Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (587)
  • Open Access

    ARTICLE

    Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

    Altaf Hussain1, Shuaiyong Li2, Tariq Hussain3, Razaz Waheeb Attar4, Farman Ali5,*, Ahmed Alhomoud6, Babar Shah7

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2357-2394, 2024, DOI:10.32604/cmc.2024.056694 - 18 November 2024

    Abstract Ad hoc networks offer promising applications due to their ease of use, installation, and deployment, as they do not require a centralized control entity. In these networks, nodes function as senders, receivers, and routers. One such network is the Flying Ad hoc Network (FANET), where nodes operate in three dimensions (3D) using Unmanned Aerial Vehicles (UAVs) that are remotely controlled. With the integration of the Internet of Things (IoT), these nodes form an IoT-enabled network called the Internet of UAVs (IoU). However, the airborne nodes in FANET consume high energy due to their payloads and… More >

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation

    Ilsun You1,*, Xiaofeng Chen2, Vishal Sharma3, Gaurav Choudhary4

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 1907-1909, 2024, DOI:10.32604/cmes.2024.058939 - 31 October 2024

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Augmenting Internet of Medical Things Security: Deep Ensemble Integration and Methodological Fusion

    Hamad Naeem1, Amjad Alsirhani2,*, Faeiz M. Alserhani3, Farhan Ullah4, Ondrej Krejcar1

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2185-2223, 2024, DOI:10.32604/cmes.2024.056308 - 31 October 2024

    Abstract When it comes to smart healthcare business systems, network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network assaults. To protect IoMT devices and networks in healthcare and medical settings, our proposed model serves as a powerful tool for monitoring IoMT networks. This study presents a robust methodology for intrusion detection in Internet of Medical Things (IoMT) environments, integrating data augmentation, feature selection, and ensemble learning to effectively handle IoMT data complexity. Following rigorous preprocessing, including feature extraction, correlation removal, and Recursive Feature Elimination (RFE), selected features are standardized… More >

  • Open Access

    ARTICLE

    Deep Learning-Driven Anomaly Detection for IoMT-Based Smart Healthcare Systems

    Attiya Khan1, Muhammad Rizwan2, Ovidiu Bagdasar2,3, Abdulatif Alabdulatif4,*, Sulaiman Alamro4, Abdullah Alnajim5

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2121-2141, 2024, DOI:10.32604/cmes.2024.054380 - 31 October 2024

    Abstract The Internet of Medical Things (IoMT) is an emerging technology that combines the Internet of Things (IoT) into the healthcare sector, which brings remarkable benefits to facilitate remote patient monitoring and reduce treatment costs. As IoMT devices become more scalable, Smart Healthcare Systems (SHS) have become increasingly vulnerable to cyberattacks. Intrusion Detection Systems (IDS) play a crucial role in maintaining network security. An IDS monitors systems or networks for suspicious activities or potential threats, safeguarding internal networks. This paper presents the development of an IDS based on deep learning techniques utilizing benchmark datasets. We propose More >

  • Open Access

    ARTICLE

    Privacy-Preserving and Lightweight V2I and V2V Authentication Protocol Using Blockchain Technology

    Muhammad Imran Ghafoor1, Awad Bin Naeem2,*, Biswaranjan Senapati3, Md. Sakiul Islam Sudman4, Satyabrata Pradhan5, Debabrata Das6, Friban Almeida6, Hesham A. Sakr7

    Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 783-803, 2024, DOI:10.32604/iasc.2024.050819 - 31 October 2024

    Abstract The confidentiality of pseudonymous authentication and secure data transmission is essential for the protection of information and mitigating risks posed by compromised vehicles. The Internet of Vehicles has meaningful applications, enabling connected and autonomous vehicles to interact with infrastructure, sensors, computing nodes, humans, and fellow vehicles. Vehicular hoc networks play an essential role in enhancing driving efficiency and safety by reducing traffic congestion while adhering to cryptographic security standards. This paper introduces a privacy-preserving Vehicle-to-Infrastructure authentication, utilizing encryption and the Moore curve. The proposed approach enables a vehicle to deduce the planned itinerary of Roadside More >

  • Open Access

    ARTICLE

    Optimizing Internet of Things Device Security with a Globalized Firefly Optimization Algorithm for Attack Detection

    Arkan Kh Shakr Sabonchi*

    Journal on Artificial Intelligence, Vol.6, pp. 261-282, 2024, DOI:10.32604/jai.2024.056552 - 18 October 2024

    Abstract The phenomenal increase in device connectivity is making the signaling and resource-based operational integrity of networks at the node level increasingly prone to distributed denial of service (DDoS) attacks. The current growth rate in the number of Internet of Things (IoT) attacks executed at the time of exchanging data over the Internet represents massive security hazards to IoT devices. In this regard, the present study proposes a new hybrid optimization technique that combines the firefly optimization algorithm with global searches for use in attack detection on IoT devices. We preprocessed two datasets, CICIDS and UNSW-NB15,… More >

  • Open Access

    ARTICLE

    V2I Physical Layer Security Beamforming with Antenna Hardware Impairments under RIS Assistance

    Zerong Tang, Tiecheng Song*, Jing Hu

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1835-1854, 2024, DOI:10.32604/cmc.2024.056983 - 15 October 2024

    Abstract The Internet of Vehicles (IoV) will carry a large amount of security and privacy-related data, which makes the secure communication between the IoV terminals increasingly critical. This paper studies the joint beamforming for physical-layer security transmission in the coexistence of Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communication with Reconfigurable Intelligent Surface (RIS) assistance, taking into account hardware impairments. A communication model for physical-layer security transmission is established when the eavesdropping user is present and the base station antenna has hardware impairments assisted by RIS. Based on this model, we propose to maximize the V2I physical-layer security… More >

  • Open Access

    ARTICLE

    Computation Offloading in Edge Computing for Internet of Vehicles via Game Theory

    Jianhua Liu*, Jincheng Wei, Rongxin Luo, Guilin Yuan, Jiajia Liu, Xiaoguang Tu

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1337-1361, 2024, DOI:10.32604/cmc.2024.056286 - 15 October 2024

    Abstract With the rapid advancement of Internet of Vehicles (IoV) technology, the demands for real-time navigation, advanced driver-assistance systems (ADAS), vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, and multimedia entertainment systems have made in-vehicle applications increasingly computing-intensive and delay-sensitive. These applications require significant computing resources, which can overwhelm the limited computing capabilities of vehicle terminals despite advancements in computing hardware due to the complexity of tasks, energy consumption, and cost constraints. To address this issue in IoV-based edge computing, particularly in scenarios where available computing resources in vehicles are scarce, a multi-master and multi-slave double-layer game model More >

  • Open Access

    ARTICLE

    Blockchain-Enabled Federated Learning with Differential Privacy for Internet of Vehicles

    Chi Cui1,2, Haiping Du2, Zhijuan Jia1,*, Yuchu He1, Lipeng Wang1

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1581-1593, 2024, DOI:10.32604/cmc.2024.055557 - 15 October 2024

    Abstract The rapid evolution of artificial intelligence (AI) technologies has significantly propelled the advancement of the Internet of Vehicles (IoV). With AI support, represented by machine learning technology, vehicles gain the capability to make intelligent decisions. As a distributed learning paradigm, federated learning (FL) has emerged as a preferred solution in IoV. Compared to traditional centralized machine learning, FL reduces communication overhead and improves privacy protection. Despite these benefits, FL still faces some security and privacy concerns, such as poisoning attacks and inference attacks, prompting exploration into blockchain integration to enhance its security posture. This paper… More >

  • Open Access

    REVIEW

    Internet Inter-Domain Path Inferring: Methods, Applications, and Future Directions

    Xionglve Li, Chengyu Wang, Yifan Yang, Changsheng Hou, Bingnan Hou, Zhiping Cai*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 53-78, 2024, DOI:10.32604/cmc.2024.055186 - 15 October 2024

    Abstract The global Internet is a complex network of interconnected autonomous systems (ASes). Understanding Internet inter-domain path information is crucial for understanding, managing, and improving the Internet. The path information can also help protect user privacy and security. However, due to the complicated and heterogeneous structure of the Internet, path information is not publicly available. Obtaining path information is challenging due to the limited measurement probes and collectors. Therefore, inferring Internet inter-domain paths from the limited data is a supplementary approach to measure Internet inter-domain paths. The purpose of this survey is to provide an overview… More >

Displaying 1-10 on page 1 of 587. Per Page