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  • Open Access

    ARTICLE

    Detection of Phishing in Internet-of-Things Using Hybrid Deep Belief Network

    S. Ashwini*, S. Magesh Kumar

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3043-3056, 2023, DOI:10.32604/iasc.2023.034551

    Abstract Increase in the use of internet of things owned devices is one of the reasons for increased network traffic. While connecting the smart devices with publicly available network many kinds of phishing attacks are able to enter into the mobile devices and corrupt the existing system. The Phishing is the slow and resilient attack stacking techniques probe the users. The proposed model is focused on detecting phishing attacks in internet of things enabled devices through a robust algorithm called Novel Watch and Trap Algorithm (NWAT). Though Predictive mapping, Predictive Validation and Predictive analysis mechanism is developed. For the test purpose… More >

  • Open Access

    ARTICLE

    Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

    Doaa Sami Khafaga1, Faten Khalid Karim1,*, Abdelaziz A. Abdelhamid2,3, El-Sayed M. El-kenawy4, Hend K. Alkahtani1, Nima Khodadadi5, Mohammed Hadwan6, Abdelhameed Ibrahim7

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3183-3198, 2023, DOI:10.32604/cmc.2023.033513

    Abstract Managing physical objects in the network’s periphery is made possible by the Internet of Things (IoT), revolutionizing human life. Open attacks and unauthorized access are possible with these IoT devices, which exchange data to enable remote access. These attacks are often detected using intrusion detection methodologies, although these systems’ effectiveness and accuracy are subpar. This paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic optimization. The employed metaheuristic optimizer is a new version of the whale optimization algorithm (WOA), which is guided by the dipper throated optimizer (DTO) to improve… More >

  • Open Access

    ARTICLE

    Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

    Reem Alkanhel1, El-Sayed M. El-kenawy2, Abdelaziz A. Abdelhamid3,4, Abdelhameed Ibrahim5, Manal Abdullah Alohali6, Mostafa Abotaleb7, Doaa Sami Khafaga8,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2677-2693, 2023, DOI:10.32604/cmc.2023.033273

    Abstract Applications of internet-of-things (IoT) are increasingly being used in many facets of our daily life, which results in an enormous volume of data. Cloud computing and fog computing, two of the most common technologies used in IoT applications, have led to major security concerns. Cyberattacks are on the rise as a result of the usage of these technologies since present security measures are insufficient. Several artificial intelligence (AI) based security solutions, such as intrusion detection systems (IDS), have been proposed in recent years. Intelligent technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection… More >

  • Open Access

    ARTICLE

    Logistic Regression Trust–A Trust Model for Internet-of-Things Using Regression Analysis

    Feslin Anish Mon Solomon1,*, Godfrey Winster Sathianesan2, R. Ramesh3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1125-1142, 2023, DOI:10.32604/csse.2023.024292

    Abstract Internet of Things (IoT) is a popular social network in which devices are virtually connected for communicating and sharing information. This is applied greatly in business enterprises and government sectors for delivering the services to their customers, clients and citizens. But, the interaction is successful only based on the trust that each device has on another. Thus trust is very much essential for a social network. As Internet of Things have access over sensitive information, it urges to many threats that lead data management to risk. This issue is addressed by trust management that help to take decision about trustworthiness… More >

  • Open Access

    ARTICLE

    Performance Evaluation of Topological Infrastructure in Internet-of-Things-Enabled Serious Games

    Shabir Ahmad, Faheem Khan, Taeg Keun Whangbo*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2653-2666, 2022, DOI:10.32604/cmc.2022.022821

    Abstract Serious games have recently enticed many researchers due to their wide range of capabilities. A serious game is a mean of gaming for a serious job such as healthcare, education, and entertainment purposes. With the advancement in the Internet of Things, new research directions are paving the way in serious games. However, the internet connectivity of players in Internet-of-things-enabled serious games is a matter of concern and has been worth investigating. Different studies on topologies, frameworks, and architecture of communication technologies are conducted to integrate them with serious games on machine and network levels. However, the Internet of things, whose… More >

  • Open Access

    ARTICLE

    Security Empowered System-on-Chip Selection for Internet of Things

    Ramesh Krishnamoorthy*, Kalimuthu Krishnan

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 403-418, 2021, DOI:10.32604/iasc.2021.018560

    Abstract Due to the rapid growth of embedded devices, the selection of System-on-Chip (SoC) has a stronger influence to enable hardware security in embedded system design. System-on-chip (SoC) devices consist of one or more CPUs through wide-ranging inbuilt peripherals for designing a system with less cost. The selection of SoC is more significant to determine the suitability for secured application development. The design space analysis of symmetric key approaches including rivest cipher (RC5), advanced encryption standard (AES), data encryption standard (DES), international data encryption algorithm (IDEA), elliptic curve cryptography (ECC), MX algorithm, and the secure hash algorithm (SHA-256) are compared to… More >

  • Open Access

    ARTICLE

    A Trusted NUMFabric Algorithm for Congestion Price Calculation at the Internet-of-Things Datacenter

    Shan Chun1, Xiaolong Chen2, Guoqiang Deng3,*, Hao Liu4

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1203-1216, 2021, DOI:10.32604/cmes.2021.012230

    Abstract The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information. However, it is difficult to predict the congestion state of the link-end accurately at the source. In this paper, we presented an improved NUMFabric algorithm for calculating the overall congestion price. In the proposed scheme, the whole network structure had been obtained by the central control server in the Software Defined Network, and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated.… More >

  • Open Access

    ARTICLE

    Roughsets-based Approach for Predicting Battery Life in IoT

    Rajesh Kaluri1, Dharmendra Singh Rajput1, Qin Xin2,*, Kuruva Lakshmanna1, Sweta Bhattacharya1, Thippa Reddy Gadekallu1, Praveen Kumar Reddy Maddikunta1

    Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 453-469, 2021, DOI:10.32604/iasc.2021.014369

    Abstract Internet of Things (IoT) and related applications have successfully contributed towards enhancing the value of life in this planet. The advanced wireless sensor networks and its revolutionary computational capabilities have enabled various IoT applications become the next frontier, touching almost all domains of life. With this enormous progress, energy optimization has also become a primary concern with the need to attend to green technologies. The present study focuses on the predictions pertinent to the sustainability of battery life in IoT frameworks in the marine environment. The data used is a publicly available dataset collected from the Chicago district beach water.… More >

  • Open Access

    ARTICLE

    A Model Transformation Approach for Detecting Distancing Violations in Weighted Graphs

    Ahmad F. Subahi*

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 13-39, 2021, DOI:10.32604/csse.2021.014376

    Abstract This work presents the design of an Internet of Things (IoT) edge-based system based on model transformation and complete weighted graph to detect violations of social distancing measures in indoor public places. A wireless sensor network based on Bluetooth Low Energy is introduced as the infrastructure of the proposed design. A hybrid model transformation strategy for generating a graph database to represent groups of people is presented as a core middleware layer of the detecting system’s proposed architectural design. A Neo4j graph database is used as a target implementation generated from the proposed transformational system to store all captured real-time… More >

  • Open Access

    ARTICLE

    A Distributed ADMM Approach for Collaborative Regression Learning in Edge Computing

    Yangyang Li1, Xue Wang2, Weiwei Fang2,*, Feng Xue2, Hao Jin1, Yi Zhang1, Xianwei Li3

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 493-508, 2019, DOI:10.32604/cmc.2019.05178

    Abstract With the recent proliferation of Internet-of-Things (IoT), enormous amount of data are produced by wireless sensors and connected devices at the edge of network. Conventional cloud computing raises serious concerns on communication latency, bandwidth cost, and data privacy. To address these issues, edge computing has been introduced as a new paradigm that allows computation and analysis to be performed in close proximity with data sources. In this paper, we study how to conduct regression analysis when the training samples are kept private at source devices. Specifically, we consider the lasso regression model that has been widely adopted for prediction and… More >

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