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Enregistrement W97579752

Privacy and security of smart grid communication

2011· article· en· W97579752 sur OpenAlexaffabout
Shahram Shah Heydari, Walid Rjaibi, Khalil El‐Khatib, Julie Thorpe

Notice bibliographique

RevueConference of the Centre for Advanced Studies on Collaborative Research · 2011
Typearticle
Langueen
DomaineEngineering
ThématiqueSmart Grid Security and Resilience
Établissements canadiensIBM (Canada)Ontario Tech University
Organismes subventionnairesnon disponible
Mots-clésSmart gridComputer scienceComputer securitySoftware deploymentGridControl (management)EngineeringElectrical engineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The concept of a Smart grid -- an intelligent and active power distribution network that uses advanced communication technology to collect and use real time operational information for efficient control of the grid -- has become one of the hottest research topics in the areas of information technology and electrical engineering. Governments and the private sector have started to invest billions of dollars into this new technology that will not only allow more efficient management of current grids, better load distribution, demand control, up-to-date status monitoring and faster failure recovery, but also promises better integration of new services and applications such as smart homes and intelligent appliances, new energy sources, and EV grids. These features will be made possible by a wide deployment of data collection devices such as embedded sensors, smart meters and communication networks to bring this data into control centres for analysis, as well as automated controls and algorithms for decision making based on the current status information. As more intelligence is built into the electrical grid, the issue of grid security becomes extremely important and must be considered within the broader field of cyber-security. The automated control functions of the smart grid could be manipulated by intruders to gain control of the power distribution networks, steal customer information, or inflict other damages. Network-based attacks may be used to disrupt the network, overload part of the grid or disconnect regions. The security of the access devices that provide real-time information must be examined carefully. A major challenge at the moment lies in the variety of options for Smart Grid Communication at both access and core networks. Smart meter communication and messaging technologies could be based on DLMS/COSEM standard or IP-based, using a wired or wireless sensor platform e.g. 6LoWPAN or IEEE802.15.4/Zigbee, in a mesh or cluster-based topology, connected using fibers or based on cellular technologies such as LTE or WiMax. The variety of technologies available poses an enormous challenge in incorporating security and survivability features into the Smart Grid design. Interoperability issues between devices pose further security challenges that must be addressed based on the undergoing standardization works, most notably the IEEE P2030 project. Overcoming security challenges in Smart Grid communication will require careful evaluation of the proposed communication technologies and their interoperation. This includes the creation of security test beds, which would allow examination of the survivability of the grid system against a variety of security attacks and further system hardening and the development of integrated simulation environments for the communication network and the power grid. Also required is the development of various components of a situational awareness system, such as Intrusion Detection and Prevention Systems and network management agents, to monitor and present the common operational picture (COP) of the grid from individual sensors and meters to the main controllers at the network control centers. In addition to the security of grid communication systems, the privacy of communication and consumer data are also extremely important, in particular in the case of Smart home/Smart Grid. This is because detailed consumer data may be collected and analyzed without active participation from the homeowner. The Canadian law greatly emphasizes the importance of protecting the privacy of users, and puts that responsibility squarely on the shoulder of data collectors, i.e. grid operators and utility companies in this case. Any design for Smart Grid communication must strike a delicate balance between functionality and privacy. While from an operational point of view it might be beneficial to collect and maintain detailed individual usage information in order to optimize the network operations, this would also cause significant privacy concerns if such data ever fell into the wrong hands or was used for individual identification in cases where consumer protection laws were applied. Many questions must be answered, for example: How do we aggregate data and minimize individual user identification without compromising the usefulness of data? How do we to maintain privacy of data along the entire path of the sensors and to the main databases? What is the most secure model for interactions between users and the Grid, to monitor and control the trust levels of devices that are connected to the Grid? The aim of this workshop was to explore the latest progress and research in the field of smart grid communication security and privacy, and to provide a forum for researchers, students and business experts from both academia and industry, to discuss the latest innovations and future works in the field. The new initiatives by federal and provincial government institutions in North America, including Ontario Smart Grid Initiative and British Columbia Smart Metering program, as well as the comprehensive US Policy Framework for the 21st Century Grid (released in June 2011) further highlight the urgency and importance of such discussion in academia and industry. Considering the broad challenges involved with the design and operation of Smart grids, this workshop focused on issues specifically dealing with security and privacy issues. The topics of interest for this workshop included the following: • Smart Grid Architecture Security • Smart Grid Security Risk Assessment • Smart Grid Physical and Device Security • Mitigating Cyber Attacks against the Smart Grid • Intrusion Detection for Smart Grid • Privacy Issues in Smart Metering • Smart Grid Resilience • Smart Grid Restoration and Failure Recovery • Grid Access and Sensor Network Security and Privacy • Evaluation of Smart Grid Communication Protocols • Smart Home Security and Privacy Issues • Trust models for Smart Grid/Smart Home Experts from the business and industry were invited to present an overview of the current trends and challenges in Smart grid security and privacy. Presentations from the academia provided a glance into the latest academic research for this field. The workshop was concluded with a panel discussion on the topic of information security and privacy that also set the agenda for future workshops of this kind.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,819
Score d'incertitude au seuil0,316

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,108
Tête enseignante GPT0,356
Écart entre enseignants0,248 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2011
Routes d'admission2
Résumé présentoui

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