Toward explainable and adaptable detection and classification of distributed denial-of-service attacks
Y Feng, J Li - Deployable Machine Learning for Security Defense …, 2020 - Springer
By attacking (eg, flooding) the bandwidth or resources of a victim (eg, a web server) on the
Internet from multiple compromised systems (eg, a botnet), distributed Denial-of-Service …
Internet from multiple compromised systems (eg, a botnet), distributed Denial-of-Service …
[图书][B] Detection and Explanation of Distributed Denial of Service (DDoS) Attack Through Interpretable Machine Learning
S Das - 2021 - search.proquest.com
Distributed denial of service (DDoS) is a network-based attack where the aim of the attacker
is to overwhelm the victim server. The attacker floods the server by sending enormous …
is to overwhelm the victim server. The attacker floods the server by sending enormous …
DDoS attacks and machine‐learning‐based detection methods: A survey and taxonomy
Distributed denial of service (DDoS) attacks represent a significant cybersecurity challenge,
posing a critical risk to computer networks. Developing an effective defense mechanism …
posing a critical risk to computer networks. Developing an effective defense mechanism …
On Explainable and Adaptable Detection of Distributed Denial-of-Service Traffic
Launched from numerous end-hosts throughout the Internet, a distributed denial-of-service
(DDoS) attack can exhaust the network bandwidth or other resources of a victim, cripple its …
(DDoS) attack can exhaust the network bandwidth or other resources of a victim, cripple its …
[HTML][HTML] Robust DDoS attack detection with adaptive transfer learning
In the evolving cybersecurity landscape, the rising frequency of Distributed Denial of Service
(DDoS) attacks requires robust defense mechanisms to safeguard network infrastructure …
(DDoS) attacks requires robust defense mechanisms to safeguard network infrastructure …
Empirical performance evaluation of machine learning based DDoS attack detections
A distributed denial-of-service attack (DDoS) is a critical attack-type that strongly damages
the Quality of Service (QoE). Although various novel security technologies have been …
the Quality of Service (QoE). Although various novel security technologies have been …
Information-theoretic ensemble learning for ddos detection with adaptive boosting
DDoS (Distributed Denial of Service) attacks pose a serious threat to the Internet as they use
large numbers of zombie hosts to forward massive numbers of packets to the target host …
large numbers of zombie hosts to forward massive numbers of packets to the target host …
CNN-LSTM Based Approach for DDoS Detection
T Alasmari, A Alshomrani, L Hsairi - 2023 Eighth International …, 2023 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attacks have become increasingly common, causing
financial and reputational losses for organizations. Despite the existence of numerous …
financial and reputational losses for organizations. Despite the existence of numerous …
A machine learning classification model using random forest for detecting DDoS attacks
TS Chu, W Si, S Simoff… - … Symposium on Networks …, 2022 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attacks exhaust the resources of network services by
generating a huge volume of network traffic. They constitute a primary threat to the current …
generating a huge volume of network traffic. They constitute a primary threat to the current …
Ensembling Supervised and Unsupervised Machine Learning Algorithms for Detecting Distributed Denial of Service Attacks
The distributed denial of service (DDoS) attack is one of the most pernicious threats in
cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic …
cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic …