CREATING SYNTHETIC ATTACKS WITH EVOLUTIONARY ALGORITHMS FOR INDUSTRIAL-CONTROL-SYSTEM SECURITY TESTING
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Authors
Haynes, Nathaniel J.
Subjects
synthetic attack
evolutionary algorithm
industrial control system
security testing
honeypot
Log4j
IEC 60870-5-104
evolutionary algorithm
industrial control system
security testing
honeypot
Log4j
IEC 60870-5-104
Advisors
Rowe, Neil C.
Nguyen, Thuy D.
Date of Issue
2022-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
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Abstract
Cybersecurity defenders can use honeypots (decoy systems) to capture and study adversarial activities. An issue with honeypots is obtaining enough data on rare attacks. To improve data collection, we created a tool that uses machine learning to generate plausible artificial attacks on two protocols, Hypertext Transfer Protocol (HTTP) and IEC 60870-5-104 (“IEC 104” for short, an industrial-control-system protocol). It uses evolutionary algorithms to create new variants of two cyberattacks: Log4j exploits (described in CVE-2021-44228 as severely critical) and the Industroyer2 malware (allegedly used in Russian attacks on Ukrainian power grids). Our synthetic attack generator (SAGO) effectively created synthetic attacks at success rates up to 70 and 40 percent for Log4j and IEC 104, respectively. We tested over 5,200 unique variations of Log4j exploits and 256 unique variations of the approach used by Industroyer2. Based on a power-grid honeypot’s response to these attacks, we identified changes to improve interactivity, which should entice intruders to mount more revealing attacks and aid defenders in hardening against new attack variants. This work provides a technique to proactively identify cybersecurity weaknesses in critical infrastructure and Department of Defense assets.
Type
Thesis
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Department
Computer Science (CS)
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Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.