Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (250)
  • Open Access

    ARTICLE

    An IoT-Based Intrusion Detection System Approach for TCP SYN Attacks

    Abdelwahed Berguiga*, Ahlem Harchay

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3839-3851, 2022, DOI:10.32604/cmc.2022.023399 - 07 December 2021

    Abstract The success of Internet of Things (IoT) deployment has emerged important smart applications. These applications are running independently on different platforms, almost everywhere in the world. Internet of Medical Things (IoMT), also referred as the healthcare Internet of Things, is the most widely deployed application against COVID-19 and offering extensive healthcare services that are connected to the healthcare information technologies systems. Indeed, with the impact of the COVID-19 pandemic, a large number of interconnected devices designed to create smart networks. These networks monitor patients from remote locations as well as tracking medication orders. However, IoT… More >

  • Open Access

    ARTICLE

    Hybridized Wrapper Filter Using Deep Neural Network for Intrusion Detection

    N. Venkateswaran1,*, K. Umadevi2

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 1-14, 2022, DOI:10.32604/csse.2022.021217 - 02 December 2021

    Abstract Huge data over the cloud computing and big data are processed over the network. The data may be stored, send, altered and communicated over the network between the source and destination. Once data send by source to destination, before reaching the destination data may be attacked by any intruders over the network. The network has numerous routers and devices to connect to internet. Intruders may attack any were in the network and breaks the original data, secrets. Detection of attack in the network became interesting task for many researchers. There are many intrusion detection feature… More >

  • Open Access

    ARTICLE

    Development of PCCNN-Based Network Intrusion Detection System for EDGE Computing

    Mohd Anul Haq, Mohd Abdul Rahim Khan*, Talal AL-Harbi

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1769-1788, 2022, DOI:10.32604/cmc.2022.018708 - 03 November 2021

    Abstract Intrusion Detection System (IDS) plays a crucial role in detecting and identifying the DoS and DDoS type of attacks on IoT devices. However, anomaly-based techniques do not provide acceptable accuracy for efficacious intrusion detection. Also, we found many difficulty levels when applying IDS to IoT devices for identifying attempted attacks. Given this background, we designed a solution to detect intrusions using the Convolutional Neural Network (CNN) for Enhanced Data rates for GSM Evolution (EDGE) Computing. We created two separate categories to handle the attack and non-attack events in the system. The findings of this study… More >

  • Open Access

    ARTICLE

    Intrusion Detection System for Energy Efficient Cluster Based Vehicular Adhoc Networks

    R. Lavanya1,*, S. Kannan2

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 323-337, 2022, DOI:10.32604/iasc.2022.021467 - 26 October 2021

    Abstract A vehicular ad hoc network (VANET), a subfield of mobile adhoc network (MANET) is defined by its high mobility by demonstrating the dissimilar mobility patterns. So, VANET clustering techniques are needed with the consideration of the mobility parameters amongst the nearby nodes for constructing the stable clustering techniques. At the same time, security is also a major design issue in VANET, this can be resolved by the intrusion detection systems (IDS). In contrast to the conventional IDS, VANET based IDS are required to be designed in such a way that the functioning of the system… More >

  • Open Access

    ARTICLE

    Improved Dragonfly Optimizer for Intrusion Detection Using Deep Clustering CNN-PSO Classifier

    K. S. Bhuvaneshwari1, K. Venkatachalam2, S. Hubálovský3,*, P. Trojovský4, P. Prabu5

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5949-5965, 2022, DOI:10.32604/cmc.2022.020769 - 11 October 2021

    Abstract With the rapid growth of internet based services and the data generated on these services are attracted by the attackers to intrude the networking services and information. Based on the characteristics of these intruders, many researchers attempted to aim to detect the intrusion with the help of automating process. Since, the large volume of data is generated and transferred through network, the security and performance are remained an issue. IDS (Intrusion Detection System) was developed to detect and prevent the intruders and secure the network systems. The performance and loss are still an issue because… More >

  • 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

    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 >

Displaying 191-200 on page 20 of 250. Per Page