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  • Open Access

    ARTICLE

    Cover Enhancement Method for Audio Steganography Based on Universal Adversarial Perturbations with Sample Diversification

    Jiangchuan Li, Peisong He*, Jiayong Liu, Jie Luo, Qiang Xia

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4893-4915, 2023, DOI:10.32604/cmc.2023.036819 - 29 April 2023

    Abstract Steganography techniques, such as audio steganography, have been widely used in covert communication. However, the deep neural network, especially the convolutional neural network (CNN), has greatly threatened the security of audio steganography. Besides, existing adversarial attacks-based countermeasures cannot provide general perturbation, and the transferability against unknown steganography detection methods is weak. This paper proposes a cover enhancement method for audio steganography based on universal adversarial perturbations with sample diversification to address these issues. Universal adversarial perturbation is constructed by iteratively optimizing adversarial perturbation, which applies adversarial attack techniques, such as Deepfool. Moreover, the sample diversification… More >

  • Open Access

    ARTICLE

    Comparative Analysis of Execution of CNN-Based Sanguine Data Transmission with LSB-SS and PVD-SS

    Alaknanda S. Patil1,*, G. Sundari1, Arun Kumar Sivaraman2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1707-1721, 2023, DOI:10.32604/csse.2023.034270 - 09 February 2023

    Abstract The intact data transmission to the authentic user is becoming crucial at every moment in the current era. Steganography; is a technique for concealing the hidden message in any cover media such as image, video; and audio to increase the protection of data. The resilience and imperceptibility are improved by choosing an appropriate embedding position. This paper gives a novel system to immerse the secret information in different videos with different methods. An audio and video steganography with novel amalgamations are implemented to immerse the confidential auditory information and the authentic user’s face image. A… More >

  • Open Access

    ARTICLE

    An Efficient EMD-Based Reversible Data Hiding Technique Using Dual Stego Images

    Ahmad A. Mohammad*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1139-1156, 2023, DOI:10.32604/cmc.2023.035964 - 06 February 2023

    Abstract Exploiting modification direction (EMD) based data hiding techniques (DHTs) provide moderate data hiding capacity and high-quality stego images. The overflow problem and the cyclic nature of the extraction function essentially hinder their application in several fields in which reversibility is necessary. Thus far, the few EMD reversible DHTs are complex and numerically demanding. This paper presents a novel EMD-based reversible DHT using dual-image. Two novel 2 × 4 modification lookup tables are introduced, replacing the reference matrix used in similar techniques and eliminating the numerically demanding search step in similar techniques. In the embedding step, one of… More >

  • Open Access

    ARTICLE

    Topic Controlled Steganography via Graph-to-Text Generation

    Bowen Sun1, Yamin Li1,2,3,*, Jun Zhang1, Honghong Xu1, Xiaoqiang Ma4, Ping Xia2,3,5

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 157-176, 2023, DOI:10.32604/cmes.2023.025082 - 05 January 2023

    Abstract Generation-based linguistic steganography is a popular research area of information hiding. The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to. However, in the course of our experiment, we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text, which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases, and that the topic of generated texts is uncontrollable, so there is still room for improvement… More >

  • Open Access

    ARTICLE

    MI-STEG: A Medical Image Steganalysis Framework Based on Ensemble Deep Learning

    Rukiye Karakis1,2,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4649-4666, 2023, DOI:10.32604/cmc.2023.035881 - 28 December 2022

    Abstract Medical image steganography aims to increase data security by concealing patient-personal information as well as diagnostic and therapeutic data in the spatial or frequency domain of radiological images. On the other hand, the discipline of image steganalysis generally provides a classification based on whether an image has hidden data or not. Inspired by previous studies on image steganalysis, this study proposes a deep ensemble learning model for medical image steganalysis to detect malicious hidden data in medical images and develop medical image steganography methods aimed at securing personal information. With this purpose in mind, a… More >

  • Open Access

    ARTICLE

    A New Generative Mathematical Model for Coverless Steganography System Based on Image Generation

    Al-Hussien Seddik1, Mohammed Salah2, Gamal Behery2, Ahmed El-harby2, Ahmed Ismail Ebada2, Sokea Teng3, Yunyoung Nam3,*, Mohamed Abouhawwash4,5

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5087-5103, 2023, DOI:10.32604/cmc.2023.035364 - 28 December 2022

    Abstract The ability of any steganography system to correctly retrieve the secret message is the primary criterion for measuring its efficiency. Recently, researchers have tried to generate a new natural image driven from only the secret message bits rather than using a cover to embed the secret message within it; this is called the stego image. This paper proposes a new secured coverless steganography system using a generative mathematical model based on semi Quick Response (QR) code and maze game image generation. This system consists of two components. The first component contains two processes, encryption process,… More >

  • Open Access

    ARTICLE

    Optimal Deep Learning Model Enabled Secure UAV Classification for Industry 4.0

    Khalid A. Alissa1, Mohammed Maray2, Areej A. Malibari3, Sana Alazwari4, Hamed Alqahtani5, Mohamed K. Nour6, Marwa Obbaya7, Mohamed A. Shamseldin8, Mesfer Al Duhayyim9,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5349-5367, 2023, DOI:10.32604/cmc.2023.033532 - 28 December 2022

    Abstract Emerging technologies such as edge computing, Internet of Things (IoT), 5G networks, big data, Artificial Intelligence (AI), and Unmanned Aerial Vehicles (UAVs) empower, Industry 4.0, with a progressive production methodology that shows attention to the interaction between machine and human beings. In the literature, various authors have focused on resolving security problems in UAV communication to provide safety for vital applications. The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification (CSODL-SUAVC) model for Industry 4.0 environment. The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such… More >

  • Open Access

    ARTICLE

    Improved Video Steganography with Dual Cover Medium, DNA and Complex Frames

    Asma Sajjad1, Humaira Ashraf1, NZ Jhanjhi2,3,*, Mamoona Humayun4, Mehedi Masud5, Mohammed A. AlZain6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3881-3898, 2023, DOI:10.32604/cmc.2023.030197 - 31 October 2022

    Abstract The most valuable resource on the planet is no longer oil, but data. The transmission of this data securely over the internet is another challenge that comes with its ever-increasing value. In order to transmit sensitive information securely, researchers are combining robust cryptography and steganographic approaches. The objective of this research is to introduce a more secure method of video steganography by using Deoxyribonucleic acid (DNA) for embedding encrypted data and an intelligent frame selection algorithm to improve video imperceptibility. In the previous approach, DNA was used only for frame selection. If this DNA is… More >

  • Open Access

    ARTICLE

    Proposed Privacy Preservation Technique for Color Medical Images

    Walid El-Shafai1,2, Hayam A. Abd El-Hameed3, Noha A. El-Hag4, Ashraf A. M. Khalaf3, Naglaa F. Soliman5, Hussah Nasser AlEisa6,*, Fathi E. Abd El-Samie1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 719-732, 2023, DOI:10.32604/iasc.2023.031079 - 29 September 2022

    Abstract Nowadays, the security of images or information is very important. This paper introduces a proposed hybrid watermarking and encryption technique for increasing medical image security. First, the secret medical image is encrypted using Advanced Encryption Standard (AES) algorithm. Then, the secret report of the patient is embedded into the encrypted secret medical image with the Least Significant Bit (LSB) watermarking algorithm. After that, the encrypted secret medical image with the secret report is concealed in a cover medical image, using Kekre’s Median Codebook Generation (KMCG) algorithm. Afterwards, the stego-image obtained is split into 16 parts.… More >

  • Open Access

    ARTICLE

    An Enhanced Graphical Authentication Scheme Using Multiple-Image Steganography

    Khalil Hamdi Ateyeh Al-Shqeerat*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2095-2107, 2023, DOI:10.32604/csse.2023.028975 - 01 August 2022

    Abstract Most remote systems require user authentication to access resources. Text-based passwords are still widely used as a standard method of user authentication. Although conventional text-based passwords are rather hard to remember, users often write their passwords down in order to compromise security. One of the most complex challenges users may face is posting sensitive data on external data centers that are accessible to others and do not be controlled directly by users. Graphical user authentication methods have recently been proposed to verify the user identity. However, the fundamental limitation of a graphical password is that… More >

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