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Determining of Robust Factors for Detecting IoT Attacks

    Authors

    • Rawaa Ismael Farhan
    • Nidaa Flaih Hassan
    • Abeer Tariq Maolood

    Al-Kut University College Journal

,

Document Type : Research Paper

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Abstract

Abstract
Abstract The detection of novel intrusion types is the target of cyber security, therefore best secured network is become very necessary. The Network Intrusion Detection Systems (NIDS) must address the real-time data, since security attacks are expected to be increased substantially in the future with the Internet of Things (IoT). Intrusion detection approaches in this time, which depends on matching patterns of packet header information have decreased their effectiveness. This paper is focused on anomaly-based intrusion detection system, where NIDS detects normal and malicious behavior by analyzing network traffic, this analysis has the potential to detect novel attacks. Robust factors are used for evaluating these attacks by covering previous researches, these factors are: "high accuracy rate", "high detection rate"(DR) and "low false alarm report"(FAR), these factors influence on NIDS performance.

Keywords

  • Internet of Things IoT
  • Intrusion Detection System IDS
  • Deep learning DL
  • Machine learning ML
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Alkut university college journal
Volume 5, Issue 1
June 2020
Page 81-99
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  • Article View: 145
  • PDF Download: 75

APA

Farhan, R. I. , Hassan, N. F. and Maolood, A. T. (2020). Determining of Robust Factors for Detecting IoT Attacks. Alkut university college journal, 5(1), 81-99.

MLA

Farhan, R. I. , , Hassan, N. F. , and Maolood, A. T. . "Determining of Robust Factors for Detecting IoT Attacks", Alkut university college journal, 5, 1, 2020, 81-99.

HARVARD

Farhan, R. I., Hassan, N. F., Maolood, A. T. (2020). 'Determining of Robust Factors for Detecting IoT Attacks', Alkut university college journal, 5(1), pp. 81-99.

CHICAGO

R. I. Farhan , N. F. Hassan and A. T. Maolood, "Determining of Robust Factors for Detecting IoT Attacks," Alkut university college journal, 5 1 (2020): 81-99,

VANCOUVER

Farhan, R. I., Hassan, N. F., Maolood, A. T. Determining of Robust Factors for Detecting IoT Attacks. Alkut university college journal, 2020; 5(1): 81-99.

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