CICFlowmeter-V4.0 (formerly known as ISCXFlowMeter) is a network traffic Bi-flow generator and analyzer for anomaly detection that has been used in many Cybersecurity datsets such as Android Adware-General Malware dataset (CICAAGM2017), IPS/IDS dataset (CICIDS2017), Android Malware dataset (CICA...
The CSE-CIC IDS datasets published in 2017 and 2018 have both attracted considerable scholarly attention towards research in intrusion detection systems. Recent work published using this dataset indicates little attention paid to the imbalance of the dataset. The study presented in this paper sets out...
NF-CSE-CIC-IDS2018-v2_cv-全量 8 NF-CSE-CIC-IDS2018-v2_cv 全量预处理生成。由源文件(https://rdm.uq.edu.au/files/ce5161d0-ef9c-11ed-827d-e762de186848)预处理生成。数据包括:n_features, e_features, edge_index,edge_label, tvt, label2idx,edge_ids,node_label...
Testing Incremental Learning methods on the CIC IDS 2018 dataset The Jupyter notebook tests the effects of learning new classes incrementally for a CNN model using the CIC IDS 2018 dataset from https://www.kaggle.com/datasets/solarmainframe/ids-intrusion-csv. The CSV files are downloaded to goog...
Kanimozhi, V., Jacob, T.P.: Artificial intelligence-based network intrusion detection with hyper-parameter optimization tuning on the realistic cyber dataset CSE-CIC- IDS2018 using cloud computing. In: 2019 international conference on communication and signal processing (ICCSP). IEEE (2019) Google ...
Intrusion Detection Evaluation Dataset (CIC-IDS2017) https://www.unb.ca/cic/datasets/ids-2017.html
CIC-IDS-2017 入侵检测数据集,包含以下8个CSV文件:可以用于机器学习的训练 Friday-WorkingHours-Afternoon-DDos.pcap_ISCX.csv Friday-WorkingHours-Afternoon-PortScan.pcap_ISCX.csv Friday-WorkingHours-Morning.pcap_ISCX.csv Monday-WorkingHours.pcap_ISCX.csv ...
CICFlowmeter-V4.0 (formerly known as ISCXFlowMeter) is an Ethernet traffic Bi-flow generator and analyzer for anomaly detection that has been used in many Cybersecurity datsets such as Android Adware-General Malware dataset (CICAAGM2017), IPS/IDS dataset
This repository contains an in-depth analysis of the Intrusion Detection Evaluation Dataset (CIC-IDS2017) for Intrusion Detection, showcasing the implementation and comparison of different machine learning models for binary and multi-class classification
Ali Ghorbani. Please cite their original paper. The dataset offers an extended set of Distributed Denial of Service attacks, most of which employ some form of amplification through reflection. The dataset shares its feature set with the other CIC NIDS datasets, IDS2017, IDS2018 and DoS2017...