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Journal of Cybersecurity and Information Management
Volume 1 , Issue 1, PP: 30-37 , 2020 | Cite this article as | XML | Html |PDF

Title

Securing the IoT: An Efficient Intrusion Detection System Using Convolutional Network

  Harith Yas 1 * ,   Manal M. Nasir 2

1  Faculty of Management, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia
    (Harith.albayati@yahoo.com)

2  Gwinnett Technical College, 5150 Sugarloaf Pkwy, Lawrenceville, GA 30043, USA
    (mnasir@gwinnetttech.edu)


Doi   :   https://doi.org/10.54216/JCIM.010105


Abstract :

The Internet of Things (IoT) is an ever-expanding network of interconnected devices that enables various applications, such as smart homes, smart cities, and industrial automation. However, with the proliferation of IoT devices, security risks have increased significantly, making it necessary to develop effective intrusion detection systems (IDS) for IoT networks. In this paper, we propose an efficient IDS for complex IoT environments based on convolutional neural networks (CNNs). Our approach uses IoT traffics as input to our CNN architecture to capture representational knowledge required to discriminate different forms of attacks. Our system achieves high accuracy and low false positive rates, even in the presence of complex and dynamic network traffic patterns. We evaluate the performance of our system using public datasets and compare it with other cutting-edge IDS approaches. Our results show that the proposed system outperforms the other approaches in terms of accuracy and false positive rates. The proposed IDS can enhance the security of IoT networks and protect them against various types of cyber-attacks.

Keywords :

IoT; Intrusion Detection; Convolutional Network; Secure IoT Systems

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Cite this Article as :
Style #
MLA Harith Yas, Manal M. Nasir. "Securing the IoT: An Efficient Intrusion Detection System Using Convolutional Network." Journal of Cybersecurity and Information Management, Vol. 1, No. 1, 2020 ,PP. 30-37 (Doi   :  https://doi.org/10.54216/JCIM.010105)
APA Harith Yas, Manal M. Nasir. (2020). Securing the IoT: An Efficient Intrusion Detection System Using Convolutional Network. Journal of Journal of Cybersecurity and Information Management, 1 ( 1 ), 30-37 (Doi   :  https://doi.org/10.54216/JCIM.010105)
Chicago Harith Yas, Manal M. Nasir. "Securing the IoT: An Efficient Intrusion Detection System Using Convolutional Network." Journal of Journal of Cybersecurity and Information Management, 1 no. 1 (2020): 30-37 (Doi   :  https://doi.org/10.54216/JCIM.010105)
Harvard Harith Yas, Manal M. Nasir. (2020). Securing the IoT: An Efficient Intrusion Detection System Using Convolutional Network. Journal of Journal of Cybersecurity and Information Management, 1 ( 1 ), 30-37 (Doi   :  https://doi.org/10.54216/JCIM.010105)
Vancouver Harith Yas, Manal M. Nasir. Securing the IoT: An Efficient Intrusion Detection System Using Convolutional Network. Journal of Journal of Cybersecurity and Information Management, (2020); 1 ( 1 ): 30-37 (Doi   :  https://doi.org/10.54216/JCIM.010105)
IEEE Harith Yas, Manal M. Nasir, Securing the IoT: An Efficient Intrusion Detection System Using Convolutional Network, Journal of Journal of Cybersecurity and Information Management, Vol. 1 , No. 1 , (2020) : 30-37 (Doi   :  https://doi.org/10.54216/JCIM.010105)