Preserving data integrity for smart grid data aggregation

Li, Fengjun; Luo, Bo

doi:10.1109/smartgridcomm.2012.6486011

Cited by 79 publications

(90 citation statements)

References 28 publications

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“…However, these solutions are either not compatible with the privacy-preserving in-network data aggregation or introduce excessive hop-by-hop verification overhead. Recently, Li et al proposed an authentication scheme that supports batch verification based on a homomorphic signature scheme [22]. However, all these solutions adopt prevention-based approaches, which can detect false data injected by network errors or external attackers without knowledge of the secrets associated with the encryption and signature schemes.…”

Section: Related Workmentioning

confidence: 99%

“…However, all these solutions adopt prevention-based approaches, which can detect false data injected by network errors or external attackers without knowledge of the secrets associated with the encryption and signature schemes. Although [22] also proposed a centralized anomaly detection scheme, this scheme introduced a large lose to in-network aggregation. The focus of our work is on a solution for efficient detection of falsified data that are injected into smart grid data aggregation by compromised or malfunctioning meters in a distributed manner.…”

Section: Related Workmentioning

confidence: 99%

“…To protect the integrity of the metering data, several signaturebased approaches have been proposed [14,21,22]. [22] presented a homomorphic signature algorithm based on a short signature scheme using bilinear pairing. It assumes all the smart meters use a same private signing key SK sig to generate the signature σ i , which can be aggregated as i=1→t σ i along with the in-network aggregation of the ciphertext messages.…”

Section: Secure In-network Aggregationmentioning

confidence: 99%

“…Unfortunately, there is only a few work that takes a difference approach other than prevention to address this problem. To the best of our knowledge, [22] was among the first to examine this problem with an attestation-based solution. The incremental integrity check proposed in [22] can be used to verify the aggregate-so-far results based on homomorphic signatures.…”

Section: Introductionmentioning

confidence: 99%

“…To the best of our knowledge, [22] was among the first to examine this problem with an attestation-based solution. The incremental integrity check proposed in [22] can be used to verify the aggregate-so-far results based on homomorphic signatures. It also incorporates anomaly detection at the collector to identify irregular data values potentially caused by accidental errors or malicious attacks.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Securing Smart Grid In-Network Aggregation through False Data Detection

Yang¹,

Li²

2017

EAI Endorsed Transactions on Industrial Networks and Intelligen

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Existing prevention-based secure in-network data aggregation schemes for the smart grids cannot effectively detect accidental errors and falsified data injected by malfunctioning or compromised meters. In this work, we develop a light-weight anomaly detector based on kernel density estimator to locate the smart meter from which the falsified data is injected. To reduce the overhead at the collector, we design a dynamic grouping scheme, which divides meters into multiple interconnected groups and distributes the verification and detection load among the root of the groups. To enable outlier detection at the root of the groups, we also design a novel data re-encryption scheme based on bilinear mapping so that data previously encrypted using the aggregation key is transformed in a form that can be recovered by the outlier detectors using a temporary re-encryption key. Therefore, our proposed detection scheme is compatible with existing innetwork aggregation approaches based on additive homomorphic encryption. We analyze the security and efficiency of our scheme in terms of storage, computation and communication overhead, and evaluate the performance of our outlier detector with experiments using real-world smart meter consumption data. The results show that the performance of the light-weight detector yield high precision and recall.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Secure In-network Aggregationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Securing Smart Grid In-Network Aggregation through False Data Detection

Yang¹,

Li²

2017

EAI Endorsed Transactions on Industrial Networks and Intelligen

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Cyber Security of Smart Meters

Sánchez

Aung³

et al. 2016

Smart Grid Handbook

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The recently emerging advanced metering infrastructure (AMI) is envisioned to be one of the most prominent features of the smart grid. Security, especially authentication, is crucial for the success of large‐scale AMI deployment. Unfortunately, authentication schemes relying on per‐packet signature and per‐signature verification introduce heavy cost for computation and communication. Due to resource constraints, smart meter authentication requirements cannot be satisfied by this scheme. In this chapter, a new authentication architecture for AMI is described to validate the delay‐tolerant metering data. In this chapter, not only a set of efficient authentication schemes, but more importantly, their corresponding fault diagnosis algorithms will be recited. The authentication scheme incurs substantially lighter overheads than those by the existing schemes, while it can effectively address the formidable authentication challenges in AMI.

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