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Record W97579752

Privacy and security of smart grid communication

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

Bibliographic record

VenueConference of the Centre for Advanced Studies on Collaborative Research · 2011
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsIBM (Canada)Ontario Tech University
Fundersnot available
KeywordsSmart gridComputer scienceComputer securitySoftware deploymentGridControl (management)EngineeringElectrical engineering
DOInot available

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.108
GPT teacher head0.356
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2011
Admission routes2
Has abstractyes

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