SKM: Scalable Key Management for Advanced Metering Infrastructure in Smart Grids

Wan, Zhiguo; Wang, Guilin; Yang, Yanjiang; Shi, Shan

doi:10.1109/tie.2014.2331014

Cited by 102 publications

(85 citation statements)

References 20 publications

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“…We compare our four schemes with the two most recent proposed schemes, i.e. Liu's et al scheme [22] and SKM+ [23], to illustrate how the multi-group key structure improve the performance of key management.…”

Section: Simulations and Performance Comparisonmentioning

confidence: 99%

“…Moreover, we assume that the batch rekeying runs twice a week. Storage and Communication overhead of Liu's et al scheme and SKM+ scheme are readily obtained from [22] and [23].…”

Section: Dynamic Membership Modelmentioning

confidence: 99%

“…Furthermore, Liu's et al [22] scheme is not tolerant to packet loss. Wan et al [23] proposed an improvement for Liu's et al scheme, called SKM, which combines identity-based cryptosystem [37] and One-way Function Trees (OFT) approach [38] for multicast key management. The use of an OFT separately for each DR program results in non-negligible overhead for keys storage at smart meters that have limited storage capacities.…”

Section: Introductionmentioning

confidence: 99%

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VerSAMI: Versatile and Scalable key management for Smart Grid AMI systems

et al. 2018

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In this paper, we propose four new key management schemes for Advanced Metering Infrastructure (AMI) to secure data communications in the Smart Grid (SG). The schemes are based on individual and batch rekeying operations using a novel multi-group key graph structure, are also versatile in the sense that they can support broadcast, unicast, as well as multicast communications. Security analysis shows that our schemes satisfy key management security properties. Furthermore, performance analysis and simulation results demonstrate that our schemes can scale to large AMI systems, and they incur low cost in terms of storage, communication overheads and time of key distribution compared to state-of-the-art schemes.

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Section: Simulations and Performance Comparisonmentioning

confidence: 99%

“…Moreover, we assume that the batch rekeying runs twice a week. Storage and Communication overhead of Liu's et al scheme and SKM+ scheme are readily obtained from [22] and [23].…”

Section: Dynamic Membership Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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VerSAMI: Versatile and Scalable key management for Smart Grid AMI systems

et al. 2018

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“…In [15], a key management scheme for Advanced Metering Infrastructure (AMI) is proposed, which is based on a key tree structure. However, the authors of [22] found that it is susceptible to de-synchronisation attacks, while it lacks scalability due to inefficient key management. For this reason, they proposed Scalable Key Management (SKM), which utilises ID-based encryption and a key graph technique for efficient multicast key management.…”

Section: Related Workmentioning

confidence: 99%

Self-organised Key Management for the Smart Grid

Demertzis

Καρόπουλος

Xenakis

et al. 2015

Ad-Hoc, Mobile, and Wireless Networks

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Abstract. As Smart Grid deployments emerge around the world, their protection against cyberattacks becomes more crucial. Before protective measures are put into place, one of the main factors to be considered is key management. Smart Grid poses special requirements compared to traditional networks; however, the review of previous work reveals that existing schemes are not complete. Here we propose a scalable and distributed key management scheme for the Smart Grid based on the Web-of-Trust concept. Our proposal is build on top of a Distributed Hash Table for efficient lookups of trust relationships. The target of this scheme is to create a key management system for the Smart Grid without the need of an always available Trusted Third Party. The underlying Distributed Hash Table can be further utilised as an infrastructure to build other Smart Grid services on top of it, like secure and/or anonymous aggregation, billing, etc.

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“…In recent years, increasing electricity consumption has caused terrible power shortage and brings a lot of inconvenience to the citizens. One reason is that traditional grid uses a rigid system with many deficiencies [6,7], including: (i) the power transmission process is lack of flexibility; (ii) the self-recovery capability is low and its duration is long; (iii) the electric services only support simple user operations; (iv) information sharing is largely limited. These defects are becoming more and more obvious so that the grid is hard to constitute a real-time and efficient power system.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Markov-Difference Based Power Consumption Prediction for Smart Grids

Le¹,

He²

2017

Journal of Electrical Engineering and Technology

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-Power prediction is critical to improve power efficiency in Smart Grids. Markov chain provides a useful tool for power prediction. With careful investigation of practical power datasets, we find an interesting phenomenon that the stochastic property of practical power datasets does not follow the Markov features. This mismatch affects the prediction accuracy if directly using Markov prediction methods. In this paper, we innovatively propose a spatial transform based data processing to alleviate this inconsistency. Furthermore, we propose an enhanced power prediction method, named by Spatial Mapping Markov-Difference (SMMD), to guarantee the prediction accuracy. In particular, SMMD adopts a second prediction adjustment based on the differential data to reduce the stochastic error. Experimental results validate that the proposed SMMD achieves an improvement in terms of the prediction accuracy with respect to state-of-the-art solutions.

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SKM: Scalable Key Management for Advanced Metering Infrastructure in Smart Grids

Cited by 102 publications

References 20 publications

VerSAMI: Versatile and Scalable key management for Smart Grid AMI systems

VerSAMI: Versatile and Scalable key management for Smart Grid AMI systems

Self-organised Key Management for the Smart Grid

Enhanced Markov-Difference Based Power Consumption Prediction for Smart Grids

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