Application of Decision Tree Classifier in Detection of Specific Denial of Service Attacks with Genetic Algorithm Based Feature Selection on NSL-KDD
Using a Genetic Algorithm and Decision Tree Classifier, the features of the NSL-KDD dataset are reduced using combinatorial optimization to determine the minimum features required to accurately classify Denial of Service attacks within the NSL-KDD dataset.
Code (0)
등록된 구현이 없습니다.
Tasks
Combinatorial Optimizationfeature selectionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced Datasets
Cybersecurity has become essential worldwide and at all levels, concerning individuals, institutions, and governments. A basic principle in cybersecurity is to be always alert. Therefore, automation is imperative in proc…
Anomaly DetectionBinary ClassificationFraud DetectionIntrusion Detection+2Tree in Tree: from Decision Trees to Decision Graphs
Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree in Tree decision graph (TnT), a framewo…
Layered Logic Classifiers: Exploring the `And' and `Or' Relations
Designing effective and efficient classifier for pattern analysis is a key problem in machine learning and computer vision. Many the solutions to the problem require to perform logic operations such as `and', `or', and `…
Pedestrian DetectionSemantic SegmentationMobility Mode Detection Using WiFi Signals
We utilize Wi-Fi communications from smartphones to predict their mobility mode, i.e. walking, biking and driving. Wi-Fi sensors were deployed at four strategic locations in a closed loop on streets in downtown Toronto. …
Cost-Aware Robust Tree Ensembles for Security Applications
There are various costs for attackers to manipulate the features of security classifiers. The costs are asymmetric across features and to the directions of changes, which cannot be precisely captured by existing cost mod…
Spam detection