Arshiya S. Ansari^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2865-2892, 2024, DOI:10.32604/cmc.2024.045908

Abstract Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look. Whereas vehicular ad hoc networks (VANETs), which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services, as they are an essential component of modern smart transportation systems. VANETs steganography has been suggested by many authors for secure, reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy protection. This paper aims to determine whether using steganography is possible to improve data security… More >

Al Hussien Seddik Saad¹, Mohammed S. Reda², Gamal M. Behery², Ahmed A. El-harby², Mohammed Baz³, Mohamed Abouhawwash^4,5,*, Ahmed Ismail Ebada⁶

Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 125-138, 2023, DOI:10.32604/iasc.2023.032084

Abstract The trend of digital information transformation has become a topic of interest. Many data are threatening; thus, protecting such data from attackers is considered an essential process. Recently, a new methodology for data concealing has been suggested by researchers called coverless steganography. Coverless steganography can be accomplished either by building an image database to match its image subblocks with the secret message to obtain the stego image or by generating an image. This paper proposes a coverless image steganography system based on pure image generation using secret message bits with a capacity higher than the other traditional systems. The system… More >

Arslan Akram^1,2, Imran Khan¹, Javed Rashid^2,3, Mubbashar Saddique^4,*, Muhammad Idrees⁴, Yazeed Yasin Ghadi⁵, Abdulmohsen Algarni⁶

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1311-1328, 2024, DOI:10.32604/cmc.2023.040512

Abstract Algorithms for steganography are methods of hiding data transfers in media files. Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information, and these methods have made it feasible to handle a wide range of problems associated with image analysis. Images with little information or low payload are used by information embedding methods, but the goal of all contemporary research is to employ high-payload images for classification. To address the need for both low- and high-payload images, this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to… More >

Shahina Anwarul¹, Sunil Kumar², Ashok Bhansali³, Hammam Alshazly^4,*, Hany S. Hussein^5,6

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3145-3163, 2023, DOI:10.32604/csse.2023.041061

Abstract Security systems are the need of the hour to protect data from unauthorized access. The dissemination of confidential information over the public network requires a high level of security. The security approach such as steganography ensures confidentiality, authentication, integrity, and non-repudiation. Steganography helps in hiding the secret data inside the cover media so that the attacker can be confused during the transmission process of secret data between sender and receiver. Therefore, we present an efficient hybrid security model that provides multifold security assurance. To this end, a rectified Advanced Encryption Standard (AES) algorithm is proposed to overcome the problems existing… More >

Nizheen A. Ali¹, Ramadhan J. Mstafa^2,3,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1451-1469, 2023, DOI:10.32604/csse.2023.039957

Abstract With the widespread use of the internet, there is an increasing need to ensure the security and privacy of transmitted data. This has led to an intensified focus on the study of video steganography, which is a technique that hides data within a video cover to avoid detection. The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency. This paper proposes a new method to video steganography, which involves utilizing a Genetic Algorithm (GA) for identifying the Region of Interest (ROI) in the cover video. The ROI… More >

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

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 strategy is designed to improve… More >

Alaknanda S. Patil^1,*, G. Sundari¹, Arun Kumar Sivaraman²

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

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 hidden message is first included… More >

Ahmad A. Mohammad^*

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

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 the modification tables modifies a… More >

Bowen Sun¹, Yamin Li^1,2,3,*, Jun Zhang¹, Honghong Xu¹, Xiaoqiang Ma⁴, Ping Xia^2,3,5

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

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 in concealment. In this paper,… More >

Rukiye Karakis^1,2,*

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

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 dataset containing brain Magnetic Resonance… More >