STSRS: A New Dataset for Simulating Security Threats in Smart Railway Systems

Mays Abukeshek; Mohammed Al-Mhiqani; Simon Parkinson

STSRS: A New Dataset for Simulating Security Threats in Smart Railway Systems

Mays Abukeshek, Mohammed Al-Mhiqani, Simon Parkinson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The digitalisation of railway systems has improved efficiency but introduced vulnerabilities in train-to-control communications. To address the lack of realistic datasets for cyber-physical railway systems, this paper introduces STSRS (Security Threats in Smart Railway Systems), a high-fidelity time-series corpus for cybersecurity and intelligent transport research. STSRS contains over 10 million synchronised records simulating interactions between 10 autonomous trains and two control centres under both normal and adversarial scenarios (DoS, Jamming, Stealthy Replay). Generated using a modular framework with stochastic dynamics, TCP/IP telemetry, and context-aware attack injection, each record includes over 10 labelled features spanning raw (e.g., speed, latency) and behavioural (e.g., Burstiness, Entropy) metrics. STSRS supports reproducible anomaly detection, cyber-defence modelling, and digital twin evaluation in railway CPS environments.

Original language	English
Title of host publication	12th International Conference on Information Systems Security and Privacy
Subtitle of host publication	ICISSP 2026
Publisher	SciTePress
Publication status	Accepted/In press - 15 Jan 2026
Event	12th International Conference on Information Systems Security and Privacy - Barceló Marbella hotel, Marbella, Spain Duration: 4 Mar 2026 → 6 Mar 2026 https://icissp.scitevents.org/

Conference

Conference	12th International Conference on Information Systems Security and Privacy
Abbreviated title	ICISSP 2026
Country/Territory	Spain
City	Marbella
Period	4/03/26 → 6/03/26
Internet address	https://icissp.scitevents.org/

Cite this

@inproceedings{ffcd30b22bc24bd8be6be88e7092cc8c,

title = "STSRS: A New Dataset for Simulating Security Threats in Smart Railway Systems",

abstract = "The digitalisation of railway systems has improved efficiency but introduced vulnerabilities in train-to-control communications. To address the lack of realistic datasets for cyber-physical railway systems, this paper introduces STSRS (Security Threats in Smart Railway Systems), a high-fidelity time-series corpus for cybersecurity and intelligent transport research. STSRS contains over 10 million synchronised records simulating interactions between 10 autonomous trains and two control centres under both normal and adversarial scenarios (DoS, Jamming, Stealthy Replay). Generated using a modular framework with stochastic dynamics, TCP/IP telemetry, and context-aware attack injection, each record includes over 10 labelled features spanning raw (e.g., speed, latency) and behavioural (e.g., Burstiness, Entropy) metrics. STSRS supports reproducible anomaly detection, cyber-defence modelling, and digital twin evaluation in railway CPS environments.",

keywords = "Security threats, Smart railway systems, STSRS",

author = "Mays Abukeshek and Mohammed Al-Mhiqani and Simon Parkinson",

year = "2026",

month = jan,

day = "15",

language = "English",

booktitle = "12th International Conference on Information Systems Security and Privacy",

publisher = "SciTePress",

address = "Portugal",

note = "12th International Conference on Information Systems Security and Privacy, ICISSP 2026 ; Conference date: 04-03-2026 Through 06-03-2026",

url = "https://icissp.scitevents.org/",

}

TY - GEN

T1 - STSRS

T2 - 12th International Conference on Information Systems Security and Privacy

AU - Abukeshek, Mays

AU - Al-Mhiqani, Mohammed

AU - Parkinson, Simon

PY - 2026/1/15

Y1 - 2026/1/15

N2 - The digitalisation of railway systems has improved efficiency but introduced vulnerabilities in train-to-control communications. To address the lack of realistic datasets for cyber-physical railway systems, this paper introduces STSRS (Security Threats in Smart Railway Systems), a high-fidelity time-series corpus for cybersecurity and intelligent transport research. STSRS contains over 10 million synchronised records simulating interactions between 10 autonomous trains and two control centres under both normal and adversarial scenarios (DoS, Jamming, Stealthy Replay). Generated using a modular framework with stochastic dynamics, TCP/IP telemetry, and context-aware attack injection, each record includes over 10 labelled features spanning raw (e.g., speed, latency) and behavioural (e.g., Burstiness, Entropy) metrics. STSRS supports reproducible anomaly detection, cyber-defence modelling, and digital twin evaluation in railway CPS environments.

AB - The digitalisation of railway systems has improved efficiency but introduced vulnerabilities in train-to-control communications. To address the lack of realistic datasets for cyber-physical railway systems, this paper introduces STSRS (Security Threats in Smart Railway Systems), a high-fidelity time-series corpus for cybersecurity and intelligent transport research. STSRS contains over 10 million synchronised records simulating interactions between 10 autonomous trains and two control centres under both normal and adversarial scenarios (DoS, Jamming, Stealthy Replay). Generated using a modular framework with stochastic dynamics, TCP/IP telemetry, and context-aware attack injection, each record includes over 10 labelled features spanning raw (e.g., speed, latency) and behavioural (e.g., Burstiness, Entropy) metrics. STSRS supports reproducible anomaly detection, cyber-defence modelling, and digital twin evaluation in railway CPS environments.

KW - Security threats

KW - Smart railway systems

KW - STSRS

M3 - Conference contribution

BT - 12th International Conference on Information Systems Security and Privacy

PB - SciTePress

Y2 - 4 March 2026 through 6 March 2026

ER -

STSRS: A New Dataset for Simulating Security Threats in Smart Railway Systems

Abstract

Conference

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