DataZoo: Streamlining Traffic Classification Experiments
The machine learning communities, such as those around computer vision or natural language processing, have developed numerous supportive tools and benchmark datasets to accelerate the development. In contrast, the network traffic classification field lacks standard benchmark datasets for most tasks, and the available supportive software is rather limited in scope. This paper aims to address the gap and introduces DataZoo, a toolset designed to streamline dataset management in network traffic classification and to reduce the space for potential mistakes in the evaluation setup. DataZoo provides a standardized API for accessing three extensive datasets -- CESNET-QUIC22, CESNET-TLS22, and CESNET-TLS-Year22. Moreover, it includes methods for feature scaling and realistic dataset partitioning, taking into consideration temporal and service-related factors. The DataZoo toolset simplifies the creation of realistic evaluation scenarios, making it easier to cross-compare classification methods and reproduce results.
Code (1)
Tasks
ClassificationManagementTraffic ClassificationSimilar Papers 제목 키워드 기반
Generic Multi-modal Representation Learning for Network Traffic Analysis
Network traffic analysis is fundamental for network management, troubleshooting, and security. Tasks such as traffic classification, anomaly detection, and novelty discovery are fundamental for extracting operational inf…
Anomaly DetectionFeature EngineeringRepresentation LearningTraffic ClassificationEnergy-Guided Data Sampling for Traffic Prediction with Mini Training Datasets
Recent endeavors aimed at forecasting future traffic flow states through deep learning encounter various challenges and yield diverse outcomes. A notable obstacle arises from the substantial data requirements of deep lea…
Deep LearningTraffic PredictionArtificial Intelligence in Traffic Systems
Existing research on AI-based traffic management systems, utilizing techniques such as fuzzy logic, reinforcement learning, deep neural networks, and evolutionary algorithms, demonstrates the potential of AI to transform…
Autonomous VehiclesEvolutionary AlgorithmsManagementTraffic Signal ControlStreamlining HTTP Flooding Attack Detection through Incremental Feature Selection
Applications over the Web primarily rely on the HTTP protocol to transmit web pages to and from systems. There are a variety of application layer protocols, but among all, HTTP is the most targeted because of its versati…
feature selectionSmart City Transportation: Deep Learning Ensemble Approach for Traffic Accident Detection
The dynamic and unpredictable nature of road traffic necessitates effective accident detection methods for enhancing safety and streamlining traffic management in smart cities. This paper offers a comprehensive explorati…
Deep LearningManagementOptical Flow EstimationTraffic Accident Detection