A Distributed Denial of Service Attack Detection System using Long Short Term Memory with Singular Value Decomposition

2021 ◽  
Author(s):  
Chukwuemeka Christian Ugwu ◽  
Olumide Olayinka Obe ◽  
Olugbemiga Solomon Popoqla ◽  
Adebayo Olusola Adetunmbi
Keyword(s):  
Short Term Memory ◽  
Detection System ◽  
Denial Of Service ◽  
Attack Detection ◽  
Distributed Denial Of Service ◽  
Short Term ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Long Short Term Memory ◽  
Value Decomposition

scholarly journals Noise-Robust Multilayer Perceptron Architecture for Distributed Denial of Service Attack Detection

2020 ◽  
pp. 1-1
Author(s):  
Joao Paulo A. Maranhao ◽  
Joao Paulo C. L. da Costa ◽  
Edison Pignaton de Freitas ◽  
Elnaz Javidi ◽  
Rafael T. de Sousa
Keyword(s):  
Multilayer Perceptron ◽  
Denial Of Service ◽  
Attack Detection ◽  
Distributed Denial Of Service ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Noise Robust

scholarly journals DoS and DDoS Attack Detection Using Deep Learning and IDS

2020 ◽  
Vol 17 (4A) ◽  
pp. 655-661
Author(s):  
Mohammad Shurman ◽  
Rami Khrais ◽  
Abdulrahman Yateem
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Detection System ◽  
Denial Of Service ◽  
Attack Detection ◽  
Target System ◽  
Online Systems ◽  
Ddos Attack ◽  
Long Short Term Memory ◽  
Ddos Attack Detection

In the recent years, Denial-of-Service (DoS) or Distributed Denial-of-Service (DDoS) attack has spread greatly and attackers make online systems unavailable to legitimate users by sending huge number of packets to the target system. In this paper, we proposed two methodologies to detect Distributed Reflection Denial of Service (DrDoS) attacks in IoT. The first methodology uses hybrid Intrusion Detection System (IDS) to detect IoT-DoS attack. The second methodology uses deep learning models, based on Long Short-Term Memory (LSTM) trained with latest dataset for such kinds of DrDoS. Our experimental results demonstrate that using the proposed methodologies can detect bad behaviour making the IoT network safe of Dos and DDoS attacks

Tensor based framework for Distributed Denial of Service attack detection

2021 ◽  
Vol 174 ◽  
pp. 102894
Author(s):  
João Paulo A. Maranhão ◽  
João Paulo C.L. da Costa ◽  
Elnaz Javidi ◽  
César A. Borges de Andrade ◽  
Rafael T. de Sousa
Keyword(s):  
Denial Of Service ◽  
Attack Detection ◽  
Distributed Denial Of Service ◽  
Denial Of Service Attack ◽  
Service Attack
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