Adaptive Strategies to Mitigate DDoS Attacks in IoT-Devices Through A Moving Target Defense Approach in SDN

The surge of IoT devices has revolutionized the world, but the inherent complexity and vulnerabilities of these devices pose significant security risks. Among security challenges, distributed denial of service (DDoS) attacks stands out as a major cybersecurity issue aimed at interfering with regular systems. This paper conducts a gap analysis of existing research on DDoS attacks in the context of SDN oriented IoT devices. The research focus is on comparing algorithms and mitigation strategies proposed in different research papers and evaluating their efficiency and cost-effectiveness as previous research efforts have taken a variety of approaches, some focused on inexpensive but ineffective procedures, while others focused on expensive but effective procedures. However, few studies have investigated both cost and performance effectiveness simultaneously. The main objective of this research paper is to evaluate and compare different strategies proposed in the literature to protect Software Defined Network oriented IoT devices from DDoS attacks through an active approach using MTD (Moving Target Defense) technique. The goal of this strategy is to protect the network from attacks while remaining cost-effective through gap analysis to suggest that the Moving Target Defense technique is less complex than previous approaches to provide better security measures and protection against DDoS attacks on networks.

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Publication Details

Journal
Journal of Engineering Technology and Applied Physics
Published
2025-09-15
DOI
https://doi.org/10.33093/jetap.2025.7.2.13
Citations
1
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
1.49
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article

Adaptive Strategies to Mitigate DDoS Attacks in IoT-Devices Through A Moving Target Defense Approach in SDN

Soomal Qureshi, Hafiz Muhammad Attaullah, Ayesha Ashraf, Rabia Laraib
1 citations
Journal of Engineering Technology and Applied Physics
Network Security and Intrusion Detection
1.49
article

Adaptive Strategies to Mitigate DDoS Attacks in IoT-Devices Through A Moving Target Defense Approach in SDN

Soomal Qureshi, Hafiz Muhammad Attaullah, Ayesha Ashraf, Rabia Laraib
article en
1 citations

Abstract

The surge of IoT devices has revolutionized the world, but the inherent complexity and vulnerabilities of these devices pose significant security risks. Among security challenges, distributed denial of service (DDoS) attacks stands out as a major cybersecurity issue aimed at interfering with regular systems. This paper conducts a gap analysis of existing research on DDoS attacks in the context of SDN oriented IoT devices. The research focus is on comparing algorithms and mitigation strategies proposed in different research papers and evaluating their efficiency and cost-effectiveness as previous research efforts have taken a variety of approaches, some focused on inexpensive but ineffective procedures, while others focused on expensive but effective procedures. However, few studies have investigated both cost and performance effectiveness simultaneously. The main objective of this research paper is to evaluate and compare different strategies proposed in the literature to protect Software Defined Network oriented IoT devices from DDoS attacks through an active approach using MTD (Moving Target Defense) technique. The goal of this strategy is to protect the network from attacks while remaining cost-effective through gap analysis to suggest that the Moving Target Defense technique is less complex than previous approaches to provide better security measures and protection against DDoS attacks on networks.

Journal of Engineering Technology and Applied PhysicsVol. 7(2)
Université Libre de Bruxelles (BE), NED University of Engineering and Technology (PK), Multimedia University (MY), Pakistan Telecommunication Company (Pakistan) (PK), National University of Sciences and Technology (PK)
Openalex Percentile: Top 13%
Network Security and Intrusion Detection
1.49
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