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Abdul Gaffar

Bio: Abdul Gaffar is an academic researcher from University of Lucknow. The author has contributed to research in topics: Encryption & Cryptography. The author has an hindex of 1, co-authored 4 publications receiving 20 citations.

Papers
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Journal ArticleDOI
TL;DR: The statistical analyses like histogram, correlation and entropy confirm the robustness of the proposed method against statistical attacks and experimental results show that the method is resistant to occlusion attack.

55 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a two-dimensional (2D) linear congruential generator (LCG), silver ratio, and Galois field, which is designed not merely to secure multiple digital images, namely, three truecolor, nine grayscale, and seventy-two binary images of different sizes, but also to address the above drawbacks.
Abstract: Security of multiple digital images over an unsecured channel is a current area of research in the field of image cryptography. Several techniques have been proposed for this purpose. However, the main drawbacks of the existing techniques are as follows: the existing techniques can be applied merely to the grayscale or the truecolor images; the size of the cipher (output) image is bigger than that of the plain (input) images; the authors have used a large number of parameters in the encryption/decryption process, besides the secret key; and the cipher/decipher rounds use the same key for encryption/decryption process. The proposed technique, which is based on a two-dimensional (2D) Linear Congruential Generator (LCG), silver ratio, and Galois field, is designed not merely to secure multiple digital images, namely, three truecolor, nine grayscale, and seventy-two binary images of different sizes, simultaneously, but also to address the above drawbacks. The designed technique achieves both confusion and diffusion properties essential for a secure cryptosystem. Also, the technique is empirically assessed via several statistical and security evaluation metrics, such as key sensitivity, histogram, chi-square, entropy, number of pixel change rate, structural similarity index measure, processing time, etc. The results of these evaluation metrics prove the efficiency and robustness of the designed technique.

2 citations

Book ChapterDOI
04 Dec 2020
TL;DR: In this paper, a method for securing different types of images (binary, gray scale, true color and index) based on stream cipher (RC4A) and MDS (Maximum Distance Separable) matrix is proposed.
Abstract: Stream ciphers are extensively used over a wide range of applications including security of digital data. In this paper, a method for securing different types of images (binary, gray scale, true color and index) based on stream cipher (RC4A) and MDS (Maximum Distance Separable) matrix is proposed. The proposed scheme is based on the cryptographic Permutation-Substitution Network (PSN) and hence achieves Shannon’s confusion-diffusion characteristics required for a robust encryption algorithm. The scheme encrypts a digital image into a random-like image from human visual as well as statistical point of view. Several encryption evaluation metrics are applied on test images to empirically assess the performance and efficiency of the proposed method. The consequences of these statistical and security tests support the concreteness of the proposed approach.
Journal ArticleDOI
16 Sep 2021
TL;DR: In this article, a method for securing different types of images (binary, gray scale, true color, and index) based on stream cipher (RC4A) and MDS (Maximum Distance Separable) matrix is proposed.
Abstract: This is an improved and extended version of the paper presented in CVIP 2020 conference. Stream ciphers are extensively used over a wide range of applications including security of digital data. In this paper, a method for securing different types of images (binary, gray scale, true color, and index) based on stream cipher (RC4A) and MDS (Maximum Distance Separable) matrix is proposed. The method adopts the framework of the Permutation-Substitution Network (PSN) of cryptography, and thus satisfies both confusion and diffusion properties required for a secure encryption algorithm. The proposed method encrypts a digital image into a random-like image from human visual as well as statistical point of view. Several encryption evaluation metrics, such as key sensitivity, chi-squared test, adjacent pixels correlation coefficient, irregular deviation, number of pixel change rate, unified averaged changed intensity, etc., are applied on test images taken from MATLAB IPT and USC-SIPI image database, to empirically assess the performance of the proposed method. The results of these statistical and security tests support the robustness of the proposed approach.

Cited by
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Journal ArticleDOI
TL;DR: In this article , a double-parameter fractal sorting matrix (DPFSM) is proposed to solve the limitation of calculation accuracy on information security, and the security analysis demonstrates the security.
Abstract: In the field of frontier research, information security has received a lot of interest, but in the field of information security algorithm, the introduction of decimals makes it impossible to bypass the topic of calculation accuracy. This article creatively proposes the definition and related proofs of double parameters fractal sorting matrix (DPFSM). As a new matrix classification with fractal properties, DPFSM contains self-similar structures in the ordering of both elements and sub-blocks in the matrix. These two self-similar structures are determined by two different parameters. To verify the theory, this paper presents a type of $2\times 2$ DPFSM iterative generation method, as well as the theory, steps, and examples of the iteration. DPFSM is a space position transformation matrix, which has a better periodic law than a single parameter fractal sorting matrix (FSM). The proposal of DPFSM expands the fractal theory and solves the limitation of calculation accuracy on information security. The image encryption algorithm based on DPFSM is proposed, and the security analysis demonstrates the security. DPFSM has good application value in the field of information security.

56 citations

Journal ArticleDOI
11 Sep 2020-Symmetry
TL;DR: This work proposes a novel bit-level permutation algorithm that contains a plain-image related rows and columns substitution, a pixel-level roll shift part, and a bit- level cyclic shift part that has good security performance and a speed advantage compared to other works.
Abstract: To ensure the security of digital images during transmission and storage, an efficient and secure chaos-based color image encryption scheme using bit-level permutation is proposed. Our proposed image encryption algorithm belongs to symmetric cryptography. Here, we process three color components simultaneously instead of individually, and consider the correlation between them. We propose a novel bit-level permutation algorithm that contains three parts: a plain-image related rows and columns substitution, a pixel-level roll shift part, and a bit-level cyclic shift part. In the plain-related rows and columns substitution part, we involve the plain-image information to generate a control sequence by using a skew tent system. This process ensures that the correlation between three color components can be totally broken, and our cryptosystem has enough plain-image sensitivity to resist the differential attack. In the pixel-level roll shift part and bit-level cyclic shift part, we have a fully bit-level permutation controlled by two sequences using a Rucklidge system. The simulation and some common security analyses are given. Test results show that our proposed scheme has good security performance and a speed advantage compared to other works.

42 citations

Journal ArticleDOI
TL;DR: The proposed cryptosystem provides the security of the digital images using the cryptographic algorithm in the frequency domain of the image using 2D discrete Haar wavelet transform (DHWT) and 3D logistic chaotic map.
Abstract: This paper proposes a new lossless encryption and decryption method for digital colour-image using 2D discrete Haar wavelet transform (DHWT) and 3D logistic chaotic map. The proposed cryptosystem p...

38 citations

Journal ArticleDOI
28 Nov 2021-Sensors
TL;DR: In this paper, a DL-based design for human action recognition (HAR) was proposed. But, the proposed design did not prove to be successful due to large video sequences which need to be processed in surveillance systems.
Abstract: Human action recognition (HAR) has gained significant attention recently as it can be adopted for a smart surveillance system in Multimedia. However, HAR is a challenging task because of the variety of human actions in daily life. Various solutions based on computer vision (CV) have been proposed in the literature which did not prove to be successful due to large video sequences which need to be processed in surveillance systems. The problem exacerbates in the presence of multi-view cameras. Recently, the development of deep learning (DL)-based systems has shown significant success for HAR even for multi-view camera systems. In this research work, a DL-based design is proposed for HAR. The proposed design consists of multiple steps including feature mapping, feature fusion and feature selection. For the initial feature mapping step, two pre-trained models are considered, such as DenseNet201 and InceptionV3. Later, the extracted deep features are fused using the Serial based Extended (SbE) approach. Later on, the best features are selected using Kurtosis-controlled Weighted KNN. The selected features are classified using several supervised learning algorithms. To show the efficacy of the proposed design, we used several datasets, such as KTH, IXMAS, WVU, and Hollywood. Experimental results showed that the proposed design achieved accuracies of 99.3%, 97.4%, 99.8%, and 99.9%, respectively, on these datasets. Furthermore, the feature selection step performed better in terms of computational time compared with the state-of-the-art.

31 citations

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper presented a new asymmetric image encryption and hiding algorithm based on SHA-3 and compressive sensing, which is able to resist the chosen-plaintext attack (CPA) and the known-plain text attack (KPA), and the experimental results show that the algorithm has strong imperceptibility and key sensitivity.
Abstract: This paper presents a new asymmetric image encryption and hiding algorithm based on SHA-3 and compressive sensing. First, to resist the chosen-plaintext attack (CPA) and the known-plaintext attack (KPA), SHA-3 is employed to calculate the hash values of the plain image, and they are transformed into the initial values of the chaotic map. Second, the plain image is divided into blocks which are processed by sparse transform, scrambling, compressive measurement, and merged. Then they are quantized and scrambled again to get an encrypted image. Third, the encrypted image is filled with zeros to the same size as the plain image. Then three numbers from the hundreds digit, tens digit, and single digit of each pixel are extracted respectively. Finally, the carrier image is transformed by integer wavelet transform (IWT) to get four coefficients, and then the above three numbers are embedded into low-frequency coefficients respectively. By inverse IWT, the carrier image containing secrets (CICS) can be obtained. The experimental results show that the algorithm has strong imperceptibility and key sensitivity. Especially, when the embedding coefficient is set to 1.0, the NC value between the carrier image (CI) and the CICS can reach 0.9999, and the PSNR value can reach about 43 dB.

29 citations