Python
cybersecurity
2023
ID: 1CP0712
Increasing the Performance of Machine Learning-Based IDS on an Imbalanced and Up-to-Date Dataset
Keywords:
Intrusion
Detection
System,
CSE-CIC-IDS2018,
Imbalanced
Dataset,
Machine
Learning,
Random
Forest,
KNN,
SVM,
Network
Security
Project Synopsis & Overview
This project develops a machine learning-based intrusion detection system using the up-to-date, imbalanced CSE-CIC-IDS2018 dataset to improve detection of rarely encountered attacks. Network traffic data is preprocessed, split into training and testing sets, and used to train K-Nearest Neighbor, Random Forest, Support Vector Machine, and Decision Tree models, classifying traffic as normal or intrusive, reducing false alarms and missed detections.
Complete Technical Specifications
| Project ID | 1CP0712 (DB ID: 712) |
| Project Title | Increasing the Performance of Machine Learning-Based IDS on an Imbalanced and Up-to-Date Dataset |
| Domain Division | Python |
| Sub-Domain / Tech | cybersecurity |
| IEEE Year | 2023 |
| Package Price | ₹6500 |
| Created Date | Nov 13, 2026 |
Project Price
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₹8000
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