A Novel Laplacian of Gaussian (LoG) and Chaotic Encryption Based Image Steganography Technique

Jan, Aiman; Parah, Shabir A.; Malik, Bilal A.

doi:10.1109/incet49848.2020.9154173

Cited by 10 publications

(3 citation statements)

References 5 publications

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“…The final step in edge detection entailsidentifying zero crossings in this enhanced second derivative, aligning with corresponding high peaks in the first derivative. This combined approach in LoG effectively addresses noise-related challenges in the edge detection process [25]. 2.…”

Section: Laplacian Of Gaussian (Log)mentioning

confidence: 99%

An In-Depth Analysis of Steganography Techniques: From Classical Edge Detection to Adaptive Approaches

Gh. Abdullah,

A. Hasso

2024

IRJIET

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This paper delves into the realm of steganography, focusing on the evolution of techniques employed to conceal data within digital images. Beginning with an exploration of the motivations behind information security and the role of cryptography, the paper introduces adaptive steganography as a discreet means of incorporating private data into a cover medium. The discussion then shifts to the three key factors in image steganography - resilience, capacity, and imperceptibility - forming the foundation of effective data hiding. The spatial and frequency domain methods are compared, with specific emphasis on the classical Least Significant Bit insertion and more advanced adaptive steganography techniques. The paper further introduces edge-based steganography, highlighting the advantage of manipulating edge areas for increased imperceptibility. Moving beyond definitions and types, the paper provides a comprehensive analysis of notable research works in the field, elucidating their objectives, methodologies, results, strengths, and limitations. The conclusion reflects on the dynamic landscape of steganography, acknowledging both achievements and areas for improvement.

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Section: Laplacian Of Gaussian (Log)mentioning

confidence: 99%

An In-Depth Analysis of Steganography Techniques: From Classical Edge Detection to Adaptive Approaches

Gh. Abdullah,

A. Hasso

2024

IRJIET

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“…The encryption process is achieved by modulus addition of the secret bits with the corresponding OTP bits. Laplacian of Gaussian (LoG) detector is used in [94] alongside a chaotic function. The secret information is first encrypted by XORing it with a PRN generated by a chaotic LM.…”

Section: Refmentioning

confidence: 99%

A Review on Security Techniques in Image Steganography

Ghoul¹,

Sulaiman²,

Shukur³

2023

IJACSA

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Given the increased popularity of the internet, the exchange of sensitive information leads to concerns about privacy and security. Techniques such as steganography and cryptography have been employed to protect sensitive information. Steganography is one of the promising tools for securely exchanging sensitive information through an unsecured medium. It is a powerful tool for protecting a user's data, wherein the user can hide messages inside other media, such as images, videos, and audios (cover media). Image steganography is the science of concealing secret information inside an image using various techniques. The nature of the embedding process makes the hidden information undetectable to human eyes. The challenges faced by image steganography techniques include achieving high embedding capacity, good imperceptibility, and high security. These criteria are inter-related since enhancing one factor undermines one or more others. This paper provides an overview of existing research related to various techniques and security in image steganography. First, basic information in this domain is presented. Next, various kinds of security techniques used in steganography are explained, such as randomization, encryption, and region-based techniques. This paper covers research published from 2017 to 2022. This review is not exhaustive and aims to explore state-of-the-art techniques applied to enhance security, crucial issues in the domain, and future directions to assist new and current researchers.

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“…To avoid suspicion from intruders, [6] applied the Local Laplacian of Gaussian on the cover image to improve its quality when embedding with a secret image. Logistic maps were applied on the secret image to scramble and embed with cover image using LSB.…”

Section: Related Workmentioning

confidence: 99%

QR Steganography for Information Hiding of Patient Record

Subramaniam¹,

Mohd-Isa²,

Yap³

2022

Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)

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In recent research studies, biosignals are used to study the behaviour of a human body function which are useful for medical diagnosis. Biosignals such as electrocardiogram (ECG) signals are used to determine the irregularities in heartbeat meanwhile electroencephalogram (EEG) signal is used to record the brain activity of a patient. This paper aims to put together a mechanism to hide patient details with image of patient medical biosignals using steganography. Patient details are stored in the QR Code meanwhile biosignals that are in 1 dimensional are converted into two-dimensional image. In this process of hiding the patient details and its biosignal, fine details may be lost. Thus, image enhancement process is needed. In this paper, methods such as Local Laplacian filter, Successive Mean Quantization Transform (SMQT) algorithm, Non-Local Means filtering, Bilateral filtering with Gaussian Kernel and Anisotropic Diffusion are used to evaluate the medical image quality of the biosignal. Quantitative metrics are used to evaluate the quality of implementation. The proposed method has given out results of Peak Signal-to-Noise Ratio (PSNR), Mean-Squared Error (MSE), Normalized Cross-Correlation (NCC) that are comparatively well with other established methods. Findings from this paper indicates improvement in the overall image quality of biosignals after extraction from its cover image using the proposed methods.

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A Novel Laplacian of Gaussian (LoG) and Chaotic Encryption Based Image Steganography Technique

Cited by 10 publications

References 5 publications

An In-Depth Analysis of Steganography Techniques: From Classical Edge Detection to Adaptive Approaches

An In-Depth Analysis of Steganography Techniques: From Classical Edge Detection to Adaptive Approaches

A Review on Security Techniques in Image Steganography

QR Steganography for Information Hiding of Patient Record

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