IoT-based botnet attacks systematic mapping study of literature

Hamid, Habiba and Noor, Rafidah Md and Omar, Syaril Nizam and Ahmedy, Ismail and Anjum, Shaik Shabana and Shah, Syed Adeel Ali and Jaswant Singh, Sheena Kaur and Othman, Fazidah and Tamil, Emran Mohd IoT-based botnet attacks systematic mapping study of literature. Scientometrics, 126 (4). pp. 2759-2800. ISSN 0138-9130, DOI https://doi.org/10.1007/s11192-020-03819-5.

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Abstract

The rapid escalation in the usage of the Internet of Things (IoT) devices is threatened by botnets. The expected increase in botnet attacks has seen numerous botnet detection/mitigation proposals from academia and industry. This paper conducts a systematic mapping study of the literature so as to distinguish, sort, and synthesize research in this domain. The investigation is guided by various research questions that are relevant to the botnet studies. In this research, a total of 3,645 studies were gotten from our preliminary pursuit outcomes. Seventy four (74) studies were recognized based on importance, of which 52 were at last picked dependent on our characterized Incorporation and Elimination criteria. A classification for the mapping study with the following components: key contribution, research aspect, validation methods, network forensic methods, datasets and evaluation metric was proposed. Likewise, in this study, we identified eleven (11) key contributions which include evaluation, approach, model, system, software architecture, method, technique, framework, mechanism, algorithm and dataset. The findings of this systematic mapping investigation demonstrate that exploration of IoT-based botnet attacks is picking up more consideration in the past three years with steady distribution yield. Finally, this investigation can be a beginning point in examining researches on botnet assaults in IoT devices and finding better ways to detect and mitigate such assaults.

Item Type: Article
Funders: Universiti Malaya (RK004-2017), Universiti Malaya (GPF004D-2019)
Uncontrolled Keywords: Botnets; IoT; Systematic mapping study; Classification; Dataset
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Z Bibliography. Library Science. Information Resources > Libraries > Library science. Information science
Divisions: Faculty of Computer Science & Information Technology
Faculty of Languages and Linguistics
Depositing User: Ms Zaharah Ramly
Date Deposited: 06 Sep 2022 04:26
Last Modified: 06 Sep 2022 04:26
URI: http://eprints.um.edu.my/id/eprint/34186

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