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Home » Cloudy with a Chance of Breach: Forecasting Cyber Security Incidents
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Cloudy with a Chance of Breach: Forecasting Cyber Security Incidents

Authors: 

Yang Liu, Armin Sarabi, Jing Zhang, and Parinaz Naghizadeh, University of Michigan; Manish Karir, QuadMetrics, Inc.; Michael Bailey, University of Illinois at Urbana-Champaign; Mingyan Liu, University of Michigan and QuadMetrics, Inc.

Abstract: 

In this study we characterize the extent to which cyber security incidents, such as those referenced by Verizon in its annual Data Breach Investigations Reports (DBIR), can be predicted based on externally observable properties of an organization’s network. We seek to proactively forecast an organization’s breaches and to do so without cooperation of the organization itself. To accomplish this goal, we collect 258 externally measurable features about an organization’s network from two main categories: mismanagement symptoms, such as misconfigured DNS or BGP within a network, and malicious activity time series, which include spam, phishing, and scanning activity sourced from these organizations. Using these features we train and test a Random Forest (RF) classifier against more than 1,000 incident reports taken from the VERIS community database, Hackmageddon, and theWeb Hacking Incidents Database that cover events from mid-2013 to the end of 2014. The resulting classifier is able to achieve a 90% True Positive (TP) rate, a 10% False Positive (FP) rate, and an overall 90% accuracy.

Yang Liu, University of Michigan

Armin Sarabi, University of Michigan

Jing Zhang, University of Michigan

Parinaz Naghizadeh, University of Michigan

Manish Karir, QuadMetrics, Inc.

Michael Bailey, University of Illinois at Urbana-Champaign

Mingyan Liu, University of Michigan and QuadMetrics, Inc.

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BibTeX
@inproceedings {191002,
author = {Yang Liu and Armin Sarabi and Jing Zhang and Parinaz Naghizadeh and Manish Karir and Michael Bailey and Mingyan Liu},
title = {Cloudy with a Chance of Breach: Forecasting Cyber Security Incidents},
booktitle = {24th USENIX Security Symposium (USENIX Security 15)},
year = {2015},
isbn = {978-1-939133-11-3},
address = {Washington, D.C.},
pages = {1009--1024},
url = {https://www.usenix.org/conference/usenixsecurity15/technical-sessions/presentation/liu},
publisher = {USENIX Association},
month = aug,
}
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