured at high embedding rates. However, in [22], the BER was around 0% against 10 dB of SNR after white Gaussian noise addition. The contradictory BER results in [19] and [22] combined reveal a research-worthy issue.…”

Section: Related Workmentioning

confidence: 93%

“…Phase coding methods have achieved high robustness and variable transparency levels, leading to a low embedding capacity. In phase coding, the maximum embedding rate when transparency and robustness are measured is 24 kbps at 32 dB, achieved by the method proposed in [22]. However, even such an embedding rate is considered low when compared to the wavelet or timedomain based methods that lack the robustness advantage.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Adaptive Multi-Level Phase Coding Method in Audio Steganography

2019

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Audio steganography allows and inspires many researchers to design methods for secure communication. Based on the evaluation on the existing methods, it was found that most methods focused on one or two requirements while disregarding others, causing imbalanced performance. Moreover, most methods lack adaptivity and dynamic allocation. Therefore, in this research, a method called Adaptive Multi-level Phase Coding (AMPC) was proposed to optimize the above issues. The reverse logic of the main tradeoffs was used to empirically design several embedding levels that that simultaneously attained good performance for all aspects as much as possible. Then, an adaptive component was added by selecting the embedding level that provided the best performance for each embedding process. Moreover, the error spreading factor was introduced to achieve a fair payload distribution. The performance balance objective requires a new formulation that will enable the accurate selection of the degree of modification, multiple-bit embedding per modification, and reduced retrieval errors. As a result, the interval centering quantization (ICQ) was formulated and implemented in the proposed method. The experimental results show that AMPC successfully fulfilled the research objectives. Also, AMPC surpassed other phase coding methods in all aspects while time-domain methods achieved the highest transparency and capacity with the lowest robustness. Moreover, experiments show that the implementation of adaptive multi-level concept is able to improve the existing method's performance significantly. In summary, AMPC was able to achieve a stable embedding rate of 33 Kbps at 35 dB of SNR, which is higher than the recorded embedding rate of other phase coding methods.

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Section: Related Workmentioning

confidence: 85%

Section: Related Workmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

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The Adaptive Multi-Level Phase Coding Method in Audio Steganography

2019

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“…Information can take many forms and data hiding schemes are dependent on the media they are intended to be used with. For instance, in [14] steganography for printed matter that can be employed in the anti-counterfeiting for product external packing in the Internet of Things (IoT) is discussed, in [15] the secret message is embedded into the cover of a quantum channel in steganography protocol for Fog Cloud IoT and in [16] the noise resilient audio steganography technique is proposed to be used in IoT networks.…”

Section: Related Workmentioning

confidence: 99%

Algorithm of Information Embedding into Digital Images Based on the Chinese Remainder Theorem for Data Security

Evsutin

Dzhanashia

2020

Cryptography

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With the huge transfers of data involved in the modern world, it is both crucial and challenging to maintain the security of data. This paper proposes a novel algorithm of information embedding into digital images that could be used to protect confidential information. The presented algorithm makes use of the Chinese remainder theorem and adaptive embedding to achieve good imperceptibility along with the possibility of hiding a decent amount of confidential information. The algorithm is evaluated via computing experiments and evaluation results, as well as comparison with similar works, demonstrate good imperceptibility qualities of the proposed scheme.

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“…The idea of hiding in expert systems lies in two basic ideas: the first is to sacrifice a large part of the complexity of hiding algorithms and thereby reduce the amount of processing and make the application lightweight, and to sacrifice part of the strength and resistance of the algorithm used against detection and various attacks. The second idea is to try to find concise methods and simplified methods of applying hiding algorithm with a much lower processing amount than the original algorithm and thus achieving the standards of lightweight applications [4][12].…”

Section: The Hiding In Lightweight Systemsmentioning

confidence: 99%

Lightweight Steganography Technique for Smartphone

Mohammed¹,

Ahmed²

2019

IJCA

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Steganography is an embedded technique that hides the message in a digital medium for the purpose of safely transferring the message. The objective of this paper is to develop and improve lightweight hiding techniques used in the systems of smartphones, by improving the well-known Least Significant Bit (LSB) algorithm by changing the attribute that is related to its work and suggesting some additions in a way that does not affect processing speed or memory usage and increases security. It also provides a large area for hiding a large secrete message with very little impact on the cover relative to the size of the cover used. This paper proposes several additions and modifications to the algorithm, including: using Pseudo Random Number Generator (PRNG) to determine pixels locations in the cover. Coding process was also proposed for the purpose of increasing randomization and provide statistical distribution unrelated to the original message. The LSB hiding process enables the use of less important bits per pixel. In this case, a distribution of hidden bits within one pixel was suggested by different distributions in each hiding process, making data of repeated hiding useless for the attackers. Various measures (MSE, PSNR, BER, and SSIM) were adopted for the purpose of measuring the quality and efficiency of the proposed algorithm through several experiments including cover image sizes in different dimensions with a variety of data for secret messages, whose results were better than other values.

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Lightweight Noise Resilient Steganography Scheme for Internet of Things

Cited by 12 publications

References 11 publications

The Adaptive Multi-Level Phase Coding Method in Audio Steganography

The Adaptive Multi-Level Phase Coding Method in Audio Steganography

Algorithm of Information Embedding into Digital Images Based on the Chinese Remainder Theorem for Data Security

Lightweight Steganography Technique for Smartphone

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