Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

Kumar, Pardeep; Lin, Yun; Bai, Guangdong; Paverd, Andrew; Dong, Jin Song; Martin, Andrew

doi:10.1109/comst.2019.2899354

Cited by 260 publications

(133 citation statements)

References 188 publications

(349 reference statements)

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“…Other attacks [9] against smart meter networks are: The Jabbering attack that takes place on end-to-end links were the attacker places a malicious smart meter which sends flooding traffic, causes de-synchronizations, so connection is interrupted. Other examples of attack include fake control signals, resynchronizing, and puppet attack.…”

Section: Related Workmentioning

confidence: 99%

Securing the Smart Grid: A Blockchain-based Secure Smart Energy System

Suciu¹,

Sachian²,

Dobrea³

et al. 2019

2019 54th International Universities Power Engineering Conference (UPEC)

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This paper presents how a Smart Grid system is secured and how blockchain implementation provides confidentiality and integrity for such a system. One main issue that has to be addressed in smart grid systems is databases security. Blockchain has been proven to be a safe alternative to be used in mining systems because it allows a secure applicability in databases. Another important feature is that each hash in a crypto mining system cannot be changed if it has such an algorithm behind its build, thus resulting in a secure and reliable system. This paper aims to show how blockchain can affect and be used in a smart power management system going forth from the SealedGRID platform. This system enables the user to monitor in real time the power usage in a smart grid system, therefore, this platform being built with security and resilience against attacks in mind.

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Section: Related Workmentioning

confidence: 99%

Securing the Smart Grid: A Blockchain-based Secure Smart Energy System

Suciu¹,

Sachian²,

Dobrea³

et al. 2019

2019 54th International Universities Power Engineering Conference (UPEC)

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“…Kumar et al [12] presented a brief overview of real cyber-attack targeting smart metering network. They classified these threats into three categories: threats in system-level security, threats and/or theft of services, threats to privacy.…”

Section: Privacy-preservingmentioning

confidence: 99%

A DNA-based Privacy-preserving Scheme in Smart-grid

Abed¹

2019

IJCIS

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Smart grid utility provider collects consumers' power consumption data for three main reasons: billing, analysis, and operation. Billing needs coarse-grained data where there are no, or minimal, privacy concerns. While analysis and operation needs fine-grained data which can highly explore consumers' privacy. Hence, consumers might be reluctant to allow for operational metering to protect their privacy.This paper presents detail description of a reliable DNA-based privacy-preserving (DNAPP) scheme in smart grid. DNAPP assures robust authentication, confidentiality, message integrity, and nonrepudiation across the smart grid as well as assuring high consumers' privacy. The scheme demonstrates many good security features, such as: high complexity of O(n!), lightweight , scalable, minimum overhead, no cryptography key exchange between the communicating parties as each of them can determine the key locally and independently. This scheme does not require any level of modifications to the existing smart grid infrastructure or smart meter. It only requires some software modifications.

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“…Both academia and industry have identified novel authentication and access control mechanisms that can enhance the overall security and safety of SG [ 6 , 7 , 8 ]. In particular, the IEC 62351 standard [ 9 ] defines appropriate solutions aiming to meet the security gaps of the vulnerable SCADA communication protocols.…”

Section: Introductionmentioning

confidence: 99%

ARIES: A Novel Multivariate Intrusion Detection System for Smart Grid

Radoglou-Grammatikis

Sarigiannidis

Efstathopoulos³

et al. 2020

Sensors

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The advent of the Smart Grid (SG) raises severe cybersecurity risks that can lead to devastating consequences. In this paper, we present a novel anomaly-based Intrusion Detection System (IDS), called ARIES (smArt gRid Intrusion dEtection System), which is capable of protecting efficiently SG communications. ARIES combines three detection layers that are devoted to recognising possible cyberattacks and anomalies against (a) network flows, (b) Modbus/Transmission Control Protocol (TCP) packets and (c) operational data. Each detection layer relies on a Machine Learning (ML) model trained using data originating from a power plant. In particular, the first layer (network flow-based detection) performs a supervised multiclass classification, recognising Denial of Service (DoS), brute force attacks, port scanning attacks and bots. The second layer (packet-based detection) detects possible anomalies related to the Modbus packets, while the third layer (operational data based detection) monitors and identifies anomalies upon operational data (i.e., time series electricity measurements). By emphasising on the third layer, the ARIES Generative Adversarial Network (ARIES GAN) with novel error minimisation functions was developed, considering mainly the reconstruction difference. Moreover, a novel reformed conditional input was suggested, consisting of random noise and the signal features at any given time instance. Based on the evaluation analysis, the proposed GAN network overcomes the efficacy of conventional ML methods in terms of Accuracy and the F1 score.

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Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

Cited by 260 publications

References 188 publications

Securing the Smart Grid: A Blockchain-based Secure Smart Energy System

Securing the Smart Grid: A Blockchain-based Secure Smart Energy System

A DNA-based Privacy-preserving Scheme in Smart-grid

ARIES: A Novel Multivariate Intrusion Detection System for Smart Grid

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