Authors:
Mehak Fatima,Arshad Ali,Muhammad Tausif Afzal Rana,Muhammad Ahmad,Fakhar Un Nisa,Hamayun Khan,Hafiz Umar Farooq,Muhammad Ahsan Ur Raheem,DOI NO:
https://doi.org/10.26782/jmcms.2024.10.00009Keywords:
DDoS attacks,Data analysis,IoT security,Security measures,Abstract
The Internet of Things (IoTs) are emerging and become a vital need in our daily routine. The privacy protection and insecurity of these IoT-based devices face many challenges. Distributed denial of service (DDoS) attacks in IoT networks become a significant growing challenge that is addressed in this research. The resilience and strategy for IoT devices due to distributed denial of service (DDoS) attacks assess current security measures by proposing modern procedures to upgrade the strength of IoT frameworks. This article proposes a mechanism that mitigiates the effects of DDoS attacks in IoTs, that cause significant destruction to existing systems. Utilizing secondary data from Kaggle, the machine is trained and tested. Our proposed approach incorporates descriptive statistics, correlations, t-tests, chi-square tests, and regression analyses to supply a systematic understanding of IoT security by critically analyzing the existing variants of numerous DDoS attacks, Security issues in IoTs, and creation of them in Botnets or zombies. Our findings show that the proposed security techniques are viable and detection rates correlate with security viability. The proposed model asses various network threat and cybersecurity arrangements for mitigating DDoS attacks in IoT’s and outperforms the previously implemented Web Application Firewall (WAF), Bot Mitigation, Resource Prioritisation, and Content Delivery Networks (CDNs)based DDoS mitigation techniques by 80.5%, 88%, 86% in terms of effectiveness, T-test, chi test, and correlation.Refference:
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