Year: 2025
Type: article
Abstract: As wireless communications evolve, many community protection threats additionally evolve. Intrusion Detection System (IDS) detects assaults and facilitates perceive attackers. In the past, various system mastering (ML) strategies have been used with intrusion detection systems (IDS) in an attempt to improve intrusion detection effects and enhance the accuracy of IDS. Using major issue analysis (PCA), random woodland class, SVM, and naive base algorithms, this work proposes a method to expand an effective IDS. According to the effects of the proposed approach, the execution time (min) is three.24 mins, the accuracy charge (%) is 96.Seventy eight%, and the mistake rate (%) is zero.21%.
Authors: Onteddu Venkata Dharani -, M.Narasimha Yadav -, Basireddy Sireesha -, Chenna Raghava -, Angadala Sathish -
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409617265