ZLBM: zero level binary mapping technique for video security

Rajalakshmi, K.; Mahesh, K.

doi:10.1007/s11042-017-4942-0

Cited by 10 publications

(4 citation statements)

References 36 publications

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“…He hid the secret data in the appropriate places using the LSB replacement approach. K. Rajalakshmi et al [34] suggested a novel approach for video steganography called Zero Level Binary Mapping (ZLBM). The cover video is first converted into frames in their suggested procedure.…”

Section: Spatial Domain Techniquesmentioning

confidence: 99%

Review: Dual Method Cryptography and Steganography in Video Frames in IoT

2023

IJCCCE

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The Internet of things (IoT) is one of those emerging technologies, which are going to rule the world in the next few decades. The IoT environment not only enables Human to Machine interaction but also fosters Machine to Machine connectivity. Numerous IoT devices have poor security and insufficient computing power, making them prime targets for hackers. The IoT environment uses lightweight cryptographic techniques to address security requirements. Another security method for IoT devices is steganography. In the contemporary Internet era, the ability to secure private information is crucial, and steganography offers this capability. Due to its great ability to conceal sensitive data, video has drawn the attention of numerous academics among all forms of digital media. The main goal of this work is to examine several methods for fusing video steganography and cryptography techniques. Additionally, a thorough investigation and evaluation of a variety of video steganography methods in both compressed and raw domains are also emphasized. The comprehensive analysis of prior material makes it easier to have in-depth knowledge while creating approaches that combine cryptography with steganography. Index Terms — IoT, Lightweight, Video, Cryptography, Stenography

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Section: Spatial Domain Techniquesmentioning

confidence: 99%

Review: Dual Method Cryptography and Steganography in Video Frames in IoT

2023

IJCCCE

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“…PSNR values below 30 dB show that the human eye is able to detect the distortion, which means that the distortion is noticeable. Steganography algorithms should thus aim for signal-to-noise ratios of at least 40 dB [37,38].…”

Section: Embedding Capacity =mentioning

confidence: 99%

Reversible Video Steganography Using Quick Response Codes and Modified ElGamal Cryptosystem

Mstafa¹

2022

Computers, Materials &Amp; Continua

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The rapid transmission of multimedia information has been achieved mainly by recent advancements in the Internet's speed and information technology. In spite of this, advancements in technology have resulted in breaches of privacy and data security. When it comes to protecting private information in today's Internet era, digital steganography is vital. Many academics are interested in digital video because it has a great capability for concealing important data. There have been a vast number of video steganography solutions developed lately to guard against the theft of confidential data. The visual imperceptibility, robustness, and embedding capacity of these approaches are all challenges that must be addressed. In this paper, a novel solution to reversible video steganography based on Discrete Wavelet Transform (DWT) and Quick Response (QR) codes is proposed to address these concerns. In order to increase the security level of the suggested method, an enhanced ElGamal cryptosystem has also been proposed. Prior to the embedding stage, the suggested method uses the modified ElGamal algorithm to encrypt secret QR codes. Concurrently, it applies two-dimensional DWT on the Y-component of each video frame resulting in Approximation (LL), Horizontal (LH), Vertical (HL), and Diagonal (HH) sub-bands. Then, the encrypted Low (L), Medium (M), Quantile (Q), and High (H) QR codes are embedded into the HL sub-band, HH sub-band, U-component, and V-component of video frames, respectively, using the Least Significant Bit (LSB) technique. As a consequence of extensive testing of the approach, it was shown to be very secure and highly invisible, as well as highly resistant to attacks from Salt & Pepper, Gaussian, Poisson, and Speckle noises, which has an average Structural Similarity Index (SSIM) of more than 0.91. Aside from visual imperceptibility, the suggested method exceeds current methods in terms of Peak Signal-to-Noise Ratio (PSNR) average of 52.143 dB, and embedding capacity 1 bpp.

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“…The results revealed that their proposed algorithm achieves higher invisibility and capacity than other existing techniques in the literature. K. Rajalakshmi and K. Mahesh [29] introduced a novel approach for video steganography, called Zero Level Binary Mapping (ZLBM). Their proposed method first converts the cover video into frames.…”

Section: Related Workmentioning

confidence: 99%

“…PSNR values falling below 30 dB indicate that the human eye can notice the distortion. Hence, a good steganography algorithm should seek for 40 dB or more [29], [49].…”

Section: B Evaluation Metricsmentioning

confidence: 99%

A New Video Steganography Scheme Based on Shi-Tomasi Corner Detector

et al. 2020

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Recent developments in the speed of the Internet and information technology have made the rapid exchange of multimedia information possible. However, these developments in technology lead to violations of information security and private information. Digital steganography provides the ability to protect private information that has become essential in the current Internet age. Among all digital media, digital video has become of interest to many researchers due to its high capacity for hiding sensitive data. Numerous video steganography methods have recently been proposed to prevent secret data from being stolen. Nevertheless, these methods have multiple issues related to visual imperceptibly, robustness, and embedding capacity. To tackle these issues, this paper proposes a new approach to video steganography based on the corner point principle and LSBs algorithm. The proposed method first uses Shi-Tomasi algorithm to detect regions of corner points within the cover video frames. Then, it uses 4-LSBs algorithm to hide confidential data inside the identified corner points. Besides, before the embedding process, the proposed method encrypts confidential data using Arnold's cat map method to boost the security level. Experimental results revealed that the proposed method is highly secure and highly invisible, in addition to its satisfactory robustness against Salt & Pepper noise, Speckle noise, and Gaussian noise attacks, which has an average Structural Similarity Index (SSIM) of more than 0.81. Moreover, the results showed that the proposed method outperforms state-of-the-art methods in terms of visual imperceptibility, which offers excellent peak signalto-noise ratio (PSNR) of average 60.7 dB, maintaining excellent embedding capacity.

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ZLBM: zero level binary mapping technique for video security

Cited by 10 publications

References 36 publications

Review: Dual Method Cryptography and Steganography in Video Frames in IoT

Review: Dual Method Cryptography and Steganography in Video Frames in IoT

Reversible Video Steganography Using Quick Response Codes and Modified ElGamal Cryptosystem

A New Video Steganography Scheme Based on Shi-Tomasi Corner Detector

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