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Open AccessReview

A Taxonomy of DDoS Attack Mitigation Approaches Featured by SDN Technologies in IoT Scenarios

1
LaTARC Research Lab (IFRN), Federal Institute of Education, Science and Technology of Rio Grande do Norte (IFRN), Natal, RN 59015-000, Brazil
2
Department of Informatics and Applied Mathematics (DIMAp), Federal University of Rio Grande do Norte (UFRN), Natal, RN 59078-970, Brazil
3
Instituto de Telecomunicações, 3810-193 Aveiro, Portugal
4
Department of Computer Science, Saint Louis University, Saint Louis, MO 63103, USA
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(11), 3078; https://doi.org/10.3390/s20113078
Received: 1 May 2020 / Revised: 16 May 2020 / Accepted: 19 May 2020 / Published: 29 May 2020
(This article belongs to the Special Issue Security and Privacy Techniques in IoT Environment)
The Internet of Things (IoT) has attracted much attention from the Information and Communication Technology (ICT) community in recent years. One of the main reasons for this is the availability of techniques provided by this paradigm, such as environmental monitoring employing user data and everyday objects. The facilities provided by the IoT infrastructure allow the development of a wide range of new business models and applications (e.g., smart homes, smart cities, or e-health). However, there are still concerns over the security measures which need to be addressed to ensure a suitable deployment. Distributed Denial of Service (DDoS) attacks are among the most severe virtual threats at present and occur prominently in this scenario, which can be mainly owed to their ease of execution. In light of this, several research studies have been conducted to find new strategies as well as improve existing techniques and solutions. The use of emerging technologies such as those based on the Software-Defined Networking (SDN) paradigm has proved to be a promising alternative as a means of mitigating DDoS attacks. However, the high granularity that characterizes the IoT scenarios and the wide range of techniques explored during the DDoS attacks make the task of finding and implementing new solutions quite challenging. This problem is exacerbated by the lack of benchmarks that can assist developers when designing new solutions for mitigating DDoS attacks for increasingly complex IoT scenarios. To fill this knowledge gap, in this study we carry out an in-depth investigation of the state-of-the-art and create a taxonomy that describes and characterizes existing solutions and highlights their main limitations. Our taxonomy provides a comprehensive view of the reasons for the deployment of the solutions, and the scenario in which they operate. The results of this study demonstrate the main benefits and drawbacks of each solution set when applied to specific scenarios by examining current trends and future perspectives, for example, the adoption of emerging technologies based on Cloud and Edge (or Fog) Computing. View Full-Text
Keywords: Distributed Denial of Service Attacks (DDoS); Software-Defined Networking (SDN); Internet of Things (IoT); taxonomy; revision; state-of-the-art Distributed Denial of Service Attacks (DDoS); Software-Defined Networking (SDN); Internet of Things (IoT); taxonomy; revision; state-of-the-art
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MDPI and ACS Style

Dantas Silva, F.S.; Silva, E.; Neto, E.P.; Lemos, M.; Venancio Neto, A.J.; Esposito, F. A Taxonomy of DDoS Attack Mitigation Approaches Featured by SDN Technologies in IoT Scenarios. Sensors 2020, 20, 3078. https://doi.org/10.3390/s20113078

AMA Style

Dantas Silva FS, Silva E, Neto EP, Lemos M, Venancio Neto AJ, Esposito F. A Taxonomy of DDoS Attack Mitigation Approaches Featured by SDN Technologies in IoT Scenarios. Sensors. 2020; 20(11):3078. https://doi.org/10.3390/s20113078

Chicago/Turabian Style

Dantas Silva, Felipe S.; Silva, Esau; Neto, Emidio P.; Lemos, Marcilio; Venancio Neto, Augusto J.; Esposito, Flavio. 2020. "A Taxonomy of DDoS Attack Mitigation Approaches Featured by SDN Technologies in IoT Scenarios" Sensors 20, no. 11: 3078. https://doi.org/10.3390/s20113078

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