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  • Open Access

    ARTICLE

    Enhanced Metaheuristics with Machine Learning Enabled Cyberattack Detection Model

    Ahmed S. Almasoud*

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2849-2863, 2023, DOI:10.32604/iasc.2023.039718 - 11 September 2023

    Abstract The Internet of Things (IoT) is considered the next-gen connection network and is ubiquitous since it is based on the Internet. Intrusion Detection System (IDS) determines the intrusion performance of terminal equipment and IoT communication procedures from IoT environments after taking equivalent defence measures based on the identified behaviour. In this background, the current study develops an Enhanced Metaheuristics with Machine Learning enabled Cyberattack Detection and Classification (EMML-CADC) model in an IoT environment. The aim of the presented EMML-CADC model is to detect cyberattacks in IoT environments with enhanced efficiency. To attain this, the EMML-CADC… More >

  • Open Access

    ARTICLE

    Sand Cat Swarm Optimization with Deep Transfer Learning for Skin Cancer Classification

    C. S. S. Anupama1, Saud Yonbawi2, G. Jose Moses3, E. Laxmi Lydia4, Seifedine Kadry5,6,7, Jungeun Kim8,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2079-2095, 2023, DOI:10.32604/csse.2023.038322 - 28 July 2023

    Abstract Skin cancer is one of the most dangerous cancer. Because of the high melanoma death rate, skin cancer is divided into non-melanoma and melanoma. The dermatologist finds it difficult to identify skin cancer from dermoscopy images of skin lesions. Sometimes, pathology and biopsy examinations are required for cancer diagnosis. Earlier studies have formulated computer-based systems for detecting skin cancer from skin lesion images. With recent advancements in hardware and software technologies, deep learning (DL) has developed as a potential technique for feature learning. Therefore, this study develops a new sand cat swarm optimization with a… More >

  • Open Access

    ARTICLE

    Quantum Cat Swarm Optimization Based Clustering with Intrusion Detection Technique for Future Internet of Things Environment

    Mohammed Basheri, Mahmoud Ragab*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3783-3798, 2023, DOI:10.32604/csse.2023.037130 - 03 April 2023

    Abstract The Internet of Things (IoT) is one of the emergent technologies with advanced developments in several applications like creating smart environments, enabling Industry 4.0, etc. As IoT devices operate via an inbuilt and limited power supply, the effective utilization of available energy plays a vital role in designing the IoT environment. At the same time, the communication of IoT devices in wireless mediums poses security as a challenging issue. Recently, intrusion detection systems (IDS) have paved the way to detect the presence of intrusions in the IoT environment. With this motivation, this article introduces a… More >

  • Open Access

    ARTICLE

    Cat Swarm with Fuzzy Cognitive Maps for Automated Soil Classification

    Ashit Kumar Dutta1,*, Yasser Albagory2, Manal Al Faraj1, Majed Alsanea3, Abdul Rahaman Wahab Sait4

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1419-1432, 2023, DOI:10.32604/csse.2023.027377 - 15 June 2022

    Abstract Accurate soil prediction is a vital parameter involved to decide appropriate crop, which is commonly carried out by the farmers. Designing an automated soil prediction tool helps to considerably improve the efficacy of the farmers. At the same time, fuzzy logic (FL) approaches can be used for the design of predictive models, particularly, Fuzzy Cognitive Maps (FCMs) have involved the concept of uncertainty representation and cognitive mapping. In other words, the FCM is an integration of the recurrent neural network (RNN) and FL involved in the knowledge engineering phase. In this aspect, this paper introduces… More >

  • Open Access

    ARTICLE

    Covid-19 Forecasting with Deep Learning-based Half-binomial Distribution Cat Swarm Optimization

    P. Renukadevi1,*, A. Rajiv Kannan2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 629-645, 2023, DOI:10.32604/csse.2023.024217 - 01 June 2022

    Abstract About 170 nations have been affected by the COvid VIrus Disease-19 (COVID-19) epidemic. On governing bodies across the globe, a lot of stress is created by COVID-19 as there is a continuous rise in patient count testing positive, and they feel challenging to tackle this situation. Most researchers concentrate on COVID-19 data analysis using the machine learning paradigm in these situations. In the previous works, Long Short-Term Memory (LSTM) was used to predict future COVID-19 cases. According to LSTM network data, the outbreak is expected to finish by June 2020. However, there is a chance… More >

  • Open Access

    ARTICLE

    IoT Based Disease Prediction Using Mapreduce and LSQN3 Techniques

    R. Gopi1,*, S. Veena2, S. Balasubramanian3, D. Ramya4, P. Ilanchezhian5, A. Harshavardhan6, Zatin Gupta7

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1215-1230, 2022, DOI:10.32604/iasc.2022.025792 - 03 May 2022

    Abstract In this modern era, the transformation of conventional objects into smart ones via internet vitality, data management, together with many more are the main aim of the Internet of Things (IoT) centered Big Data (BD) analysis. In the past few years, significant augmentation in the IoT-centered Healthcare (HC) monitoring can be seen. Nevertheless, the merging of health-specific parameters along with IoT-centric Health Monitoring (HM) systems with BD handling ability is turned out to be a complicated research scope. With the aid of Map-Reduce and LSQN3 techniques, this paper proposed IoT devices in Wireless Sensors Networks (WSN)… More >

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