Jan 26, 2019 · We propose a novel framework to detect different types of EDoS attacks by designing a profile that learns from and classifies the normal and abnormal behaviors.
In this work, we propose a novel framework to detect different types of EDoS attacks by designing a profile that learns from and classifies the normal and ...
In this work, we propose a novel framework to detect different types of EDoS attacks by designing a profile that learns from and classifies the normal and ...
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Oct 28, 2024 · This research introduces the Integrated Model Prediction and Feature Selection (I-MPaFS) framework to address EDoS attacks.
Evaluating our framework when using SVM. Machine Learning-Based EDoS Attack Detection Technique Using Execution Trace Analysis. Article. Full-text available.
Machine Learning-Based EDoS Attack Detection Technique Using Execution Trace Analysis. Journal of Hardware and Systems Security. 2019-06-26 | Journal article.
We, therefore, propose a two-phase deep learning-based EDoS detection scheme that uses an LSTM model to detect each abnormal flow in network traffic.
Machine learning-based EDoS attack detection technique using execution trace analysis · The use of anomaly detection for the detection of different types of DDoS ...
(2019). Machine learning-based EDoS attack detection technique using execution trace analysis. Journal of Hardware and Systems Security, 3(2), 164-176.
The main objective of the proposed work is to design a profile-based novel framework for maximizing the detection of various types of EDoS attacks. During this ...