Encryption-based steganography of images by multiobjective whale optimal pixel selection

Ambika, .; Biradar, Rajkumar L.; Burkpalli, Vishwanath

doi:10.1080/1206212x.2019.1692442

Cited by 25 publications

(13 citation statements)

References 17 publications

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“…According to a combination of those 2 values, 2 message bits may be hidden on every one of the pixels. Ambika et al [17] proposed an encryption-based steganographic method. The cover image was separated to RGB components in a separate manner.…”

Section: Literature Surveymentioning

confidence: 99%

Subject Review: Information Steganography Based on Different Methods

Maryoosh

Dhaief

Mustafa

2021

IJASRE

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Today, huge amounts of information are transmitted over the communication networks, especially via the Internet. Therefore, many individuals are concerned with data security. Various methods were appeared to maintain data security, and the most common of these methods are cryptography. Encryption methods are exposed to many attacks, and if the attacker obtains the key, the data is decrypted, so many algorithms have emerged to hide the information within the multimedia. When the attacker gets the data, he will not suspect that this multimedia may contain other information. Data security may depend on the type of hiding algorithm used and sometimes encryption is used in conjunction with hiding to increase data security. The major aim of this work is reviewing and describing many approaches utilized for hiding data within multimedia and to create a comparison of these methods.

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Section: Literature Surveymentioning

confidence: 99%

Subject Review: Information Steganography Based on Different Methods

Maryoosh

Dhaief

Mustafa

2021

IJASRE

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“…The input image is classified into R, G and B modules individually to examine the modules of the initial colors of all parts of the image [14]. In RGB, the cover image is separated on the basis of LL, LH, HL and HH bands for determining the pixels' position.…”

Section: Image Decompositionmentioning

confidence: 99%

“…When compared with diverse vector coefficients, a best pixel has been elected under the application of IWOA. Generally, WOA is stimulated by the hunting performance of humpback whales that applies the shrinking encircling method, spiral for simulating bubble net assaulting method and surrounds the prey [14].Here, 3 functions accelerate the performances of humpback whales are encircling victim, exploring the victim (exploration stage) and bubble-net foraging (exploitation stage), correspondingly.…”

Section: Optimal Pixel Selection Using Iwoamentioning

confidence: 99%

“…The variables applied in Signcryption model are sender 'S', standard parameter 'cp', secret key of sender 'xs', public key of receiver 'yr' as well as sender and receiver's public key 'ys', 'yr' as 'binfo' are defined as inputs for Signcryption approach. The variable 'binfo' is significant to protect the Signcryption that is composed of strings used for finding transmitter and receiver's public keys hash values [14]. The working process involved in DLCM technique is shown in Figure 2.…”

Section: Encryption Of B Components Using Signcryptionmentioning

confidence: 99%

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An Efficient Chaotic Encryption with Video Watermarking Technique using Improved Whale Optimization Algorithm

2020

IJATCSE

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Due to the advancements and familiarity of the Internet and the rise of different live broadcasting environments, digital videos have become a part of every day's life. On the other hand, security of videos poses a major threat in the common public networks. Digital watermarking is an effective approach commonly used to secure the digital information. Watermarking is a process of hiding data into multimedia content with no loss of the quality of the content in such a way that the watermark can be extracted by the legal user. This paper proposes a new digital video watermarking with encryption (DVWE) technique using improved whale optimization algorithm. The proposed model initially splits the input video into a sequence of frames and watermark data is hidden into every individual frame. Then, the image frames are decomposed using multi-level discrete wavelet transform (DWT). Besides, improved whale optimization algorithm (IWOA) is derived by incorporating the benefits of whale optimization algorithm (WOA) with levy flight (LF) concept for optimal pixel selection in the cover image. Followed by, the R, G and B components in the watermark data is encrypted by three encryption techniques namely elliptic curve cryptography (ECC), double logistic chaotic map (DLCM) and signcryption. As a result, the encrypted watermark image data is embedded into the cover image and then converted into a watermarked video. At the receiving end, the reverse process takes place to retrieve the secret watermark video. In order to assess the performance of the proposed model, an extensive experimental results analysis takes place. The simulation outcome depicted the effective performance of the presented model over the existing models.

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“…[5] Thus, the face segmentation and recognition have drawn considerable attention by researchers. However, can be applied in smart applications like human computer interaction, querying the database, [6] virtual reality, information security, [7] operating system, health monitoring reports, [8] real-time online bank transactions, biometrics, etc. [9] The efficiency of face recognition methods are highly influenced by few factors such as complex background, distortion in the expression, head lying position, the distance between the camera and the subject, lighting conditions, etc.…”

Section: Introductionmentioning

confidence: 99%

Facial Image Segmentation by Integration of Level Set and Neural Network Optimization with Hybrid Filter Pre-processing Model

Rangayya¹,

Patil²,

Patil³

2021

Eng. Sci.

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Face segmentation is the process of segmenting the visible parts of the face excluding the neck, ears, hair, and beards. In this field, several methods have been developed, but none of them have been effective in providing optimal face segmentation. Hence, we proposed a novel face segmentation method known as level-set-based neural network (NN) algorithm. This method exploits a hybrid filter for the pre-processing of images, which eliminates the unwanted noises and blurring effect from the images. The hybrid filter is the combination of Median, Mean, and Gaussian filters and effectively removes the unwanted noises. Hence the images are segmented by utilizing level-set-based NN algorithm which is commonly based on the population set and effectively reduces the gap between the predicted and expected outcomes. The proposed method is compared with state-of-art methods such as Fully convolution network (FCN), Gabor filter(GF), multi-class semantic face segmentation(MSFS), and genetic algorithms (GA). From the experimental analysis, it is evident that the proposed work achieved better results comparing to other approaches.

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Encryption-based steganography of images by multiobjective whale optimal pixel selection

Cited by 25 publications

References 17 publications

Subject Review: Information Steganography Based on Different Methods

Subject Review: Information Steganography Based on Different Methods

An Efficient Chaotic Encryption with Video Watermarking Technique using Improved Whale Optimization Algorithm

Facial Image Segmentation by Integration of Level Set and Neural Network Optimization with Hybrid Filter Pre-processing Model

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