A comprehensive review of vulnerabilities and AI-enabled defense against DDoS attacks for securing cloud services
The advent of cloud computing has made a global impact by providing on-demand services,
elasticity, scalability, and flexibility, hence delivering cost-effective resources to end users in …
elasticity, scalability, and flexibility, hence delivering cost-effective resources to end users in …
A survey on enterprise network security: Asset behavioral monitoring and distributed attack detection
Enterprise networks that host valuable assets and services are popular and frequent targets
of distributed network attacks. In order to cope with the ever-increasing threats, industrial …
of distributed network attacks. In order to cope with the ever-increasing threats, industrial …
Enhancing DDoS attack detection and mitigation in SDN using an ensemble online machine learning model
Software Defined Networks (SDN) offer dynamic reconfigurability and scalability,
revolutionizing traditional networking. However, countering Distributed Denial of Service …
revolutionizing traditional networking. However, countering Distributed Denial of Service …
Distributed Denial of Service Attack Detection in IoT Networks using Deep Learning and Feature Fusion: A Review
The explosive growth of Internet of Things (IoT) devices has led to escalating threats from
distributed denial of service (DDoS) attacks. Moreover, the scale and heterogeneity of IoT …
distributed denial of service (DDoS) attacks. Moreover, the scale and heterogeneity of IoT …
Toward a Real‐Time TCP SYN Flood DDoS Mitigation Using Adaptive Neuro‐Fuzzy Classifier and SDN Assistance in Fog Computing
The growth of the Internet of Things (IoT) has recently impacted our daily lives in many ways.
As a result, a massive volume of data are generated and need to be processed in a short …
As a result, a massive volume of data are generated and need to be processed in a short …
Evaluating modern intrusion detection methods in the face of Gen V multi-vector attacks with fuzzy AHP-TOPSIS
W Alhakami - Plos one, 2024 - journals.plos.org
The persistent evolution of cyber threats has given rise to Gen V Multi-Vector Attacks,
complex and sophisticated strategies that challenge traditional security measures. This …
complex and sophisticated strategies that challenge traditional security measures. This …
2019–2023 in Review: Projecting DDoS Threats With ARIMA and ETS Forecasting Techniques
This comprehensive study investigates the trends, impacts, and global distribution of major
Distributed Denial of Service (DDoS) attacks from 2019 to 2023, aiming to understand their …
Distributed Denial of Service (DDoS) attacks from 2019 to 2023, aiming to understand their …
[HTML][HTML] An empirical assessment of ML models for 5G network intrusion detection: A data leakage-free approach
MA Bouke, A Abdullah - e-Prime-Advances in Electrical Engineering …, 2024 - Elsevier
This paper thoroughly compares thirteen unique Machine Learning (ML) models utilized for
Intrusion detection systems (IDS) in a meticulously controlled environment. Unlike previous …
Intrusion detection systems (IDS) in a meticulously controlled environment. Unlike previous …
DDoS‐MSCT: A DDoS Attack Detection Method Based on Multiscale Convolution and Transformer
B Wang, Y Jiang, Y Liao, Z Li - IET Information Security, 2024 - Wiley Online Library
Distributed denial‐of‐service (DDoS) attacks pose a significant threat to network security
due to their widespread impact and detrimental consequences. Currently, deep learning …
due to their widespread impact and detrimental consequences. Currently, deep learning …
A Critical Assessment of Interpretable and Explainable Machine Learning for Intrusion Detection
There has been a large number of studies in interpretable and explainable ML for
cybersecurity, in particular, for intrusion detection. Many of these studies have significant …
cybersecurity, in particular, for intrusion detection. Many of these studies have significant …