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  • Open Access

    ARTICLE

    Federated Blockchain Model for Cyber Intrusion Analysis in Smart Grid Networks

    N. Sundareswaran*, S. Sasirekha

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2129-2143, 2023, DOI:10.32604/iasc.2023.034381 - 05 January 2023

    Abstract Smart internet of things (IoT) devices are used to manage domestic and industrial energy needs using sustainable and renewable energy sources. Due to cyber infiltration and a lack of transparency, the traditional transaction process is inefficient, unsafe and expensive. Smart grid systems are now efficient, safe and transparent owing to the development of blockchain (BC) technology and its smart contract (SC) solution. In this study, federated learning extreme gradient boosting (FL-XGB) framework has been developed along with BC to learn the intrusion inside the smart energy system. FL is best suited for a decentralized BC-enabled… More >

  • Open Access

    ARTICLE

    Optimal Deep Learning Driven Intrusion Detection in SDN-Enabled IoT Environment

    Mohammed Maray1, Haya Mesfer Alshahrani2, Khalid A. Alissa3, Najm Alotaibi4, Abdulbaset Gaddah5, Ali Meree1,6, Mahmoud Othman7, Manar Ahmed Hamza8,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6587-6604, 2023, DOI:10.32604/cmc.2023.034176 - 28 December 2022

    Abstract In recent years, wireless networks are widely used in different domains. This phenomenon has increased the number of Internet of Things (IoT) devices and their applications. Though IoT has numerous advantages, the commonly-used IoT devices are exposed to cyber-attacks periodically. This scenario necessitates real-time automated detection and the mitigation of different types of attacks in high-traffic networks. The Software-Defined Networking (SDN) technique and the Machine Learning (ML)-based intrusion detection technique are effective tools that can quickly respond to different types of attacks in the IoT networks. The Intrusion Detection System (IDS) models can be employed… More >

  • Open Access

    ARTICLE

    Chaotic Metaheuristics with Multi-Spiking Neural Network Based Cloud Intrusion Detection

    Mohammad Yamin1,*, Saleh Bajaba2, Zenah Mahmoud AlKubaisy1

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6101-6118, 2023, DOI:10.32604/cmc.2023.033677 - 28 December 2022

    Abstract Cloud Computing (CC) provides data storage options as well as computing services to its users through the Internet. On the other hand, cloud users are concerned about security and privacy issues due to the increased number of cyberattacks. Data protection has become an important issue since the users’ information gets exposed to third parties. Computer networks are exposed to different types of attacks which have extensively grown in addition to the novel intrusion methods and hacking tools. Intrusion Detection Systems (IDSs) can be used in a network to manage suspicious activities. These IDSs monitor the… More >

  • Open Access

    ARTICLE

    Probe Attack Detection Using an Improved Intrusion Detection System

    Abdulaziz Almazyad, Laila Halman, Alaa Alsaeed*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4769-4784, 2023, DOI:10.32604/cmc.2023.033382 - 28 December 2022

    Abstract The novel Software Defined Networking (SDN) architecture potentially resolves specific challenges arising from rapid internet growth of and the static nature of conventional networks to manage organizational business requirements with distinctive features. Nevertheless, such benefits lead to a more adverse environment entailing network breakdown, systems paralysis, and online banking fraudulence and robbery. As one of the most common and dangerous threats in SDN, probe attack occurs when the attacker scans SDN devices to collect the necessary knowledge on system susceptibilities, which is then manipulated to undermine the entire system. Precision, high performance, and real-time systems… More >

  • Open Access

    ARTICLE

    Optimal Fuzzy Logic Enabled Intrusion Detection for Secure IoT-Cloud Environment

    Fatma S. Alrayes1, Nuha Alshuqayran2, Mohamed K Nour3, Mesfer Al Duhayyim4,*, Abdullah Mohamed5, Amgad Atta Abdelmageed Mohammed6, Gouse Pasha Mohammed6, Ishfaq Yaseen6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6737-6753, 2023, DOI:10.32604/cmc.2023.032591 - 28 December 2022

    Abstract Recently, Internet of Things (IoT) devices have developed at a faster rate and utilization of devices gets considerably increased in day to day lives. Despite the benefits of IoT devices, security issues remain challenging owing to the fact that most devices do not include memory and computing resources essential for satisfactory security operation. Consequently, IoT devices are vulnerable to different kinds of attacks. A single attack on networking system/device could result in considerable data to data security and privacy. But the emergence of artificial intelligence (AI) techniques can be exploited for attack detection and classification… More >

  • Open Access

    ARTICLE

    Intrusion Detection Using Federated Learning for Computing

    R. S. Aashmi1,*, T. Jaya2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1295-1308, 2023, DOI:10.32604/csse.2023.027216 - 03 November 2022

    Abstract The integration of clusters, grids, clouds, edges and other computing platforms result in contemporary technology of jungle computing. This novel technique has the aptitude to tackle high performance computation systems and it manages the usage of all computing platforms at a time. Federated learning is a collaborative machine learning approach without centralized training data. The proposed system effectively detects the intrusion attack without human intervention and subsequently detects anomalous deviations in device communication behavior, potentially caused by malicious adversaries and it can emerge with new and unknown attacks. The main objective is to learn overall… More >

  • Open Access

    ARTICLE

    Genetic-based Fuzzy IDS for Feature Set Reduction and Worm Hole Attack Detection

    M. Reji1,*, Christeena Joseph2, K. Thaiyalnayaki2, R. Lathamanju2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1265-1278, 2023, DOI:10.32604/csse.2023.026776 - 03 November 2022

    Abstract The wireless ad-hoc networks are decentralized networks with a dynamic topology that allows for end-to-end communications via multi-hop routing operations with several nodes collaborating themselves, when the destination and source nodes are not in range of coverage. Because of its wireless type, it has lot of security concerns than an infrastructure networks. Wormhole attacks are one of the most serious security vulnerabilities in the network layers. It is simple to launch, even if there is no prior network experience. Signatures are the sole thing that preventive measures rely on. Intrusion detection systems (IDS) and other… More >

  • Open Access

    ARTICLE

    Wrapper Based Linear Discriminant Analysis (LDA) for Intrusion Detection in IIoT

    B. Yasotha1,*, T. Sasikala2, M. Krishnamurthy3

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1625-1640, 2023, DOI:10.32604/csse.2023.025669 - 03 November 2022

    Abstract The internet has become a part of every human life. Also, various devices that are connected through the internet are increasing. Nowadays, the Industrial Internet of things (IIoT) is an evolutionary technology interconnecting various industries in digital platforms to facilitate their development. Moreover, IIoT is being used in various industrial fields such as logistics, manufacturing, metals and mining, gas and oil, transportation, aviation, and energy utilities. It is mandatory that various industrial fields require highly reliable security and preventive measures against cyber-attacks. Intrusion detection is defined as the detection in the network of security threats… More >

  • Open Access

    ARTICLE

    Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

    Doaa Sami Khafaga1, Faten Khalid Karim1,*, Abdelaziz A. Abdelhamid2,3, El-Sayed M. El-kenawy4, Hend K. Alkahtani1, Nima Khodadadi5, Mohammed Hadwan6, Abdelhameed Ibrahim7

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3183-3198, 2023, DOI:10.32604/cmc.2023.033513 - 31 October 2022

    Abstract Managing physical objects in the network’s periphery is made possible by the Internet of Things (IoT), revolutionizing human life. Open attacks and unauthorized access are possible with these IoT devices, which exchange data to enable remote access. These attacks are often detected using intrusion detection methodologies, although these systems’ effectiveness and accuracy are subpar. This paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic optimization. The employed metaheuristic optimizer is a new version of the whale optimization algorithm (WOA), which is guided by the dipper… More >

  • Open Access

    ARTICLE

    Enhanced Coyote Optimization with Deep Learning Based Cloud-Intrusion Detection System

    Abdullah M. Basahel1, Mohammad Yamin1, Sulafah M. Basahel2, E. Laxmi Lydia3,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4319-4336, 2023, DOI:10.32604/cmc.2023.033497 - 31 October 2022

    Abstract Cloud Computing (CC) is the preference of all information technology (IT) organizations as it offers pay-per-use based and flexible services to its users. But the privacy and security become the main hindrances in its achievement due to distributed and open architecture that is prone to intruders. Intrusion Detection System (IDS) refers to one of the commonly utilized system for detecting attacks on cloud. IDS proves to be an effective and promising technique, that identifies malicious activities and known threats by observing traffic data in computers, and warnings are given when such threats were identified. The… More >

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