A Stacked Ensemble Approach to Generalize the Classifier Prediction for the Detection of DDoS Attack in Cloud Network

Verma, Priyanka; Kowsik, A. Rama Krishna; Pateriya, R. K.; Bharot, Nitesh; Vidyarthi, Ankit; Gupta, Deepak

doi:10.1007/s11036-023-02225-4

Cited by 3 publications

(2 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Emerging TCP/IP threats, such as distributed denial-of-service (DDoS) attacks leveraging TCP/IP vulnerabilities, can overwhelm network resources, causing service disruptions and downtime [113], [114]. These attacks target critical infrastructure, including financial institutions, healthcare systems, and government agencies, impacting the delivery of essential services and affecting millions of users [115]. The resulting economic losses, operational disruptions, and reputational damage underscore the importance of robust network defenses and proactive mitigation strategies to ensure network availability and resilience in the face of emerging TCP/IP threats.…”

Section: Impact Of Emerging Threatsmentioning

confidence: 99%

Survey on evolving threats in TCP/IP header attacks: Emerging trends and future directions

Winnie Owoko

2024

World J. Adv. Eng. Technol. Sci.

View full text Add to dashboard Cite

The TCP/IP protocol suite, a cornerstone of modern networking, faces escalating threats from evolving attack vectors targeting its headers. This survey explores emerging trends in TCP/IP header attacks, assessing their potential impact and outlining future directions for defense strategies. By scrutinizing recent research and real-world incidents, the paper aims to offer insights into the evolving threat landscape and provide recommendations for enhancing network security. Key areas of investigation include the historical evolution of TCP/IP header vulnerabilities, the adaptation of attackers' techniques over time, and the development of novel defense mechanisms to counteract these threats. The survey underscores the critical importance of understanding TCP/IP header attacks in contemporary cybersecurity and highlights the necessity for proactive measures to safeguard network infrastructures. By addressing the challenges posed by evolving TCP/IP header attacks and identifying areas for further research and development, this survey contributes to the ongoing efforts to strengthen network defenses and mitigate the risks associated with cyber threats targeting TCP/IP protocols.

show abstract

Section: Impact Of Emerging Threatsmentioning

confidence: 99%

Survey on evolving threats in TCP/IP header attacks: Emerging trends and future directions

Winnie Owoko

2024

World J. Adv. Eng. Technol. Sci.

View full text Add to dashboard Cite

show abstract

“…Innovative approaches, such as ensemble-based weighted voting, should be adopted to improve detection accuracy and efficiency [15]. Ensemblebased voting optimizes predictive outcomes by fusing diverse algorithms to mitigate inherent uncertainties and strengthen model robustness [16].…”

Section: Introductionmentioning

confidence: 99%

Efficient IoT Security: Weighted Voting for BASHLITE and Mirai Attack Detection

Abu-Zanona

2023

IJACSA

View full text Add to dashboard Cite

The increasing number of devices in the Internet of Things (IoT) has exposed various vulnerabilities, such as BASHLITE and Mirai attacks, making it easier for cyber threats to emerge. Due to these vulnerabilities, developing innovative detection and mitigation strategies is essential. Our proposed solution is an ensemble-based weighted voting model that combines different classifiers, including Random Forest, eXtreme Gradient Boosting (XGBoost), Gradient Boosting, K-nearest neighbor (KNN), Multilayer Perceptron (MLP), and Adaptive Boosting (AdaBoost), using artificial intelligence and machine learning. We evaluated our model on the N-BaIoT dataset, a benchmark in this domain. Our results show that the weighted voting approach has exceptional accuracy, precision, recall, and F1-Score. This highlights the effectiveness of our model in classifying various attack instances within the IoT security context. Our approach performs better than other state-of-the-art methods, achieving a remarkable accuracy of 99.9955% in detecting and preventing BASHLITE and Mirai cyber-attacks on IoT devices.

show abstract

Advancements in detecting, preventing, and mitigating DDoS attacks in cloud environments: A comprehensive systematic review of state-of-the-art approaches

Ouhssini,

Afdel,

Akouhar

et al. 2024

Egyptian Informatics Journal

View full text Add to dashboard Cite

A Stacked Ensemble Approach to Generalize the Classifier Prediction for the Detection of DDoS Attack in Cloud Network

Cited by 3 publications

References 30 publications

Survey on evolving threats in TCP/IP header attacks: Emerging trends and future directions

Survey on evolving threats in TCP/IP header attacks: Emerging trends and future directions

Efficient IoT Security: Weighted Voting for BASHLITE and Mirai Attack Detection

Advancements in detecting, preventing, and mitigating DDoS attacks in cloud environments: A comprehensive systematic review of state-of-the-art approaches

Contact Info

Product

Resources

About