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SIEM-based detection and mitigation of IoT-botnet DDoS attacks

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 10 No. 2 (2020)

DOI
10.11591/ijece.v10i2.pp2182-2191
ISSN
2088-8708, 2088-8708
Published
2020-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

The Internet of Things (IoT) is becoming an integral part of our daily life including health, environment, homes, military, etc. The enormous growth of IoT in recent years has attracted hackers to take advantage of their computation and communication capabilities to perform different types of attacks. The major concern is that IoT devices have several vulnerabilities that can be easily exploited to form IoT botnets consisting of millions of IoT devices and posing significant threats to Internet security. In this context, DDoS attacks originating from IoT botnets is a major problem in today’s Internet that requires immediate attention. In this paper, we propose a Security Information and Event Management-based IoT botnet DDoS attack detection and mitigation system. This system detects and blocks DDoS attack traffic from compromised IoT devices by monitoring specific packet types including TCP SYN, ICMP and DNS packets originating from these devices. We discuss a prototype implementation of the proposed system and we demonstrate that SIEM based solutions can be configured to accurately identify and block malicious traffic originating from compromised IoT devices.

Collaboration network of the authors

6 authors · 15 co-authorship links

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  • Jordan University of Science and Technology
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>SIEM-based detection and mitigation of IoT-botnet DDoS attacks</dc:title><dc:creator>Al-Duwairi, Basheer</dc:creator><dc:creator>Al-Kahla, Wafaa</dc:creator><dc:creator>AlRefai, Mhd Ammar</dc:creator><dc:creator>Abedalqader, Yazid</dc:creator><dc:creator>Rawash, Abdullah</dc:creator><dc:creator>Fahmawi, Rana</dc:creator><dc:description>&lt;jats:p&gt;The Internet of Things (IoT) is becoming an integral part of our daily life including health, environment, homes, military, etc. The enormous growth of IoT in recent years has attracted hackers to take advantage of their computation and communication capabilities to perform different types of attacks. The major concern is that IoT devices have several vulnerabilities that can be easily exploited to form IoT botnets consisting of millions of IoT devices and posing significant threats to Internet security. In this context, DDoS attacks originating from IoT botnets is a major problem in today’s Internet that requires immediate attention. In this paper, we propose a Security Information and Event Management-based IoT botnet DDoS attack detection and mitigation system. This system detects and blocks DDoS attack traffic from compromised IoT devices by monitoring specific packet types including TCP SYN, ICMP and DNS packets originating from these devices. We discuss a prototype implementation of the proposed system and we demonstrate that SIEM based solutions can be configured to accurately identify and block malicious traffic originating from compromised IoT devices.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2020-04-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v10i2.pp2182-2191</dc:identifier><dc:identifier>10.11591/ijece.v10i2.pp2182-2191</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 10 No 2 (2020); 2182</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/20812/pdf</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>