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  • Open Access

    ARTICLE

    Network Intrusion Detection in Internet of Blended Environment Using Ensemble of Heterogeneous Autoencoders (E-HAE)

    Lelisa Adeba Jilcha1, Deuk-Hun Kim2, Julian Jang-Jaccard3, Jin Kwak4,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3261-3284, 2023, DOI:10.32604/csse.2023.037615

    Abstract Contemporary attackers, mainly motivated by financial gain, consistently devise sophisticated penetration techniques to access important information or data. The growing use of Internet of Things (IoT) technology in the contemporary convergence environment to connect to corporate networks and cloud-based applications only worsens this situation, as it facilitates multiple new attack vectors to emerge effortlessly. As such, existing intrusion detection systems suffer from performance degradation mainly because of insufficient considerations and poorly modeled detection systems. To address this problem, we designed a blended threat detection approach, considering the possible impact and dimensionality of new attack surfaces due to the aforementioned convergence.… More >

  • Open Access

    ARTICLE

    Intelligent System Application to Monitor the Smart City Building Lighting

    Tzu-Chia Chen1, Ngakan Ketut Acwin Dwijendra2,*, Saurabh Singhal3, R. Sivaraman4, Amr Mamdouh5

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3159-3169, 2023, DOI:10.32604/cmc.2023.035418

    Abstract A smart city incorporates infrastructure methods that are environmentally responsible, such as smart communications, smart grids, smart energy, and smart buildings. The city administration has prioritized the use of cutting-edge technology and informatics as the primary strategy for enhancing service quality, with energy resources taking precedence. To achieve optimal energy management in the multidimensional system of a city tribe, it is necessary not only to identify and study the vast majority of energy elements, but also to define their implicit interdependencies. This is because optimal energy management is required to reach this objective. The lighting index is an essential consideration… More >

  • Open Access

    ARTICLE

    Deep Consensus Network for Recycling Waste Detection in Smart Cities

    Manar Ahmed Hamza1,*, Hanan Abdullah Mengash2, Noha Negm3, Radwa Marzouk2, Abdelwahed Motwakel1, Abu Sarwar Zamani1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4191-4205, 2023, DOI:10.32604/cmc.2023.027050

    Abstract Recently, urbanization becomes a major concern for developing as well as developed countries. Owing to the increased urbanization, one of the important challenging issues in smart cities is waste management. So, automated waste detection and classification model becomes necessary for the smart city and to accomplish better recyclable waste management. Effective recycling of waste offers the chance of reducing the quantity of waste disposed to the land fill by minimizing the requirement of collecting raw materials. This study develops a novel Deep Consensus Network with Whale Optimization Algorithm for Recycling Waste Object Detection (DCNWO-RWOD) in Smart Cities. The goal of… More >

  • Open Access

    REVIEW

    Modeling Methods of 3D Model in Digital Twins

    Ruijun Liu1, Haisheng Li1,*, Zhihan Lv2

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 985-1022, 2023, DOI:10.32604/cmes.2023.023154

    Abstract To understand the current application and development of 3D modeling in Digital Twins (DTs), abundant literatures on DTs and 3D modeling are investigated by means of literature review. The transition process from 3D modeling to DTs modeling is analyzed, as well as the current application of DTs modeling in various industries. The application of 3D DTs modeling in the fields of smart manufacturing, smart ecology, smart transportation, and smart buildings in smart cities is analyzed in detail, and the current limitations are summarized. It is found that the 3D modeling technology in DTs has broad prospects for development and has… More >

  • Open Access

    ARTICLE

    The Role of Deep Learning in Parking Space Identification and Prediction Systems

    Faizan Rasheed1, Yasir Saleem2, Kok-Lim Alvin Yau3,*, Yung-Wey Chong4,*, Sye Loong Keoh5

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 761-784, 2023, DOI:10.32604/cmc.2023.034988

    Abstract In today’s smart city transportation, traffic congestion is a vexing issue, and vehicles seeking parking spaces have been identified as one of the causes leading to approximately 40% of traffic congestion. Identifying parking spaces alone is insufficient because an identified available parking space may have been taken by another vehicle when it arrives, resulting in the driver’s frustration and aggravating traffic jams while searching for another parking space. This explains the need to predict the availability of parking spaces. Recently, deep learning (DL) has been shown to facilitate drivers to find parking spaces efficiently, leading to a promising performance enhancement… More >

  • Open Access

    ARTICLE

    Deep Learning Implemented Visualizing City Cleanliness Level by Garbage Detection

    M. S. Vivekanandan1, T. Jesudas2,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1639-1652, 2023, DOI:10.32604/iasc.2023.032301

    Abstract In an urban city, the daily challenges of managing cleanliness are the primary aspect of routine life, which requires a large number of resources, the manual process of labour, and budget. Street cleaning techniques include street sweepers going away to different metropolitan areas, manually verifying if the street required cleaning taking action. This research presents novel street garbage recognizing robotic navigation techniques by detecting the city’s street-level images and multi-level segmentation. For the large volume of the process, the deep learning-based methods can be better to achieve a high level of classification, object detection, and accuracy than other learning algorithms.… More >

  • Open Access

    ARTICLE

    Resilient Service Authentication for Smart City Application Using IoT

    Gokulakannan Elamparithi*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 145-152, 2023, DOI:10.32604/iasc.2023.032036

    Abstract Internet of Things (IoT) support for smart city systems improves service scales by ignoring various user congestion. People are looking for different security features for reliable and robust applications. Here, the Permanent Denial of Service (PDoS) problem arises from improper user identification. This article introduces the Service-Reliant Application Authentication (SRAA) to prevent PDoS attacks in a smart area of the city. In this authentication method, the security of the application is ensured through the distribution of guarded access. The supervised access distribution uses user interface features and sync with the user device. Abnormality in linking user device, application, and authentication… More >

  • Open Access

    ARTICLE

    A Cross-Domain Trust Model of Smart City IoT Based on Self-Certification

    Yao Wang1, Yubo Wang1, Zhenhu Ning1,*, Sadaqat ur Rehman2, Muhammad Waqas1,3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 981-996, 2023, DOI:10.32604/iasc.2023.030091

    Abstract Smart city refers to the information system with Internet of things and cloud computing as the core technology and government management and industrial development as the core content, forming a large-scale, heterogeneous and dynamic distributed Internet of things environment between different Internet of things. There is a wide demand for cooperation between equipment and management institutions in the smart city. Therefore, it is necessary to establish a trust mechanism to promote cooperation, and based on this, prevent data disorder caused by the interaction between honest terminals and malicious terminals. However, most of the existing research on trust mechanism is divorced… More >

  • Open Access

    ARTICLE

    Privacy Preserving Blockchain with Optimal Deep Learning Model for Smart Cities

    K. Pradeep Mohan Kumar1, Jenifer Mahilraj2, D. Swathi3, R. Rajavarman4, Subhi R. M. Zeebaree5, Rizgar R. Zebari6, Zryan Najat Rashid7, Ahmed Alkhayyat8,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5299-5314, 2022, DOI:10.32604/cmc.2022.030825

    Abstract Recently, smart cities have emerged as an effective approach to deliver high-quality services to the people through adaptive optimization of the available resources. Despite the advantages of smart cities, security remains a huge challenge to be overcome. Simultaneously, Intrusion Detection System (IDS) is the most proficient tool to accomplish security in this scenario. Besides, blockchain exhibits significance in promoting smart city designing, due to its effective characteristics like immutability, transparency, and decentralization. In order to address the security problems in smart cities, the current study designs a Privacy Preserving Secure Framework using Blockchain with Optimal Deep Learning (PPSF-BODL) model. The… More >

  • Open Access

    ARTICLE

    Foundation Treatment in Urban Underground Engineering Using Big Data Analysis for Smart City Applications

    Fei Liu1,2, Yunkai Zhang1,2, Jian Zhang3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 153-172, 2022, DOI:10.32604/cmes.2022.017967

    Abstract A core element of the sustainable approach to global living quality improvement can now become the intensive and organized usage of underground space. There is a growing interest in underground building and growth worldwide. The reduced consumption of electricity, effective preservation of green land, sustainable wastewater and sewage treatment, efficient reverse degradation of the urban environment, and reliable critical infrastructure management can improve the quality of life. At the same time, technological innovations such as artificial intelligence (AI), cloud computing (CC), the internet of things (IoT), and big data analytics (BDA) play a significant role in improved quality of life.… More >

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