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  • Open Access

    ARTICLE

    Proposing a High-Robust Approach for Detecting the Tampering Attacks on English Text Transmitted via Internet

    Fahd N. Al-Wesabi1,*, 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 More >

  • Open Access

    ARTICLE

    University Learning and Anti-Plagiarism Back-End Services

    Manjur Kolhar*, Abdalla Alameen

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1215-1226, 2021, DOI:10.32604/cmc.2020.012658

    Abstract Plagiarism refers to the use of other people’s ideas and information without acknowledging the source. In this research, anti-plagiarism software was designed especially for the university and its campuses to identify plagiarized text in students’ written assignments and laboratory reports. The proposed framework collected original documents to identify plagiarized text using natural language processing. Our research proposes a method to detect plagiarism by applying the core concept of text, which is semantic associations of words and their syntactic composition. Information on the browser was obtained through Request application programming interface by name Url.AbsoluteUri, and it is… More >

  • Open Access

    ARTICLE

    A Hybrid Intelligent Approach for Content Authentication and Tampering Detection of Arabic Text Transmitted via Internet

    Fahd N. Al-Wesabi1,2,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 195-211, 2021, DOI:10.32604/cmc.2020.012088

    Abstract In this paper, a hybrid intelligent text zero-watermarking approach has been proposed by integrating text zero-watermarking and hidden Markov model as natural language processing techniques for the content authentication and tampering detection of Arabic text contents. The proposed approach known as Second order of Alphanumeric Mechanism of Markov model and Zero-Watermarking Approach (SAMMZWA). Second level order of alphanumeric mechanism based on hidden Markov model is integrated with text zero-watermarking techniques to improve the overall performance and tampering detection accuracy of the proposed approach. The SAMMZWA approach embeds and detects the watermark logically without altering the More >

  • Open Access

    ARTICLE

    A Smart English Text Zero-Watermarking Approach Based on Third-Level Order and Word Mechanism of Markov Model

    Fahd N. Al-Wesabi1, 2, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1137-1156, 2020, DOI:10.32604/cmc.2020.011151

    Abstract Text information is principally dependent on the natural languages. Therefore, improving security and reliability of text information exchanged via internet network has become the most difficult challenge that researchers encounter. Content authentication and tampering detection of digital contents have become a major concern in the area of communication and information exchange via the Internet. In this paper, an intelligent text Zero-Watermarking approach SETZWMWMM (Smart English Text Zero-Watermarking Approach Based on Mid-Level Order and Word Mechanism of Markov Model) has been proposed for the content authentication and tampering detection of English text contents. The SETZWMWMM approach… More >

  • Open Access

    ARTICLE

    A Longest Matching Resource Mapping Algorithm with State Compression Dynamic Programming Optimization

    Zhang Min, Teng Haibin, Jiang Ming, Wen Tao, Tang Jingfan

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 625-635, 2019, DOI:10.31209/2019.100000117

    Abstract Mapping from sentence phrases to knowledge graph resources is an important step for applications such as search engines, automatic question answering systems based on acknowledge base and knowledge graphs. The existing solution maps a simple phrase to a knowledge graph resource strictly or approximately from the text. However, it is difficult to detect phrases and map the composite semantic resource. This paper proposes a longest matching resource mapping scheme to solve this problem, namely, to find the longest substring in a sentence that can match the knowledge base resource. Based on this scheme, we propose More >

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