Secure University Modbus Middleware Infrastructure Testbed (SUMMIT)

A paired dataset of plaintext and TLS-encrypted Modbus/TCP traffic from an identical industrial source, supporting machine learning-based network intrusion detection research.

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Citation

Using this work? Please cite as:

Lawrence, H., Zhuang, Y., Bloom, G., Evaluating the Resilience of Flow-Based Machine Learning Classifiers on Encrypted ICS Traffic, IEEE Transactions on Industrial Informatics, 2026.

Overview

SUMMIT provides the first high-fidelity, paired dataset of plaintext Modbus/TCP and TLS-encrypted Modbus/TCP Security traffic from an identical source. The data was generated on a simulated water treatment plant (WTP) testbed running in Kubernetes, following the Purdue Enterprise Reference Architecture. Traffic was captured over cleartext Modbus (TCP port 502) and Modbus/TCP Security (TCP port 802) to enable direct comparative analysis of machine learning classifiers on encrypted ICS traffic.

Raw Packet Captures

All pcap files are hosted on DigitalOcean Spaces. Downloads are organized by protocol (NON-TLS / TLS) and scenario type (normal / attack).

SUMMIT-NON-TLS (Plaintext Modbus/TCP)

Scenario File Description
Normal normal_non-tls_90000s (19.6 MB) Baseline benign traffic — 2026-02-02
Normal normal_non-tls_90000s (19.7 MB) Baseline benign traffic — 2026-02-04
Reconnaissance recon (58.5 MB) Network scanning followed by flood DoS
C2 c2 (14.8 MB) DNS beaconing to attacker-controlled domain
Write Coil write_coil (5.3 MB) Unauthorized WRITE_COIL command injection
Replay replay (1.4 MB) Stateful replay of legitimate control command
Flood flood (247.0 MB) High-volume flood attack
Coordinated Attack coordinated (0.2 MB) Distributed command injection from multiple agents

SUMMIT-TLS (Encrypted Modbus/TCP Security)

Scenario File Description
Normal normal_tls_90000s (21.6 MB) Baseline benign traffic — 2026-02-02
Normal normal_tls_90000s (21.7 MB) Baseline benign traffic — 2026-02-04
Reconnaissance recon (85.8 MB) Network scanning followed by flood DoS
C2 c2 (17.1 MB) DNS beaconing to attacker-controlled domain
Write Coil write_coil (7.0 MB) Unauthorized WRITE_COIL command injection
Replay replay (2.0 MB) Stateful replay of legitimate control command
Flood flood (244.5 MB) High-volume flood attack
Coordinated Attack coordinated (0.7 MB) Distributed command injection from multiple agents

Feature Engineering

Raw packet captures were processed using NFStream to extract flow-based features, producing bidirectional network flows. Each row represents a single flow with columns corresponding to extracted features (flow duration, packet/byte counts, TCP flags, IP addresses, ports, and protocol metadata). No payload data is included. The resulting parquet files contain label-encoded categorical features (IP addresses) for direct compatibility with machine learning pipelines.

Pipeline code (GitHub)

Dataset Statistics

Metric SUMMIT-NON-TLS SUMMIT-TLS
Total Flows 200,639 201,235
Attack Flows 160,105 160,740
Normal Flows 40,534 40,495
Imbalance Ratio 0.798 0.799
Feature File Size 274 MB 282 MB

SUMMIT dataset — Secure University Modbus Middleware Infrastructure Testbed