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  • Open Access

    ARTICLE

    A New Speed Limit Recognition Methodology Based on Ensemble Learning: Hardware Validation

    Mohamed Karray1,*, Nesrine Triki2,*, Mohamed Ksantini2

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 119-138, 2024, DOI:10.32604/cmc.2024.051562

    Abstract Advanced Driver Assistance Systems (ADAS) technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road. Traffic Sign Recognition System (TSRS) is one of the most important components of ADAS. Among the challenges with TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time. Accordingly, this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules. Firstly, the Speed Limit Detection (SLD) module uses… More >

  • Open Access

    ARTICLE

    Unweighted Voting Method to Detect Sinkhole Attack in RPL-Based Internet of Things Networks

    Shadi Al-Sarawi1, Mohammed Anbar1,*, Basim Ahmad Alabsi2, Mohammad Adnan Aladaileh3, Shaza Dawood Ahmed Rihan2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 491-515, 2023, DOI:10.32604/cmc.2023.041108

    Abstract The Internet of Things (IoT) consists of interconnected smart devices communicating and collecting data. The Routing Protocol for Low-Power and Lossy Networks (RPL) is the standard protocol for Internet Protocol Version 6 (IPv6) in the IoT. However, RPL is vulnerable to various attacks, including the sinkhole attack, which disrupts the network by manipulating routing information. This paper proposes the Unweighted Voting Method (UVM) for sinkhole node identification, utilizing three key behavioral indicators: DODAG Information Object (DIO) Transaction Frequency, Rank Harmony, and Power Consumption. These indicators have been carefully selected based on their contribution to sinkhole… More >

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