Energy Theft in the Advanced Metering Infrastructure

McLaughlin, S.W.; Podkuiko, Dmitry; McDaniel, Patrick

doi:10.1007/978-3-642-14379-3_15

Cited by 176 publications

(105 citation statements)

References 5 publications

Supporting

Mentioning

103

Contrasting

Unclassified

Order By: Relevance

“…Moreover, if the smart meter is physically tampered, the hackers can capture optical port protocol used to communicate with smart meters. If the smart meter is opened, they will put a reader device on this port to capture the other password for other protocols [13]. Without firmware integrity protections in smart meters, meter storage can also be tampered.…”

Section: Threats a Smart Metersmentioning

confidence: 99%

Advanced Metering Infrastructure Security Issues and its Solution: A Review

XU¹

2015

IJIRCCE

View full text Add to dashboard Cite

Advanced metering infrastructure (AMI) is the core component in smart grid. Moreover, two-way communication between the user and the power utility is realized through AMI. Composition of AMI is described. AMI security requirements are illustrated. The threats on the smart meters, communications network, and data collector are analyzed, respectively. Passive and active defenses are investigated. For the passive defense, the traditional encryption technology has low key transportation security, while the public key infrastructure (PKI) used in the whole smart grid has high cost and long computation time and current ID-based authentication mechanism does not offer mutual authentication between smart meter and smart device. When intrusion detection system (IDS) is deployed on AMI key nodes, it is possible to meet the cost effectiveness and computational efficiency and to make up for the passive security policy.

show abstract

Section: Threats a Smart Metersmentioning

confidence: 99%

Advanced Metering Infrastructure Security Issues and its Solution: A Review

XU¹

2015

IJIRCCE

View full text Add to dashboard Cite

show abstract

“…It does this by recursively breaking down a goal into finer-and finergrained subgoals and finally to a set of attacks that achieve the original goal. An example attack tree that formed the genesis of this work [5] is shown in Figure 1. The root specifies the end goal, committing energy fraud by forging the energy usage information reported to the utility.…”

Section: Approachmentioning

confidence: 99%

“…Academic and industrial pen-testing efforts have found flaws in smart meter hardware [13], firmware [14] and network protocols [5]. Recently, Pacific Gas and Electric (PG&E) has experienced problems with measurement accuracy and meter network connectivity in their 5 million meter deployment, one of the largest in the US [15].…”

Section: A Ami Security Concernsmentioning

confidence: 99%

Structured security testing in the smart grid

McDaniel

McLaughlin

2012

2012 5th International Symposium on Communications, Control and Signal Processing

Self Cite

View full text Add to dashboard Cite

Abstract-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 often outpace security efforts: new devices from a dizzying array of vendors are being introduced into grids with limited 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. 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. We provide a detailed example of one such attack as tested using our developed methodology.

show abstract

“…A good example of such issues can be seen in the domain for Smart Metering. In the Netherlands the government intended to make a compulsory roll out of meters as part of a national energy reduction plan, but this was curbed when privacy issues were raised [12]. The scheme is now voluntary and the issues of recording of device level data in the home can be seen to raise other privacy and trust risks for consumers [28].…”

Section: Introductionmentioning

confidence: 99%

Risk driven Smart Home resource management using cloud services

Kirkham

Armstrong

Djemame

et al. 2014

Future Generation Computer Systems

View full text Add to dashboard Cite

In order to fully exploit the concept of the Smart Home, challenges associated with multiple device management in consumer facing applications have to be addressed. Specific to this is the management of resource usage in the home via the improved utilisation of devices, this is achieved by integration with the wider environment they operate in. The traditional model of the isolated device no longer applies, the future home will be connected with services provided by third parties ranging from supermarkets to domestic appliance manufacturers. In order to achieve this risk based integrated device management and contextualization is explored in this paper based on the cloud computing model. We produce an architecture and evaluate risk models to assist in this management of devices from a security, privacy and resource management perspective. We later propose and expansion on the risk based approach to wider data sharing between the home and external services using the key indicators of TREC (Trust, Risk, Eco-efficiency and Cost). The paper contributes to Smart Home research by defining how Cloud service management principles of risk and contextualization for virtual machines can produce solutions to emerging challenges facing a new generation of Smart Home devices.

show abstract

Energy Theft in the Advanced Metering Infrastructure

Cited by 176 publications

References 5 publications

Advanced Metering Infrastructure Security Issues and its Solution: A Review

Advanced Metering Infrastructure Security Issues and its Solution: A Review

Structured security testing in the smart grid

Risk driven Smart Home resource management using cloud services

Contact Info

Product

Resources

About