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  • Open Access

    ARTICLE

    Machine Learning Approaches to Detect DoS and Their Effect on WSNs Lifetime

    Raniyah Wazirali1, Rami Ahmad2,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4922-4946, 2022, DOI:10.32604/cmc.2022.020044 - 11 October 2021

    Abstract Energy and security remain the main two challenges in Wireless Sensor Networks (WSNs). Therefore, protecting these WSN networks from Denial of Service (DoS) and Distributed DoS (DDoS) is one of the WSN networks security tasks. Traditional packet deep scan systems that rely on open field inspection in transport layer security packets and the open field encryption trend are making machine learning-based systems the only viable choice for these types of attacks. This paper contributes to the evaluation of the use machine learning algorithms in WSN nodes traffic and their effect on WSN network life time.… More >

  • Open Access

    ARTICLE

    Fuzzy Based Latent Dirichlet Allocation for Intrusion Detection in Cloud Using ML

    S. Ranjithkumar1,*, S. Chenthur Pandian2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4261-4277, 2022, DOI:10.32604/cmc.2022.019031 - 11 October 2021

    Abstract The growth of cloud in modern technology is drastic by provisioning services to various industries where data security is considered to be common issue that influences the intrusion detection system (IDS). IDS are considered as an essential factor to fulfill security requirements. Recently, there are diverse Machine Learning (ML) approaches that are used for modeling effectual IDS. Most IDS are based on ML techniques and categorized as supervised and unsupervised. However, IDS with supervised learning is based on labeled data. This is considered as a common drawback and it fails to identify the attack patterns.… More >

  • Open Access

    ARTICLE

    Industrial Datasets with ICS Testbed and Attack Detection Using Machine Learning Techniques

    Sinil Mubarak1, Mohamed Hadi Habaebi1,*, Md Rafiqul Islam1, Asaad Balla1, Mohammad Tahir2, Elfatih A. A. Elsheikh3, F. M. Suliman3

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1345-1360, 2022, DOI:10.32604/iasc.2022.020801 - 09 October 2021

    Abstract Industrial control systems (ICS) are the backbone for the implementation of cybersecurity solutions. They are susceptible to various attacks, due to openness in connectivity, unauthorized attempts, malicious attacks, use of more commercial off the shelf (COTS) software and hardware, and implementation of Internet protocols (IP) that exposes them to the outside world. Cybersecurity solutions for Information technology (IT) secured with firewalls, intrusion detection/protection systems do nothing much for Operational technology (OT) ICS. An innovative concept of using real operational technology network traffic-based testbed, for cyber-physical system simulation and analysis, is presented. The testbed is equipped… More >

  • Open Access

    ARTICLE

    Efficient Autonomous Defense System Using Machine Learning on Edge Device

    Jaehyuk Cho*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3565-3588, 2022, DOI:10.32604/cmc.2022.020826 - 27 September 2021

    Abstract As a large amount of data needs to be processed and speed needs to be improved, edge computing with ultra-low latency and ultra-connectivity is emerging as a new paradigm. These changes can lead to new cyber risks, and should therefore be considered for a security threat model. To this end, we constructed an edge system to study security in two directions, hardware and software. First, on the hardware side, we want to autonomically defend against hardware attacks such as side channel attacks by configuring field programmable gate array (FPGA) which is suitable for edge computing… More >

  • Open Access

    ARTICLE

    Data Fusion-Based Machine Learning Architecture for Intrusion Detection

    Muhammad Adnan Khan, Taher M. Ghazal2,3, Sang-Woong Lee1,*, Abdur Rehman4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3399-3413, 2022, DOI:10.32604/cmc.2022.020173 - 27 September 2021

    Abstract In recent years, the infrastructure of Wireless Internet of Sensor Networks (WIoSNs) has been more complicated owing to developments in the internet and devices’ connectivity. To effectively prepare, control, hold and optimize wireless sensor networks, a better assessment needs to be conducted. The field of artificial intelligence has made a great deal of progress with deep learning systems and these techniques have been used for data analysis. This study investigates the methodology of Real Time Sequential Deep Extreme Learning Machine (RTS-DELM) implemented to wireless Internet of Things (IoT) enabled sensor networks for the detection of… More >

  • Open Access

    ARTICLE

    Optimal Deep Reinforcement Learning for Intrusion Detection in UAVs

    V. Praveena1, A. Vijayaraj2, P. Chinnasamy3, Ihsan Ali4,*, Roobaea Alroobaea5, Saleh Yahya Alyahyan6, Muhammad Ahsan Raza7

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2639-2653, 2022, DOI:10.32604/cmc.2022.020066 - 27 September 2021

    Abstract In recent years, progressive developments have been observed in recent technologies and the production cost has been continuously decreasing. In such scenario, Internet of Things (IoT) network which is comprised of a set of Unmanned Aerial Vehicles (UAV), has received more attention from civilian to military applications. But network security poses a serious challenge to UAV networks whereas the intrusion detection system (IDS) is found to be an effective process to secure the UAV networks. Classical IDSs are not adequate to handle the latest computer networks that possess maximum bandwidth and data traffic. In order… More >

  • Open Access

    ARTICLE

    Blockchain-Based SQKD and IDS in Edge Enabled Smart Grid Network

    Abdullah Musaed Alkhiari1, Shailendra Mishra2,*, Mohammed AlShehri1

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2149-2169, 2022, DOI:10.32604/cmc.2022.019562 - 27 September 2021

    Abstract Smart Grid is a power grid that improves flexibility, reliability, and efficiency through smart meters. Due to extensive data exchange over the Internet, the smart grid faces many security challenges that have led to data loss, data compromise, and high power consumption. Moreover, the lack of hardware protection and physical attacks reduce the overall performance of the smart grid network. We proposed the BLIDSE model (Blockchain-based secure quantum key distribution and Intrusion Detection System in Edge Enables Smart Grid Network) to address these issues. The proposed model includes five phases: The first phase is blockchain-based… More >

  • Open Access

    ARTICLE

    Cross-Layer Hidden Markov Analysis for Intrusion Detection

    K. Venkatachalam1, P. Prabu2, B. Saravana Balaji3, Byeong-Gwon Kang4, Yunyoung Nam4,*, Mohamed Abouhawwash5,6

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3685-3700, 2022, DOI:10.32604/cmc.2022.019502 - 27 September 2021

    Abstract Ad hoc mobile cloud computing networks are affected by various issues, like delay, energy consumption, flexibility, infrastructure, network lifetime, security, stability, data transition, and link accomplishment. Given the issues above, route failure is prevalent in ad hoc mobile cloud computing networks, which increases energy consumption and delay and reduces stability. These issues may affect several interconnected nodes in an ad hoc mobile cloud computing network. To address these weaknesses, which raise many concerns about privacy and security, this study formulated clustering-based storage and search optimization approaches using cross-layer analysis. The proposed approaches were formed by cross-layer analysis based… More >

  • Open Access

    ARTICLE

    IoT Wireless Intrusion Detection and Network Traffic Analysis

    Vasaki Ponnusamy1, Aun Yichiet1, NZ Jhanjhi2,*, Mamoona humayun3, Maram Fahhad Almufareh3

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 865-879, 2022, DOI:10.32604/csse.2022.018801 - 24 September 2021

    Abstract Enhancement in wireless networks had given users the ability to use the Internet without a physical connection to the router. Almost every Internet of Things (IoT) devices such as smartphones, drones, and cameras use wireless technology (Infrared, Bluetooth, IrDA, IEEE 802.11, etc.) to establish multiple inter-device connections simultaneously. With the flexibility of the wireless network, one can set up numerous ad-hoc networks on-demand, connecting hundreds to thousands of users, increasing productivity and profitability significantly. However, the number of network attacks in wireless networks that exploit such flexibilities in setting and tearing down networks has become… More >

  • Open Access

    ARTICLE

    Intrusion Detection Systems in Internet of Things and Mobile Ad-Hoc Networks

    Vasaki Ponnusamy1,*, Mamoona Humayun2, N. Z. Jhanjhi3, Aun Yichiet1, Maram Fahhad Almufareh2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1199-1215, 2022, DOI:10.32604/csse.2022.018518 - 24 September 2021

    Abstract Internet of Things (IoT) devices work mainly in wireless mediums; requiring different Intrusion Detection System (IDS) kind of solutions to leverage 802.11 header information for intrusion detection. Wireless-specific traffic features with high information gain are primarily found in data link layers rather than application layers in wired networks. This survey investigates some of the complexities and challenges in deploying wireless IDS in terms of data collection methods, IDS techniques, IDS placement strategies, and traffic data analysis techniques. This paper’s main finding highlights the lack of available network traces for training modern machine-learning models against IoT… More >

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