Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization
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Summary
A reliable dataset that contains benign and seven common attack network flows, which meets real world criteria and is publicly avaliable is produced.
- Type
- article
- Published
- 2018-01-01
- Cited by
- 5,083
- References
- 27
- Access
- Open access
- OpenAlex
- https://openalex.org/W2789828921
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:4707749
Keywords
Intrusion detection system, Computer science, Intrusion, Data mining, Geology
References
- Network Intrusion Detection and Prevention - Concepts and Techniques
- Toward Instrumenting Network Warfare Competitions to Generate Labeled Datasets
- Evaluating host-based anomaly detection systems: Application of the one-class SVM algorithm to ADFA-LD
- Generation of a new IDS test dataset: Time to retire the KDD collection
- Testing Intrusion detection systems
- Statistical analysis of honeypot data and building of Kyoto 2006+ dataset for NIDS evaluation
- Evaluating host-based anomaly detection systems: A preliminary analysis of ADFA-LD
- Toward developing a systematic approach to generate benchmark datasets for intrusion detection
- Evaluating data mining procedures: techniques for generating artificial data sets
- Anomaly Based Intrusion Detection Using Hybrid Learning Approach of Combining k-Medoids Clustering and Naïve Bayes Classification
- A detailed analysis of the KDD CUP 99 data set
- Analysis of the 1999 DARPA/Lincoln Laboratory IDS evaluation data with NetADHICT
- Uses and Challenges for Network Datasets
- Forensic investigation of the OneSwarm anonymous filesharing system
- Unknown Attacks Detection Using Feature Extraction from Anomaly-Based IDS Alerts
- A critical evaluation of datasets for investigating IDSs and IPSs researches
- Characterization of Tor Traffic using Time based Features
- An Evaluation Framework for Intrusion Detection Dataset
- Towards a Reliable Intrusion Detection Benchmark Dataset
- A Labeled Data Set for Flow-Based Intrusion Detection
Cited by
- Progress in Artificial Intelligence: 19th EPIA Conference on Artificial Intelligence, EPIA 2019, Vila Real, Portugal, September 3–6, 2019, Proceedings, Part I
- Intrusion detection system for wireless mesh network using multiple support vector machine classifiers with genetic-algorithm-based feature selection
- Sequence Aggregation Rules for Anomaly Detection in Computer Network Traffic
- A Comparison of Header and Deep Packet Features when Detecting Network Intrusions
- How to Test an IDS?: GENESIDS: An Automated System for Generating Attack Traffic
- Study of long short-term memory in flow-based network intrusion detection system
- Testing IDS using GENESIDS: Realistic Mixed Traffic Generation for IDS Evaluation
- ALDD: A Hybrid Traffic-User Behavior Detection Method for Application Layer DDoS
- Accelerating VNF-based Deep Packet Inspection with the use of GPUs
- Real-time Intrusion Detection using Multidimensional Sequence-to-Sequence Machine Learning and Adaptive Stream Processing
- Building an emulation environment for cyber security analyses of complex networked systems
- Compression Analytics for Classification and Anomaly Detection Within Network Communication
- Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset
- Network traffic fusion and analysis against DDoS flooding attacks with a novel reversible sketch
- A new method for assigning appropriate labels to create a 28 Standard Android Botnet Dataset (28-SABD)
- Investigation of network intrusion detection using data visualization methods
- Chained Anomaly Detection Models for Federated Learning: An Intrusion Detection Case Study
- A holistic review of Network Anomaly Detection Systems: A comprehensive survey
- Infrastructure for Generating New IDS Dataset
- A Novel Hierarchical Intrusion Detection System Based on Decision Tree and Rules-Based Models
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