Mendeley
TY  _  JOUR
ID  -  1403013146422
TI  -  Providing an Intrusion Detection System in the Industrial Internet of Things Using the Gray Wolf Algorithm
JO  -  Journal of Information and Communication Technology
JA  -  ES
LA  -  fa
SN  -  2717-0411
AU  -  Alimohamadi Sajad
AU  -  Fathi Mohammad
AD  -  
AD  -  دانشگاه کردستان
Y1  -  2024
PY  -  2024
VL  -  61
IS  -  
SP  -  218
EP  -  228
KW  -  Intrusion detection system
KW  -   gray wolf algorithm
KW  -   industrial internet of things
DO  -  
N2  -  <p>Security is a main goal in the design of industrial Internet of Things network. Due to the ever-increasing developments in the Internet of Things, it is necessary to use new methods to detect active network attacks. In this article, an intrusion detection system for industrial Internet of Things is proposed. This system uses the combination of gray wolf meta-heuristic algorithms (GWO) and decision tree (DT), nearest neighbor (KNN) and artificial neural network (ANN) classification algorithms. First, the data is pre-processed and then normalized, in the next step, data feature extraction is performed using the gray wolf algorithm to extract its independent and effective features. Then it is trained using classification algorithms and finally evaluated. The obtained results show that the use of the combined GWO-ANN algorithm with 93.22% accuracy has a better performance in detecting attacks. Also, the ANN algorithm is more accurate than the DT and KNN algorithms when combined with the GWO algorithm. ,</p>
UR  - rimag.ir/en/Article/46422
L1  - rimag.ir/en/Article/Download/46422
ER  -  
