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  • 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 >

  • Open Access

    ARTICLE

    Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

    Reem Alkanhel1, El-Sayed M. El-kenawy2, Abdelaziz A. Abdelhamid3,4, Abdelhameed Ibrahim5, Manal Abdullah Alohali6, Mostafa Abotaleb7, Doaa Sami Khafaga8,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2677-2693, 2023, DOI:10.32604/cmc.2023.033273 - 31 October 2022

    Abstract Applications of internet-of-things (IoT) are increasingly being used in many facets of our daily life, which results in an enormous volume of data. Cloud computing and fog computing, two of the most common technologies used in IoT applications, have led to major security concerns. Cyberattacks are on the rise as a result of the usage of these technologies since present security measures are insufficient. Several artificial intelligence (AI) based security solutions, such as intrusion detection systems (IDS), have been proposed in recent years. Intelligent technologies that require data preprocessing and machine learning algorithm-performance augmentation require… More >

  • Open Access

    ARTICLE

    Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection Systems

    Reem Alkanhel1,*, Doaa Sami Khafaga2, El-Sayed M. El-kenawy3, Abdelaziz A. Abdelhamid4,5, Abdelhameed Ibrahim6, Rashid Amin7, Mostafa Abotaleb8, B. M. El-den6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2695-2709, 2023, DOI:10.32604/cmc.2023.033153 - 31 October 2022

    Abstract The Internet of Things (IoT) is a modern approach that enables connection with a wide variety of devices remotely. Due to the resource constraints and open nature of IoT nodes, the routing protocol for low power and lossy (RPL) networks may be vulnerable to several routing attacks. That’s why a network intrusion detection system (NIDS) is needed to guard against routing assaults on RPL-based IoT networks. The imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network attacks. Therefore, we propose in this paper… More >

  • Open Access

    ARTICLE

    Central Aggregator Intrusion Detection System for Denial of Service Attacks

    Sajjad Ahmad1, Imran Raza1, M. Hasan Jamal1, Sirojiddin Djuraev2, Soojung Hur3, Imran Ashraf3,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2363-2377, 2023, DOI:10.32604/cmc.2023.032694 - 31 October 2022

    Abstract Vehicle-to-grid technology is an emerging field that allows unused power from Electric Vehicles (EVs) to be used by the smart grid through the central aggregator. Since the central aggregator is connected to the smart grid through a wireless network, it is prone to cyber-attacks that can be detected and mitigated using an intrusion detection system. However, existing intrusion detection systems cannot be used in the vehicle-to-grid network because of the special requirements and characteristics of the vehicle-to-grid network. In this paper, the effect of denial-of-service attacks of malicious electric vehicles on the central aggregator of… More >

  • Open Access

    ARTICLE

    A Fused Machine Learning Approach for Intrusion Detection System

    Muhammad Sajid Farooq1, Sagheer Abbas1, Atta-ur-Rahman2, Kiran Sultan3, Muhammad Adnan Khan4,*, Amir Mosavi5,6,7

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2607-2623, 2023, DOI:10.32604/cmc.2023.032617 - 31 October 2022

    Abstract The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of internet. The interconnectivity of networks has brought various complexities in maintaining network availability, consistency, and discretion. Machine learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit activities. An intrusion detection system controls the flow of network traffic with the help of computer systems. Various deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network traffic. For this purpose, when the network More >

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