SpliDT Decision Trees Dataset

In this data repository, we share seven datasets used for training and testing of SpliDT decision trees: <b>C</b><b>IC-IDS-2017-PCAPS1-f10: </b>A network intrusion detection dataset for various attack scenarios, including DoS, DDoS, and brute force.<b>CIC-IDS-2018-PCAPS1-f10: </b>An anomaly detection dataset capturing network traffic for diverse attacks and benign activities.<b>CIC-IoMT-2024-PCAPS1-f10: </b>A cybersecurity dataset with Internet of Medical Things (IoMT) traffic for intrusion detection in healthcare.<b>CIC-IOT-2023-32-PCAPS1-f10: </b>A comprehensive IoT dataset containing multi-class network traffic data for evaluating IoT security threats.<b>CIC-IOT-2023-PCAPS1-f10: </b>A simplified version of the CIC-IoT-2023 dataset, categorized into four primary classes of IoT traffic.<b>ISCXVPN2016-PCAPS0-f10: </b>A dataset containing VPN and non-VPN traffic for evaluating VPN detection and privacy-related analyses.<b>UCSBFinetuning-PCAPS0-f10: </b>UCSB campus dataset containing various application types, including web, cloud, social, and, streaming traffic.These are the inputs required to evaluate SpliDT as described in "SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate", NSDI'26.