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  • Open Access


    Internet of Things (IoT) Security Enhancement Using XGboost Machine Learning Techniques

    Dana F. Doghramachi1,*, Siddeeq Y. Ameen2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 717-732, 2023, DOI:10.32604/cmc.2023.041186

    Abstract The rapid adoption of the Internet of Things (IoT) across industries has revolutionized daily life by providing essential services and leisure activities. However, the inadequate software protection in IoT devices exposes them to cyberattacks with severe consequences. Intrusion Detection Systems (IDS) are vital in mitigating these risks by detecting abnormal network behavior and monitoring safe network traffic. The security research community has shown particular interest in leveraging Machine Learning (ML) approaches to develop practical IDS applications for general cyber networks and IoT environments. However, most available datasets related to Industrial IoT suffer from imbalanced class distributions. This study proposes a… More >

  • Open Access


    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 attack detection and other relevant… More >

  • Open Access


    Collaborative Detection and Prevention of Sybil Attacks against RPL-Based Internet of Things

    Muhammad Ali Khan1, Rao Naveed Bin Rais2,*, Osman Khalid1

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 827-843, 2023, DOI:10.32604/cmc.2023.040756

    Abstract The Internet of Things (IoT) comprises numerous resource-constrained devices that generate large volumes of data. The inherent vulnerabilities in IoT infrastructure, such as easily spoofed IP and MAC addresses, pose significant security challenges. Traditional routing protocols designed for wired or wireless networks may not be suitable for IoT networks due to their limitations. Therefore, the Routing Protocol for Low-Power and Lossy Networks (RPL) is widely used in IoT systems. However, the built-in security mechanism of RPL is inadequate in defending against sophisticated routing attacks, including Sybil attacks. To address these issues, this paper proposes a centralized and collaborative approach for… More >

  • Open Access


    Intelligent Service Search Model Using Emerging Technologies

    Farhan Amin, Gyu Sang Choi*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1165-1181, 2023, DOI:10.32604/cmc.2023.040693

    Abstract In recent years, the Internet of Things (IoT) has played a vital role in providing various services to users in a smart city. However, searching for services, objects, data, and frameworks remains a concern. The technological advancements in Cyber-Physical Systems (CPSs) and the Social Internet of Things (SIoT) open a new era of research. Thus, we propose a Cyber-Physical-Social Systems (CPSs) for service search. Herein, service search and object discovery operation carries with the suitable selection of friends in the network. Our proposed model constructs a graph and performs social network analysis (SNA). We suggest degree centrality, clustering, and scale-free… More >

  • Open Access


    NPBMT: A Novel and Proficient Buffer Management Technique for Internet of Vehicle-Based DTNs

    Sikandar Khan1, Khalid Saeed1, Muhammad Faran Majeed2,*, Salman A. AlQahtani3, Khursheed Aurangzeb3, Muhammad Shahid Anwar4,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1303-1323, 2023, DOI:10.32604/cmc.2023.039697

    Abstract Delay Tolerant Networks (DTNs) have the major problem of message delay in the network due to a lack of end-to-end connectivity between the nodes, especially when the nodes are mobile. The nodes in DTNs have limited buffer storage for storing delayed messages. This instantaneous sharing of data creates a low buffer/shortage problem. Consequently, buffer congestion would occur and there would be no more space available in the buffer for the upcoming messages. To address this problem a buffer management policy is proposed named “A Novel and Proficient Buffer Management Technique (NPBMT) for the Internet of Vehicle-Based DTNs”. NPBMT combines appropriate-size… More >

  • Open Access


    Adaptive Momentum-Backpropagation Algorithm for Flood Prediction and Management in the Internet of Things

    Jayaraj Thankappan1, Delphin Raj Kesari Mary2, Dong Jin Yoon3, Soo-Hyun Park4,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1053-1079, 2023, DOI:10.32604/cmc.2023.038437

    Abstract Flooding is a hazardous natural calamity that causes significant damage to lives and infrastructure in the real world. Therefore, timely and accurate decision-making is essential for mitigating flood-related damages. The traditional flood prediction techniques often encounter challenges in accuracy, timeliness, complexity in handling dynamic flood patterns and leading to substandard flood management strategies. To address these challenges, there is a need for advanced machine learning models that can effectively analyze Internet of Things (IoT)-generated flood data and provide timely and accurate flood predictions. This paper proposes a novel approach-the Adaptive Momentum and Backpropagation (AM-BP) algorithm-for flood prediction and management in… More >

  • Open Access


    Binary Oriented Feature Selection for Valid Product Derivation in Software Product Line

    Muhammad Fezan Afzal1, Imran Khan1, Javed Rashid1,2,3, Mubbashar Saddique4,*, Heba G. Mohamed5

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3653-3670, 2023, DOI:10.32604/cmc.2023.041627

    Abstract Software Product Line (SPL) is a group of software-intensive systems that share common and variable resources for developing a particular system. The feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints (CTC). CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things (IoT) devices because different Internet devices and protocols are communicated. Therefore, managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex, time-consuming, and hard. However, the CTC… More >

  • Open Access


    Malicious Traffic Compression and Classification Technique for Secure Internet of Things

    Yu-Rim Lee1, Na-Eun Park1, Seo-Yi Kim2, Il-Gu Lee1,2,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3465-3482, 2023, DOI:10.32604/cmc.2023.041196

    Abstract With the introduction of 5G technology, the application of Internet of Things (IoT) devices is expanding to various industrial fields. However, introducing a robust, lightweight, low-cost, and low-power security solution to the IoT environment is challenging. Therefore, this study proposes two methods using a data compression technique to detect malicious traffic efficiently and accurately for a secure IoT environment. The first method, compressed sensing and learning (CSL), compresses an event log in a bitmap format to quickly detect attacks. Then, the attack log is detected using a machine-learning classification model. The second method, precise re-learning after CSL (Ra-CSL), comprises a… More >

  • Open Access


    Reliability Analysis of Correlated Competitive and Dependent Components Considering Random Isolation Times

    Shuo Cai1, Tingyu Luo1, Fei Yu1,*, Pradip Kumar Sharma2, Weizheng Wang1, Lairong Yin3

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2763-2777, 2023, DOI:10.32604/cmc.2023.037825

    Abstract In the Internet of Things (IoT) system, relay communication is widely used to solve the problem of energy loss in long-distance transmission and improve transmission efficiency. In Body Sensor Network (BSN) systems, biosensors communicate with receiving devices through relay nodes to improve their limited energy efficiency. When the relay node fails, the biosensor can communicate directly with the receiving device by releasing more transmitting power. However, if the remaining battery power of the biosensor is insufficient to enable it to communicate directly with the receiving device, the biosensor will be isolated by the system. Therefore, a new combinatorial analysis method… More >

  • Open Access


    The Sav-AQ Project: Study of Obstacles and Levers Related to the Use of a Website Dedicated to Breast Cancer Patients; the Example of the Nouvelle-Aquitaine Region

    Le projet Sav-AQ : étude des freins et facteurs à l’utilisation d’un site internet dédié aux patientes atteintes de cancer du sein, l’exemple de la Nouvelle-Aquitaine

    Valérie Berger1,2,*, Hélène Hoarau1,2, Florence Saillour3,4

    Psycho-Oncologie, Vol.17, No.3, pp. 159-166, 2023, DOI:10.32604/po.2023.044727

    Abstract The development of digital platforms is transforming caregiver-patient interactions and the dissemination of knowledge. Obtaining information from the Internet has become a habit for many patients and must be considered by caregivers. Thus, understanding the use of digital tools by patients is a public health issue. The Sav-AQ study aims to understand patterns of use by women with breast cancer and the role of health professionals. Sav-AQ is an exploratory feasibility study with a mixed design, exploring patient and healthcare experience before and after the integration of a specific website into their care pathways. The research is based on the… More >

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