*.pcap
Identifying patterns in the modus operandi of attackers is an essential requirement in the study of Advanced Persistent Threats. Previous studies have been hampered by the lack of accurate, relevant, and representative datasets of current threats. System logs and network traffic captured during attacks on real companies’ information systems are the best data sources to build such datasets. Unfortunately, for apparent reasons of companies’ reputation, privacy, and security, such data is seldom available.
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The dataset is generated by performing different Man-in-the-Middle (MiTM) attacks in the synthetic cyber-physical electric grid in RESLab Testbed at Texas AM University, US. The testbed consists of a real-time power system simulator (Powerworld Dynamic Studio), network emulator (CORE), Snort IDS, open DNP3 master, SEL real-time automation controller (RTAC), and Cisco Layer-3 switch. With different scenarios of MiTM attack, we implement a logic-based defense mechanism in RTAC and save the traffic data and related cyber alert data under the attack.
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The dataset is oriented on encrypted traffic classification problems. The dataset contains three classes of flows: web flows, YouTube flows, and Netflixflows. These classes are chosen because web and video traffic account for 90% of global traffic, while YouTube and Netflix are the largest video services. The structure of the dataset is as follows. It includes 100 download traces of the most popular web pages according to https://httparchive.org, 100 the most popular YouTube videos, and 50 Netflix series and movies.
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This data set contains packet captures (PCAPs) of a 5G campus network.
The corresponding paper can be found at 5G Campus Networks: A First Measurement Study
Acknowledgement:
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Datasets as described in the research paper "Intrusion Detection using Network Traffic Profiling and Machine Learning for IoT Applications".
There are two main dataset provided here, firstly is the data relating to the initial training of the machine learning module for both normal and malicious traffic, these are in binary visulisation format, compresed into the document traffic-dataset.zip.
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