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  • Open Access

    ARTICLE

    SlowFast Based Real-Time Human Motion Recognition with Action Localization

    Gyu-Il Kim1, Hyun Yoo2, Kyungyong Chung3,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2135-2152, 2023, DOI:10.32604/csse.2023.041030

    Abstract Artificial intelligence is increasingly being applied in the field of video analysis, particularly in the area of public safety where video surveillance equipment such as closed-circuit television (CCTV) is used and automated analysis of video information is required. However, various issues such as data size limitations and low processing speeds make real-time extraction of video data challenging. Video analysis technology applies object classification, detection, and relationship analysis to continuous 2D frame data, and the various meanings within the video are thus analyzed based on the extracted basic data. Motion recognition is key in this analysis. Motion recognition is a challenging… More >

  • Open Access

    ARTICLE

    An Innovative Technique for Constructing Highly Non-Linear Components of Block Cipher for Data Security against Cyber Attacks

    Abid Mahboob1, Muhammad Asif2, Rana Muhammad Zulqarnain3,*, Imran Siddique4, Hijaz Ahmad5, Sameh Askar6, Giovanni Pau7

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2547-2562, 2023, DOI:10.32604/csse.2023.040855

    Abstract The rapid advancement of data in web-based communication has created one of the biggest issues concerning the security of data carried over the internet from unauthorized access. To improve data security, modern cryptosystems use substitution-boxes. Nowadays, data privacy has become a key concern for consumers who transfer sensitive data from one place to another. To address these problems, many companies rely on cryptographic techniques to secure data from illegal activities and assaults. Among these cryptographic approaches, AES is a well-known algorithm that transforms plain text into cipher text by employing substitution box (S-box). The S-box disguises the relationship between cipher… More >

  • Open Access

    ARTICLE

    Dimensionality Reduction Using Optimized Self-Organized Map Technique for Hyperspectral Image Classification

    S. Srinivasan, K. Rajakumar*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2481-2496, 2023, DOI:10.32604/csse.2023.040817

    Abstract

    The high dimensionalhyperspectral image classification is a challenging task due to the spectral feature vectors. The high correlation between these features and the noises greatly affects the classification performances. To overcome this, dimensionality reduction techniques are widely used. Traditional image processing applications recently propose numerous deep learning models. However, in hyperspectral image classification, the features of deep learning models are less explored. Thus, for efficient hyperspectral image classification, a depth-wise convolutional neural network is presented in this research work. To handle the dimensionality issue in the classification process, an optimized self-organized map model is employed using a water strider optimization… More >

  • Open Access

    ARTICLE

    3D Model Encryption Algorithm by Parallel Bidirectional Diffusion and 1D Map with Sin and Logistic Coupling

    Yongsheng Hu*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1819-1838, 2023, DOI:10.32604/csse.2023.040729

    Abstract 3D models are essential in virtual reality, game development, architecture design, engineering drawing, medicine, and more. Compared to digital images, 3D models can provide more realistic visual effects. In recent years, significant progress has been made in the field of digital image encryption, and researchers have developed new algorithms that are more secure and efficient. However, there needs to be more research on 3D model encryption. This paper proposes a new 3D model encryption algorithm, called the 1D map with sin and logistic coupling (1D-MWSLC), because existing digital image encryption algorithms cannot be directly applied to 3D models. Firstly, this… More >

  • Open Access

    ARTICLE

    Towards Generating a Practical SUNBURST Attack Dataset for Network Attack Detection

    Ehab AlMasri1, Mouhammd Alkasassbeh1, Amjad Aldweesh2,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2643-2669, 2023, DOI:10.32604/csse.2023.040626

    Abstract Supply chain attacks, exemplified by the SUNBURST attack utilizing SolarWinds Orion updates, pose a growing cybersecurity threat to entities worldwide. However, the need for suitable datasets for detecting and anticipating SUNBURST attacks is a significant challenge. We present a novel dataset collected using a unique network traffic data collection methodology to address this gap. Our study aims to enhance intrusion detection and prevention systems by understanding SUNBURST attack features. We construct realistic attack scenarios by combining relevant data and attack indicators. The dataset is validated with the J48 machine learning algorithm, achieving an average F-Measure of 87.7%. Our significant contribution… More >

  • Open Access

    ARTICLE

    Privacy Preserved Brain Disorder Diagnosis Using Federated Learning

    Ali Altalbe1,2,*, Abdul Rehman Javed3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2187-2200, 2023, DOI:10.32604/csse.2023.040624

    Abstract Federated learning has recently attracted significant attention as a cutting-edge technology that enables Artificial Intelligence (AI) algorithms to utilize global learning across the data of numerous individuals while safeguarding user data privacy. Recent advanced healthcare technologies have enabled the early diagnosis of various cognitive ailments like Parkinson’s. Adequate user data is frequently used to train machine learning models for healthcare systems to track the health status of patients. The healthcare industry faces two significant challenges: security and privacy issues and the personalization of cloud-trained AI models. This paper proposes a Deep Neural Network (DNN) based approach embedded in a federated… More >

  • Open Access

    ARTICLE

    Applying Customized Convolutional Neural Network to Kidney Image Volumes for Kidney Disease Detection

    Ali Altalbe1,2,*, Abdul Rehman Javed3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2119-2134, 2023, DOI:10.32604/csse.2023.040620

    Abstract Kidney infection is a severe medical issue affecting individuals worldwide and increasing mortality rates. Chronic Kidney Disease (CKD) is treatable during its initial phases but can become irreversible and cause renal failure. Among the various diseases, the most prevalent kidney conditions affecting kidney function are cyst growth, kidney tumors, and nephrolithiasis. The significant challenge for the medical community is the immediate diagnosis and treatment of kidney disease. Kidney failure could result from kidney disorders like tumors, stones, and cysts if not often identified and addressed. Computer-assisted diagnostics are necessary to support clinicians’ and specialists’ medical assessments due to the rising… More >

  • Open Access

    ARTICLE

    Muti-Fusion Swarm Intelligence Optimization Algorithm in Base Station Coverage Optimization Problems

    Zhenyu Yan1,*, Haotian Bian2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2241-2257, 2023, DOI:10.32604/csse.2023.040603

    Abstract As millimeter waves will be widely used in the Internet of Things (IoT) and Telematics to provide high bandwidth communication and mass connectivity, the coverage optimization of base stations can effectively improve the quality of communication services. How to optimize the convergence speed of the base station coverage solution is crucial for IoT service providers. This paper proposes the Muti-Fusion Sparrow Search Algorithm (MFSSA) optimize the situation to address the problem of discrete coverage maximization and rapid convergence. Firstly, the initial swarm diversity is enriched using a sine chaotic map, and dynamic adaptive weighting is added to the discoverer location… More >

  • Open Access

    ARTICLE

    Knee Osteoarthritis Classification Using X-Ray Images Based on Optimal Deep Neural Network

    Abdul Haseeb1, Muhammad Attique Khan1,*, Faheem Shehzad1, Majed Alhaisoni2, Junaid Ali Khan1, Taerang Kim3, Jae-Hyuk Cha3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2397-2415, 2023, DOI:10.32604/csse.2023.040529

    Abstract X-Ray knee imaging is widely used to detect knee osteoarthritis due to ease of availability and lesser cost. However, the manual categorization of knee joint disorders is time-consuming, requires an expert person, and is costly. This article proposes a new approach to classifying knee osteoarthritis using deep learning and a whale optimization algorithm. Two pre-trained deep learning models (Efficientnet-b0 and Densenet201) have been employed for the training and feature extraction. Deep transfer learning with fixed hyperparameter values has been employed to train both selected models on the knee X-Ray images. In the next step, fusion is performed using a canonical… More >

  • Open Access

    ARTICLE

    An Efficient Heterogeneous Ring Signcryption Scheme for Wireless Body Area Networks

    Qingqing Ning, Chunhua Jin*, Zhiwei Chen, Yongliang Xu, Huaqi Lu

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2061-2078, 2023, DOI:10.32604/csse.2023.040483

    Abstract Wireless body area networks (WBANs) are an emerging technology for the real-time monitoring of physiological signals. WBANs provide a mechanism for collecting, storing, and transmitting physiological data to healthcare providers. However, the open wireless channel and limited resources of sensors bring security challenges. To ensure physiological data security, this paper provides an efficient Certificateless Public Key Infrastructure Heterogeneous Ring Signcryption (CP-HRSC) scheme, in which sensors are in a certificateless cryptosystem (CLC) environment, and the server is in a public key infrastructure (PKI) environment. CLC could solve the limitations of key escrow in identity-based cryptography (IBC) and certificate management for public… More >

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