TY - GEN
T1 - Multi-vendor penetration testing in the advanced metering infrastructure
AU - McLaughlin, Stephen
AU - Podkuiko, Dmitry
AU - Miadzvezhanka, Sergei
AU - Delozier, Adam
AU - McDaniel, Patrick
PY - 2010
Y1 - 2010
N2 - The advanced metering infrastructure (AMI) is revolutionizing electrical grids. Intelligent AMI "smart meters" report real time usage data that enables efficient energy generation and use. However, aggressive deployments are outpacing security efforts: new devices from a dizzying array of vendors are being introduced into grids with little or no understanding of the security problems they represent. In this paper we develop an archetypal attack tree approach to guide penetration testing across multiple-vendor implementations of a technology class. In this, we graft archetypal attack trees modeling broad adversary goals and attack vectors to vendor-specific concrete attack trees. Evaluators then use the grafted trees as a roadmap to penetration testing. We apply this approach within AMI to model attacker goals such as energy fraud and denial of service. Our experiments with multiple vendors generate real attack scenarios using vulnerabilities identified during directed penetration testing, e.g., manipulation of energy usage data, spoofing meters, and extracting sensitive data from internal registers. More broadly, we show how we can reuse efforts in penetration testing to efficiently evaluate the increasingly large body of AMI technologies being deployed in the field.
AB - The advanced metering infrastructure (AMI) is revolutionizing electrical grids. Intelligent AMI "smart meters" report real time usage data that enables efficient energy generation and use. However, aggressive deployments are outpacing security efforts: new devices from a dizzying array of vendors are being introduced into grids with little or no understanding of the security problems they represent. In this paper we develop an archetypal attack tree approach to guide penetration testing across multiple-vendor implementations of a technology class. In this, we graft archetypal attack trees modeling broad adversary goals and attack vectors to vendor-specific concrete attack trees. Evaluators then use the grafted trees as a roadmap to penetration testing. We apply this approach within AMI to model attacker goals such as energy fraud and denial of service. Our experiments with multiple vendors generate real attack scenarios using vulnerabilities identified during directed penetration testing, e.g., manipulation of energy usage data, spoofing meters, and extracting sensitive data from internal registers. More broadly, we show how we can reuse efforts in penetration testing to efficiently evaluate the increasingly large body of AMI technologies being deployed in the field.
UR - http://www.scopus.com/inward/record.url?scp=78751557822&partnerID=8YFLogxK
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U2 - 10.1145/1920261.1920277
DO - 10.1145/1920261.1920277
M3 - Conference contribution
AN - SCOPUS:78751557822
SN - 9781450301336
T3 - Proceedings - Annual Computer Security Applications Conference, ACSAC
SP - 107
EP - 116
BT - Proceedings - 26th Annual Computer Security Applications Conference, ACSAC 2010
PB - IEEE Computer Society
ER -