TY  - EJOU
AU  - Nawaz, Gul 
AU  - Junaid, Muhammad 
AU  - Akhunzada, Adnan 
AU  - Gani, Abdullah 
AU  - Nawazish, Shamyla 
AU  - Yaqub, Asim 
AU  - Ahmed, Adeel 
AU  - Ajab, Huma 

TI  - Detecting and Mitigating DDOS Attacks in SDNs Using Deep Neural Network
T2  - Computers, Materials \& Continua

PY  - 2023
VL  - 77
IS  - 2
SN  - 1546-2226

AB  - Distributed denial of service (DDoS) attack is the most common attack that obstructs a network and makes it
unavailable for a legitimate user. We proposed a deep neural network (DNN) model for the detection of DDoS
attacks in the Software-Defined Networking (SDN) paradigm. SDN centralizes the control plane and separates
it from the data plane. It simplifies a network and eliminates vendor specification of a device. Because of this
open nature and centralized control, SDN can easily become a victim of DDoS attacks. We proposed a supervised
Developed Deep Neural Network (DDNN) model that can classify the DDoS attack traffic and legitimate traffic.
Our Developed Deep Neural Network (DDNN) model takes a large number of feature values as compared to
previously proposed Machine Learning (ML) models. The proposed DNN model scans the data to find the
correlated features and delivers high-quality results. The model enhances the security of SDN and has better
accuracy as compared to previously proposed models. We choose the latest state-of-the-art dataset which consists of
many novel attacks and overcomes all the shortcomings and limitations of the existing datasets. Our model results
in a high accuracy rate of 99.76% with a low false-positive rate and 0.065% low loss rate. The accuracy increases to
99.80% as we increase the number of epochs to 100 rounds. Our proposed model classifies anomalous and normal
traffic more accurately as compared to the previously proposed models. It can handle a huge amount of structured
and unstructured data and can easily solve complex problems.
KW  - Distributed denial of service (DDoS) attacks; software-defined networking (SDN); classification; deep neural network (DNN)

DO  - 10.32604/cmc.2023.026952