Intrusion Detection System Based on Neural Networks Using Bipolar Input with Bipolar Sigmoid Activation Function
Vulnerabilities in common security components such as firewalls are inevitable. Intrusion Detection Systems (IDS) are used as another wall to protect computer systems and to identify corresponding vulnerabilities. The purpose of this paper is to use Backpropagation algorithm for IDS by applying bipo...
Main Authors: | Adel Issa, Adnan Abdulazeez |
---|---|
Format: | Article |
Language: | Arabic |
Published: |
Mosul University
2011-12-01
|
Series: | Al-Rafidain Journal of Computer Sciences and Mathematics |
Subjects: | |
Online Access: | https://csmj.mosuljournals.com/article_163644_a9bd6deea1d616fc8e682b3a54eba967.pdf |
Similar Items
-
Design of Intrusion Detection System for Internet of Things Based on Improved BP Neural Network
by: Aimin Yang, et al.
Published: (2019-01-01) -
PERFORMANCE COMPARISON FOR INTRUSION DETECTION SYSTEM USING NEURAL NETWORK WITH KDD DATASET
by: S. Devaraju, et al.
Published: (2014-04-01) -
GLOBAL AND LOCAL CLUSTERING SOFT ASSIGNMENT FOR INTRUSION DETECTION SYSTEM: A COMPARATIVE STUDY
by: Mohd Rizal Kadis, et al.
Published: (2017-06-01) -
A New Intrusion Detection System Based on Fast Learning Network and Particle Swarm Optimization
by: Mohammed Hasan Ali, et al.
Published: (2018-01-01) -
A Framework for implementing an ML or DL model to improve Intrusion Detection Systems (IDS) in the NTMA context, with an example on the dataset (CSE-CIC-IDS2018)
by: Azeroual Hakim, et al.
Published: (2022-01-01)