数据来源:https://www.unb.ca/cic/datasets/ids-2017.html 入侵检测系统(IDSs)和入侵防御系统(IPSs)是抵御复杂且不断增长的网络攻击的最重要的防御工具。由于缺乏可靠的测试和验证数据集,基于异常的入侵检测方法正面临着一致和准确的性能演化。 我们对自1998年以来现有的11个数据集的评估表明,大多数数据集已经过时...
CICIDS2017数据集包含良性和最新的常见攻击,与真实的现实世界数据(PCAPs)相类似。它还包括使用CICFlowMeter进行网络流量分析的结果,并根据时间戳、源和目的IP、源和目的端口、协议和攻击来标记流量(CSV文件)。此外,还提供了提取的特征定义。 生成真实的背景流量是我们建立这个数据集的首要任务。我们使用了我们提出的B-...
https://www.unb.ca/cic/datasets/ids-2017.html
Intrusion Detection Evaluation Dataset (CIC-IDS2017) 数据集 数据集简介 对自1998年以来现有的11个数据集的评估表明,大多数数据集(比如经典的KDDCUP99,NSLKDD等——就是上一个章节的数据集,笔者注)已经过时且不可靠。其中一些数据集缺乏流量多样性和容量,一些数据集没有涵盖各种已知的攻击,而另一些数据集将数据...
A comparative analysis of the performance of deep neural network, convolutional neural network, and long short-term memory using the CIC-IDS 2017 dataset.doi:10.11591/ijece.v13i1.pp1134-1141Jose, JinsiJose, Deepa V.International Journal of Electrical & Computer Engineering (2088-8708)...
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
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...
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 ...
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
预处理文件 随机采样40% 交叉验证。数据包含n_features, e_features, edge_index,edge_label, tvt, label2idx,edge_ids,node_label