An efficient distributed approach for key management in microgrids

Baza, Mohamed; Fouda, Mostafa M.; Eldien, Adly S. Tag; Mansour, Hala A.

doi:10.1109/icenco.2015.7416320

Cited by 15 publications

(6 citation statements)

References 17 publications

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“…and f 5 (•), α and β(d, t j ) are random variables that are uniformly distributed over the interval [0.1, 0.6] [1]. For attack f 3 (•), t s (d) is a uniform random variable in [0,42], and the duration of the attack, i.e., t f (d) − t s (d), is a uniform random variable in [8,48], and hence, the maximum value of t f (d) = 48. Applying the electricity theft attack's functions on each SM's readings results inX SM i dataset which contains 536 honest samples (days) and 3, 216 malicious samples.…”

Section: B: Electricity Theft Attacksmentioning

confidence: 99%

PPETD: Privacy-Preserving Electricity Theft Detection Scheme With Load Monitoring and Billing for AMI Networks

et al. 2019

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In advanced metering infrastructure (AMI) networks, smart meters installed at the consumer side should report fine-grained power consumption readings (every few minutes) to the system operator for billing, real-time load monitoring, and energy management. On the other hand, the AMI networks are vulnerable to cyber-attacks where malicious consumers report false (low) electricity consumption to reduce their bills in an illegal way. Therefore, it is imperative to develop schemes to accurately identify the consumers that steal electricity by reporting false electricity usage. Most of the existing schemes rely on machine learning for electricity theft detection using the consumers' fine-grained power consumption meter readings. However, this fine-grained data that is used for electricity theft detection, load monitoring, and billing can also be misused to infer sensitive information regarding the consumers such as whether they are on travel, the appliances they use, and so on. In this paper, we propose an efficient and privacy-preserving electricity theft detection scheme for the AMI network and we refer to it as PPETD. Our scheme allows system operators to identify the electricity thefts, monitor the loads, and compute electricity bills efficiently using masked fine-grained meter readings without violating the consumers' privacy. The PPETD uses secret sharing to allow the consumers to send masked readings to the system operator such that these readings can be aggregated for the purpose of monitoring and billing. In addition, secure two-party protocols using arithmetic and binary circuits are executed by the system operator and each consumer to evaluate a generalized convolutional-neural network model on the reported masked fine-grained power consumption readings for the purpose of electricity theft detection. An extensive analysis of real datasets is performed to evaluate the security and the performance of the PPETD. Our results confirm that our scheme is accurate in detecting fraudulent consumers with privacy preservation and acceptable communication and computation overhead.INDEX TERMS Privacy preservation, machine learning, electricity theft detection, dynamic billing, secure multi-party computation. I. INTRODUCTIONElectricity theft is a serious problem in the existing power grid, which causes great economic loss. Many countries experience a considerable amount of electricity theft. In the UnitedThe associate editor coordinating the review of this manuscript and approving it for publication was Mehedi Masud.

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Section: B: Electricity Theft Attacksmentioning

confidence: 99%

PPETD: Privacy-Preserving Electricity Theft Detection Scheme With Load Monitoring and Billing for AMI Networks

et al. 2019

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“…Currently, several AKA schemes for microgrids have been discussed, but some have proved insecure and vulnerable to different attacks. In 2015, Baza et al [7] proposed a distributed key management scheme for microgrids, utilizing the one-way function tree technique. However, the scheme is not flexible enough for nodes to join or leave the microgrid because this necessitates updating the partial key, which also increases the risk of inconsistency.…”

Section: Related Workmentioning

confidence: 99%

Quantum-Resistant Lightweight Authentication and Key Agreement Protocol for Fog-Based Microgrids

2021

IEEE Access

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A microgrid is a flexible and localized grid that can disconnect from the main grid and operate independently on the traditional and/or renewable resource. It also can work with the main grid, and even provide power to the main grid when it has excess power to help relieve the pressure of energy. The flow of power between main grid and microgrid is monitored by smart meter, which kept the end user's privacy information and his/her energy usage in real time. Hence, ensuring the privacy and security of these information is a considerable challenge. In this paper, we investigate the relationship between microgrids and the main grid, and design a quantum-resistant lightweight authentication and key agreement (AKA) protocol based on fog computing. The proposed protocol provides the mutual authentication and generates a session key between a smart meter and a fog node. More importantly, it can resist against quantum computing attacks, as the security of our scheme relies on the hardness of the learning parity with noise (LPN) problem, an NP-complete problem. Finally, we evaluate the performance of our proposed protocol and prove that our protocol is more lightweight and efficient.

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“…This solution cannot cope with (C1), presented in the previous section. In [18] the functionality of the proposed distributed key management approach for microgrids is based on an oneway function tree. In this case, partial key update is needed when nodes join or leave the microgrid (C1).…”

Section: Related Workmentioning

confidence: 99%

Distributed Key Management in Microgrids

Bolgouras¹,

Ntantogian

Panaousis

et al. 2020

IEEE Trans. Ind. Inf.

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Security for smart industrial systems is prominent due to the proliferation of cyber threats threatening national critical infrastructures. Smart grid comes with intelligent applications that can utilize the bidirectional communication network among its entities. Microgrids are small-scale smart grids that enable Machine-to-Machine (M2M) communications as they can operate with some degree of independence from the main grid. In addition to protecting critical microgrid applications, an underlying key management scheme is needed to enable secure M2M message transmission and authentication. Existing key management schemes are not adequate due to microgrid special features and requirements. We propose the Micro sElf-orgaNiSed mAnagement (MENSA), which is the first hybrid key management and authentication scheme that combines Public Key Infrastructure (PKI) and Web-of-Trust concepts in microgrids. Our experimental results demonstrate the efficiency of MENSA in terms of scalability and swiftness.

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An efficient distributed approach for key management in microgrids

Cited by 15 publications

References 17 publications

PPETD: Privacy-Preserving Electricity Theft Detection Scheme With Load Monitoring and Billing for AMI Networks

PPETD: Privacy-Preserving Electricity Theft Detection Scheme With Load Monitoring and Billing for AMI Networks

Quantum-Resistant Lightweight Authentication and Key Agreement Protocol for Fog-Based Microgrids

Distributed Key Management in Microgrids

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