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  • Open Access

    ARTICLE

    Anomaly Detection for Industrial Internet of Things Cyberattacks

    Rehab Alanazi*, Ahamed Aljuhani

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2361-2378, 2023, DOI:10.32604/csse.2023.026712

    Abstract The evolution of the Internet of Things (IoT) has empowered modern industries with the capability to implement large-scale IoT ecosystems, such as the Industrial Internet of Things (IIoT). The IIoT is vulnerable to a diverse range of cyberattacks that can be exploited by intruders and cause substantial reputational and financial harm to organizations. To preserve the confidentiality, integrity, and availability of IIoT networks, an anomaly-based intrusion detection system (IDS) can be used to provide secure, reliable, and efficient IIoT ecosystems. In this paper, we propose an anomaly-based IDS for IIoT networks as an effective security solution to efficiently and effectively… More >

  • Open Access

    ARTICLE

    Towards Developing Privacy-Preserved Data Security Approach (PP-DSA) in Cloud Computing Environment

    S. Stewart Kirubakaran1,*, V. P. Arunachalam1, S. Karthik1, S. Kannan2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1881-1895, 2023, DOI:10.32604/csse.2023.026690

    Abstract In the present scenario of rapid growth in cloud computing models, several companies and users started to share their data on cloud servers. However, when the model is not completely trusted, the data owners face several security-related problems, such as user privacy breaches, data disclosure, data corruption, and so on, during the process of data outsourcing. For addressing and handling the security-related issues on Cloud, several models were proposed. With that concern, this paper develops a Privacy-Preserved Data Security Approach (PP-DSA) to provide the data security and data integrity for the outsourcing data in Cloud Environment. Privacy preservation is ensured… More >

  • Open Access

    ARTICLE

    A Novel Segment White Matter Hyperintensities Approach for Detecting Alzheimer

    Antonitta Eileen Pious1,*, U. K. Sridevi2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2715-2726, 2023, DOI:10.32604/csse.2023.026582

    Abstract Segmentation has been an effective step that needs to be done before the classification or detection of an anomaly like Alzheimer’s on a brain scan. Segmentation helps detect pixels of the same intensity or volume and group them together as one class or region, where in that particular region of interest (ROI) can be concentrated on, rather than focusing on the entire image. In this paper White Matter Hyperintensities (WMH) is taken as a strong biomarker that supports and determines the presence of Alzheimer’s. As the first step a proper segmentation of the lesions has to be carried out. As… More >

  • Open Access

    ARTICLE

    Diabetic Retinopathy Diagnosis Using Interval Neutrosophic Segmentation with Deep Learning Model

    V. Thanikachalam1,*, M. G. Kavitha2, V. Sivamurugan1

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2129-2145, 2023, DOI:10.32604/csse.2023.026527

    Abstract In recent times, Internet of Things (IoT) and Deep Learning (DL) models have revolutionized the diagnostic procedures of Diabetic Retinopathy (DR) in its early stages that can save the patient from vision loss. At the same time, the recent advancements made in Machine Learning (ML) and DL models help in developing Computer Aided Diagnosis (CAD) models for DR recognition and grading. In this background, the current research works designs and develops an IoT-enabled Effective Neutrosophic based Segmentation with Optimal Deep Belief Network (ODBN) model i.e., NS-ODBN model for diagnosis of DR. The presented model involves Interval Neutrosophic Set (INS) technique… More >

  • Open Access

    ARTICLE

    A Secure Hardware Implementation for Elliptic Curve Digital Signature Algorithm

    Mouna Bedoui1,*, Belgacem Bouallegue1,2, Abdelmoty M. Ahmed2, Belgacem Hamdi1,3, Mohsen Machhout1, Mahmoud1, M. Khattab2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2177-2193, 2023, DOI:10.32604/csse.2023.026516

    Abstract Since the end of the 1990s, cryptosystems implemented on smart cards have had to deal with two main categories of attacks: side-channel attacks and fault injection attacks. Countermeasures have been developed and validated against these two types of attacks, taking into account a well-defined attacker model. This work focuses on small vulnerabilities and countermeasures related to the Elliptic Curve Digital Signature Algorithm (ECDSA) algorithm. The work done in this paper focuses on protecting the ECDSA algorithm against fault-injection attacks. More precisely, we are interested in the countermeasures of scalar multiplication in the body of the elliptic curves to protect against… More >

  • Open Access

    ARTICLE

    Non Sub-Sampled Contourlet with Joint Sparse Representation Based Medical Image Fusion

    Kandasamy Kittusamy*, Latha Shanmuga Vadivu Sampath Kumar

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1989-2005, 2023, DOI:10.32604/csse.2023.026501

    Abstract Medical Image Fusion is the synthesizing technology for fusing multimodal medical information using mathematical procedures to generate better visual on the image content and high-quality image output. Medical image fusion represents an indispensible role in fixing major solutions for the complicated medical predicaments, while the recent research results have an enhanced affinity towards the preservation of medical image details, leaving color distortion and halo artifacts to remain unaddressed. This paper proposes a novel method of fusing Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) using a hybrid model of Non Sub-sampled Contourlet Transform (NSCT) and Joint Sparse Representation (JSR). This… More >

  • Open Access

    ARTICLE

    An Optimized Novel Trust-Based Security Mechanism Using Elephant Herd Optimization

    Saranya Veerapaulraj1,*, M. Karthikeyan1, S. Sasipriya2, A. S. Shanthi1

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2489-2500, 2023, DOI:10.32604/csse.2023.026463

    Abstract Routing strategies and security issues are the greatest challenges in Wireless Sensor Network (WSN). Cluster-based routing Low Energy adaptive Clustering Hierarchy (LEACH) decreases power consumption and increases network lifetime considerably. Securing WSN is a challenging issue faced by researchers. Trust systems are very helpful in detecting interfering nodes in WSN. Researchers have successfully applied Nature-inspired Metaheuristics Optimization Algorithms as a decision-making factor to derive an improved and effective solution for a real-time optimization problem. The metaheuristic Elephant Herding Optimizations (EHO) algorithm is formulated based on elephant herding in their clans. EHO considers two herding behaviors to solve and enhance optimization… More >

  • Open Access

    ARTICLE

    Colliding Bodies Optimization with Machine Learning Based Parkinson’s Disease Diagnosis

    Ashit Kumar Dutta1,*, Nazik M. A. Zakari2, Yasser Albagory3, Abdul Rahaman Wahab Sait4

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2195-2207, 2023, DOI:10.32604/csse.2023.026461

    Abstract Parkinson’s disease (PD) is one of the primary vital degenerative diseases that affect the Central Nervous System among elderly patients. It affect their quality of life drastically and millions of seniors are diagnosed with PD every year worldwide. Several models have been presented earlier to detect the PD using various types of measurement data like speech, gait patterns, etc. Early identification of PD is important owing to the fact that the patient can offer important details which helps in slowing down the progress of PD. The recently-emerging Deep Learning (DL) models can leverage the past data to detect and classify… More >

  • Open Access

    ARTICLE

    Early Skin Disease Identification Using eep Neural Network

    Vinay Gautam1, Naresh Kumar Trivedi1, Abhineet Anand1, Rajeev Tiwari2,*, Atef Zaguia3, Deepika Koundal4, Sachin Jain5

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2259-2275, 2023, DOI:10.32604/csse.2023.026358

    Abstract Skin lesions detection and classification is a prominent issue and difficult even for extremely skilled dermatologists and pathologists. Skin disease is the most common disorder triggered by fungus, viruses, bacteria, allergies, etc. Skin diseases are most dangerous and may be the cause of serious damage. Therefore, it requires to diagnose it at an earlier stage, but the diagnosis therapy itself is complex and needs advanced laser and photonic therapy. This advance therapy involves financial burden and some other ill effects. Therefore, it must use artificial intelligence techniques to detect and diagnose it accurately at an earlier stage. Several techniques have… More >

  • Open Access

    ARTICLE

    Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

    Dhanalakshmi R1, Sovan Samanta2, Arun Kumar Sivaraman3, Jeong Gon Lee4,*, Balasundaram A5, Sanamdikar Sanjay Tanaji6, Priya Ravindran7

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1939-1950, 2023, DOI:10.32604/csse.2023.026254

    Abstract Fuzzy sets have undergone several expansions and generalisations in the literature, including Atanasov’s intuitionistic fuzzy sets, type 2 fuzzy sets, and fuzzy multisets, to name a few. They can be regarded as fuzzy multisets from a formal standpoint; nevertheless, their interpretation differs from the two other approaches to fuzzy multisets that are currently available. Hesitating fuzzy sets (HFS) are very useful if consultants have hesitation in dealing with group decision-making problems between several possible memberships. However, these possible memberships can be not only crisp values in [0,1], but also interval values during a practical evaluation process. Hesitant bipolar valued fuzzy… More >

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