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  • Open Access

    ARTICLE

    Anomaly Detection Based on Discrete Wavelet Transformation for Insider Threat Classification

    Dong-Wook Kim1, Gun-Yoon Shin1, Myung-Mook Han2,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 153-164, 2023, DOI:10.32604/csse.2023.034589 - 20 January 2023

    Abstract Unlike external attacks, insider threats arise from legitimate users who belong to the organization. These individuals may be a potential threat for hostile behavior depending on their motives. For insider detection, many intrusion detection systems learn and prevent known scenarios, but because malicious behavior has similar patterns to normal behavior, in reality, these systems can be evaded. Furthermore, because insider threats share a feature space similar to normal behavior, identifying them by detecting anomalies has limitations. This study proposes an improved anomaly detection methodology for insider threats that occur in cybersecurity in which a discrete… More >

  • Open Access

    ARTICLE

    Implementation of VLSI on Signal Processing-Based Digital Architecture Using AES Algorithm

    Mohanapriya Marimuthu1, Santhosh Rajendran2, Reshma Radhakrishnan2, Kalpana Rengarajan3, Shahzada Khurram4, Shafiq Ahmad5, Abdelaty Edrees Sayed5, Muhammad Shafiq6,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4729-4745, 2023, DOI:10.32604/cmc.2023.033020 - 28 December 2022

    Abstract Continuous improvements in very-large-scale integration (VLSI) technology and design software have significantly broadened the scope of digital signal processing (DSP) applications. The use of application-specific integrated circuits (ASICs) and programmable digital signal processors for many DSP applications have changed, even though new system implementations based on reconfigurable computing are becoming more complex. Adaptable platforms that combine hardware and software programmability efficiency are rapidly maturing with discrete wavelet transformation (DWT) and sophisticated computerized design techniques, which are much needed in today’s modern world. New research and commercial efforts to sustain power optimization, cost savings, and improved… More >

  • Open Access

    ARTICLE

    Optimal IoT Based Improved Deep Learning Model for Medical Image Classification

    Prasanalakshmi Balaji1,*, B. Sri Revathi2, Praveetha Gobinathan3, Shermin Shamsudheen3, Thavavel Vaiyapuri4

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2275-2291, 2022, DOI:10.32604/cmc.2022.028560 - 16 June 2022

    Abstract Recently medical image classification plays a vital role in medical image retrieval and computer-aided diagnosis system. Despite deep learning has proved to be superior to previous approaches that depend on handcrafted features; it remains difficult to implement because of the high intra-class variance and inter-class similarity generated by the wide range of imaging modalities and clinical diseases. The Internet of Things (IoT) in healthcare systems is quickly becoming a viable alternative for delivering high-quality medical treatment in today’s e-healthcare systems. In recent years, the Internet of Things (IoT) has been identified as one of the… More >

  • Open Access

    ARTICLE

    Research on Thunderstorm Identification Based on Discrete Wavelet Transform

    Xiaopeng Li1, Ziyuan Xu3,4, Jin Han1,*, Xingming Sun1,2, Yi Cao5

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1153-1166, 2022, DOI:10.32604/iasc.2022.023261 - 08 February 2022

    Abstract Lightning has been one of the most talked-about natural disasters worldwide in recent years, as it poses a great threat to all industries and can cause huge economic losses. Thunderstorms are often accompanied by natural phenomena such as lightning strikes and lightning, and many scholars have studied deeply the regulations of thunderstorm generation, movement and dissipation to reduce the risk of lightning damage. Most of the current methods for studying thunderstorms focus on using more complex algorithms based on radar or lightning data, which increases the computational burden and reduces the computational efficiency to some… More >

  • Open Access

    ARTICLE

    Synovial Sarcoma Classification Technique Using Support Vector Machine and Structure Features

    P. Arunachalam1, N. Janakiraman1,*, Arun Kumar Sivaraman2, A. Balasundaram3, Rajiv Vincent2, Sita Rani4, Barnali Dey5, A. Muralidhar2, M. Rajesh2

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1241-1259, 2022, DOI:10.32604/iasc.2022.022573 - 17 November 2021

    Abstract Digital clinical histopathology technique is used for accurately diagnosing cancer cells and achieving optimal results using Internet of Things (IoT) and blockchain technology. The cell pattern of Synovial Sarcoma (SS) cancer images always appeared as spindle shaped cell (SSC) structures. Identifying the SSC and its prognostic indicator are very crucial problems for computer aided diagnosis, especially in healthcare industry applications. A constructive framework has been proposed for the classification of SSC feature components using Support Vector Machine (SVM) with the assistance of relevant Support Vectors (SVs). This framework used the SS images, and it has… More >

  • Open Access

    ARTICLE

    Detection of Fuel Adulteration Using Wave Optical with Machine Learning Algorithms

    S. Dilip Kumar1,*, T. V. Sivasubramonia Pillai2

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 19-33, 2022, DOI:10.32604/csse.2022.019366 - 08 October 2021

    Abstract Fuel is a very important factor and has considerable influence on the air quality in the environment, which is the heart of the world. The increase of vehicles in lived-in areas results in greater emission of carbon particles in the environment. Adulterated fuel causes more contaminated particles to mix with breathing air and becomes the main source of dangerous pollution. Adulteration is the mixing of foreign substances in fuel, which damages vehicles and causes more health problems in living beings such as humans, birds, aquatic life, and even water resources by emitting high levels of… More >

  • Open Access

    ARTICLE

    Image Authenticity Detection Using DWT and Circular Block-Based LTrP Features

    Marriam Nawaz1, Zahid Mehmood2,*, Tahira Nazir1, Momina Masood1, Usman Tariq3, Asmaa Mahdi Munshi4, Awais Mehmood1, Muhammad Rashid5

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1927-1944, 2021, DOI:10.32604/cmc.2021.018052 - 21 July 2021

    Abstract Copy-move forgery is the most common type of digital image manipulation, in which the content from the same image is used to forge it. Such manipulations are performed to hide the desired information. Therefore, forgery detection methods are required to identify forged areas. We have introduced a novel method for features computation by employing a circular block-based method through local tetra pattern (LTrP) features to detect the single and multiple copy-move attacks from the images. The proposed method is applied over the circular blocks to efficiently and effectively deal with the post-processing operations. It also… More >

  • Open Access

    ARTICLE

    Digital Forensics for Skulls Classification in Physical Anthropology Collection Management

    Imam Yuadi1,*, Myrtati D. Artaria2, Sakina3, A. Taufiq Asyhari4

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3979-3995, 2021, DOI:10.32604/cmc.2021.015417 - 06 May 2021

    Abstract The size, shape, and physical characteristics of the human skull are distinct when considering individual humans. In physical anthropology, the accurate management of skull collections is crucial for storing and maintaining collections in a cost-effective manner. For example, labeling skulls inaccurately or attaching printed labels to skulls can affect the authenticity of collections. Given the multiple issues associated with the manual identification of skulls, we propose an automatic human skull classification approach that uses a support vector machine and different feature extraction methods such as gray-level co-occurrence matrix features, Gabor features, fractal features, discrete wavelet… More >

  • Open Access

    ARTICLE

    A Triple-Channel Encrypted Hybrid Fusion Technique to Improve Security of Medical Images

    Ahmed S. Salama1,2,3, Mohamed Amr Mokhtar3, Mazhar B. Tayel3, Esraa Eldesouky4,6, Ahmed Ali5,6,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 431-446, 2021, DOI:10.32604/cmc.2021.016165 - 22 March 2021

    Abstract Assuring medical images protection and robustness is a compulsory necessity nowadays. In this paper, a novel technique is proposed that fuses the wavelet-induced multi-resolution decomposition of the Discrete Wavelet Transform (DWT) with the energy compaction of the Discrete Wavelet Transform (DCT). The multi-level Encryption-based Hybrid Fusion Technique (EbhFT) aims to achieve great advances in terms of imperceptibility and security of medical images. A DWT disintegrated sub-band of a cover image is reformed simultaneously using the DCT transform. Afterwards, a 64-bit hex key is employed to encrypt the host image as well as participate in the… More >

  • Open Access

    ARTICLE

    Multimodal Medical Image Registration and Fusion for Quality Enhancement

    Muhammad Adeel Azam1, Khan Bahadar Khan2,*, Muhammad Ahmad3, Manuel Mazzara4

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 821-840, 2021, DOI:10.32604/cmc.2021.016131 - 22 March 2021

    Abstract For the last two decades, physicians and clinical experts have used a single imaging modality to identify the normal and abnormal structure of the human body. However, most of the time, medical experts are unable to accurately analyze and examine the information from a single imaging modality due to the limited information. To overcome this problem, a multimodal approach is adopted to increase the qualitative and quantitative medical information which helps the doctors to easily diagnose diseases in their early stages. In the proposed method, a Multi-resolution Rigid Registration (MRR) technique is used for multimodal… More >

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