Chaotic-based optimization, based feature selection with shallow neural network technique for effective identification of intrusion detection
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.spl.24Keywords:
Chaotic optimization, Feature selection, Shallow neural networks, Intrusion detection, cybersecurity.Dimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The work in this paper attempts to deal with intrusion detection using a chaotic-based optimization technique and feature selection + shallow neural networks. The idea of chaotic systems is used to get randomness in the feature selection process, which can enable a shallow neural network to perform better for intrusion detection. Experiments on benchmark datasets reveal the effectiveness of this proposed solution by significant improvements in detection accuracy, false positive reduction at run-time and computational efficiency as compared to conventional methods.Abstract
How to Cite
Downloads
Similar Articles
- P. Ananthi, A. Chandrabose, Exploring learning-assisted optimization for mobile crowd sensing , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Mufeeda V. K., R. Suganya, Novel deep learning assisted plant leaf classification system using optimized threshold-based CNN , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Jayaganesh Jagannathan, Dr. Agrawal Rajesh K, Dr. Neelam Labhade-Kumar, Ravi Rastogi, Manu Vasudevan Unni, K. K. Baseer, Developing interpretable models and techniques for explainable AI in decision-making , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- C. Muruganandam, V. Maniraj, A Self-driven dual reinforcement model with meta heuristic framework to conquer the iot based clustering to enhance agriculture production , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Archana Dhamotharan, Kanthalakshmi Srinivasan, Analog Circuits Based Fault Diagnosis using ANN and SVM , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- M. Menaha, J. Lavanya, Crop yield prediction in diverse environmental conditions using ensemble learning , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Neerav Nishant, Nisha Rathore, Vinay Kumar Nassa, Vijay Kumar Dwivedi, Thulasimani T, Surrya Prakash Dillibabu, Integrating machine learning and mathematical programming for efficient optimization of electric discharge machining technique , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Radha K. Jana, Dharmpal Singh, Saikat Maity, Modified firefly algorithm and different approaches for sentiment analysis , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Lakshminarayani A, A Shaik Abdul Khadir, A blockchain-integrated smart healthcare framework utilizing dynamic hunting leadership algorithm with deep learning-based disease detection and classification model , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Sreenath M.V. Reddy, D. Annapurna, Anand Narasimhamurthy, Influence node analysis based on neighborhood influence vote rank method in social network , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- S. Hemalatha, N. Vanjulavalli, K. Sujith, R. Surendiran, Effective gorilla troops optimization-based hierarchical clustering with HOP field neural network for intrusion detection , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- V. Seethala Devi, N. Vanjulavalli, K. Sujith, R. Surendiran, A metaheuristic optimisation algorithm-based optimal feature subset strategy that enhances the machine learning algorithm’s classifier performance , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper