Xingyu Chen^*

Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 103-113, 2022, DOI:10.32604/jihpp.2022.039766

Abstract With the popularization of high-performance electronic imaging equipment and the wide application of digital image editing software, the threshold of digital image editing becomes lower and lower. This makes it easy to trick the human visual system with professionally altered images. These tampered images have brought serious threats to many fields, including personal privacy, news communication, judicial evidence collection, information security and so on. Therefore, the security and reliability of digital information has been increasingly concerned by the international community. In this paper, digital image tamper detection methods are classified according to the clues that they rely on, detection methods… More >

Liang Xiu-jian^1,2,*, Sun He²

Journal of Cyber Security, Vol.4, No.2, pp. 119-133, 2022, DOI:10.32604/jcs.2022.032915

Abstract Increasingly advanced image processing technology has made digital image editing easier and easier. With image processing software at one’s fingertips, one can easily alter the content of an image, and the altered image is so realistic that it is illegible to the naked eye. These tampered images have posed a serious threat to personal privacy, social order, and national security. Therefore, detecting and locating tampered areas in images has important practical significance, and has become an important research topic in the field of multimedia information security. In recent years, deep learning technology has been widely used in image tampering localization,… More >

Anwer Mustafa Hilal^1,*, Fahd N. Al-Wesabi^2,3, Mohammed Alamgeer⁴, Manar Ahmed Hamza¹, Mohammad Mahzari⁵, Murad A. Almekhlafi⁶

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5583-5600, 2022, DOI:10.32604/cmc.2022.019686

Abstract Due to the rapid increase in the exchange of text information via internet networks, the security and authenticity of digital content have become a major research issue. The main challenges faced by researchers are how to hide the information within the text to use it later for authentication and attacks tampering detection without effects on the meaning and size of the given digital text. In this paper, an efficient text-based watermarking method has been proposed for detecting the illegal tampering attacks on the Arabic text transmitted online via an Internet network. Towards this purpose, the accuracy of tampering detection and… More >

Mesfer Al Duhayyim¹, Manal Abdullah Alohali², Fahd N. Al-Wesabi^3,4, Anwer Mustafa Hilal^5,*, Mohammad Medani³, Manar Ahmed Hamza⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2879-2894, 2022, DOI:10.32604/cmc.2022.019594

Abstract The most common digital media exchanged via the Internet is in text form. The Arabic language is considered one of the most sensitive languages of content modification due to the presence of diacritics that can cause a change in the meaning. In this paper, an intelligent scheme is proposed for improving the reliability and security of the text exchanged via the Internet. The core mechanism of the proposed scheme depends on integrating the hidden Markov model and zero text watermarking techniques. The watermark key will be generated by utilizing the extracted features of the text analysis process using the third… More >

Fahd N. Al-Wesabi^1,2,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1519-1536, 2021, DOI:10.32604/cmc.2021.018202

Abstract In this paper, the text analysis-based approach RTADZWA (Reliable Text Analysis and Digital Zero-Watermarking Approach) has been proposed for transferring and receiving authentic English text via the internet. Second level order of alphanumeric mechanism of hidden Markov model has been used in RTADZWA approach as a natural language processing to analyze the English text and extracts the features of the interrelationship between contexts of the text and utilizes the extracted features as watermark information and then validates it later with attacked English text to detect any tampering occurred on it. Text analysis and text zero-watermarking techniques have been integrated by… More >

Bozhi Xu¹, Jiarui Liu¹, Jifan Liang¹, Wei Lu^1,*, Yue Zhang²

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1375-1388, 2021, DOI:10.32604/cmc.2021.016760

Abstract In recent years, with the rapid development of deep learning technologies, some neural network models have been applied to generate fake media. DeepFakes, a deep learning based forgery technology, can tamper with the face easily and generate fake videos that are difficult to be distinguished by human eyes. The spread of face manipulation videos is very easy to bring fake information. Therefore, it is important to develop effective detection methods to verify the authenticity of the videos. Due to that it is still challenging for current forgery technologies to generate all facial details and the blending operations are used in… More >

Fahd N. Al-Wesabi^1,2,*, Saleh Alzahrani³, Fuad Alyarimi³, Mohammed Abdul³, Nadhem Nemri³, Mohammed M. Almazah⁴

Computer Systems Science and Engineering, Vol.37, No.3, pp. 297-311, 2021, DOI:10.32604/csse.2021.015915

Abstract In this paper, a combined approach CAZWNLP (a combined approach of zero-watermarking and natural language processing) has been developed for the tampering detection of English text exchanged through the Internet. The third gram of alphanumeric of the Markov model has been used with text-watermarking technologies to improve the performance and accuracy of tampering detection issues which are limited by the existing works reviewed in the literature of this study. The third-grade level of the Markov model has been used in this method as natural language processing technology to analyze an English text and extract the textual characteristics of the given… More >

Fahd N. Al-Wesabi^1,2,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3701-3719, 2021, DOI:10.32604/cmc.2021.015785

Abstract Due to the rapid increase in the exchange of text information via internet networks, the security and the reliability of digital content have become a major research issue. The main challenges faced by researchers are authentication, integrity verification, and tampering detection of the digital contents. In this paper, text zero-watermarking and text feature-based approach is proposed to improve the tampering detection accuracy of English text contents. The proposed approach embeds and detects the watermark logically without altering the original English text document. Based on hidden Markov model (HMM), the fourth level order of the word mechanism is used to analyze… More >

Fahd N. Al-Wesabi¹, Abdelzahir Abdelmaboud^2,*, Adnan A. Zain³, Mohammed M. Almazah⁴, Ammar Zahary⁵

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 483-498, 2021, DOI:10.32604/iasc.2021.014322

Abstract Text information depends primarily on natural languages processing. Improving the security and usability of text information shared through the public internet has therefore been the most demanding problem facing researchers. In contact and knowledge sharing through the Internet, the authentication of content and the identification of digital content are becoming a key problem. Therefore, in this paper, a fragile approach of zero-watermarking based on natural language processing has been developed for authentication of content and prevention of misuse of Arabic texts distributed over the Internet. According to the proposed approach, watermark embedding, and identification was technically carried out such that… More >

Fahd N. Al-Wesabi^1,*, Huda G. Iskandar², Mohammad Alamgeer³, Mokhtar M. Ghilan²

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1267-1283, 2020, DOI:10.32604/iasc.2020.013782

Abstract In this paper, a robust approach INLPETWA (an Intelligent Natural Language Processing and English Text Watermarking Approach) is proposed to tampering detection of English text by integrating zero text watermarking and hidden Markov model as a soft computing and natural language processing techniques. In the INLPETWA approach, embedding and detecting the watermark key logically conducted without altering the plain text. Second-gram and word mechanism of hidden Markov model is used as a natural text analysis technique to extracts English text features and use them as a watermark key and embed them logically and validates them during detection process to detect… More >