Privacy Issues in Smart Grid R. Newman

Topics Defining anonymity Need for anonymity Defining privacy Threats to anonymity and privacy Mechanisms to provide anonymity Metrics for Anonymity Applications of anonymity technology

The electrical grid encompasses: Electrical power generation Electrical power distribution Electrical power consumption Originally Generation plant produced power Converted to high voltage AC for long distance distribution Converted to medium voltage AC for intermediate distance distribution Converted to low voltage AC to supply customers Smart Grid

Now: Smart Grid Multiple generation plants produce power Must coordinate interconnected grid Consumer power generation (solar power) Consumer involvment in load manipulation Incentives to reduce load at peak usage times Power consumption monitoring for user control Prices according to current and projected loads All this requires reporting of power data Smart Grid

Consumer privacy Usage may reveal lifestyle information Usage may reveal occupation of home Hence, need privacy! Accurate data needed for utilities Needed to project loads Used for pricing – liars can game system! Needed to coordinate interconnected grids Innaccurate data can cause disruption! Smart Grid Threats

Loading patterns reveal usage Usage reveals lifestyle, presence Periodic loads = A/C, refridgerator, etc. Load info can reveal appliance model! Lighting, microwave use – show presence Absence = attractive target for burglars Hiding load information Aggregate data Use energy storage to balance load Use energy generation to balance load Consumer Load Data

Storage Use batteries to increase load during low usage periods (charge batteries) Use batteries to decrease load during peak periods (draw power from batteries) Can use electric vehicle batteries for storage Must take usage patterns into account Desirable for economic reasons also Generation Use set points in PhotoVoltaic (solar) generation to alter efficiency, hence output Generator & batteries may be combined Load Balancing

Needed to assess current load & predict load Pricing is based on predicted loads Prices for energy consumption Prices for energy generation (offer/bid) Manipulation of data can cause economic losses Need fair auction mechanisms Sensor data needed for grid synchronization Voltage Frequency Phase Utility Sensor Information

Utility wants to pay lowest price Pricing is based on predicted loads and bids Protocol to offer rates, receive bids, then repeat Must hold accepted bids as contracts Suppliers want to get highest price Information about other suppliers is valuable If less supply, then can ask more for energy Users want to preserve privacy For safety and personal reasons For economic reasons Hiding Auction Information

Storage units generate & store, buy low, sell high Aggregator Act as communication intermediary Bidirectional Utility company Calculates loads and supply Decides when to ask for more power Decides how much to offer for power Auction Model

Cryptographic Approach Hide bids using crypto Aggregate bid information Utility obtains aggregate bids only Initialization by trusted third party (TTP) All parties supplied with public and private keys All parties supplied with certificates Auction Model

Utility sends power request to Aggregator Offers prices per time slot for t slots Bilinear pairing used for signature Aggregator broadcasts request to suppliers Validates freshness using timestamps Verifies signature using utility public key Suppliers offer bids Aggregator combines bids Utility assesses bids Auction Protocol

Utility sends power request to Aggregator Aggregator broadcasts request to suppliers Suppliers offer bids Amount of power offered per time slot Zero if none available or prices is too low Bids masked using one-time random shared key – allows utilties to verify aggregate bids but not see individual bids Computes signature Computes MAC Auction Protocol

Utility sends power request to Aggregator Aggregator broadcasts request to suppliers Suppliers offer bids Aggregator combines bids Verifies signatures Aggregates masked bids into masked aggreate bid Aggregates signatures into aggregate signature Aggregates MACs into aggregate MAC Aggregation by summation Care taken that there can be no overflow/carry Auction Protocol

Utility sends power request to Aggregator Aggregator broadcasts request to suppliers Suppliers offer bids Aggregator combines bids, sends to utility Utility assesses bids Verifies aggregate signature, MAC Determines aggregated bid per slot Auction Protocol

Security receiving increasing attention in Smart Grid operations Conflicting needs between data resolution and accuracy on one hand, and privacy on other Mechanisms to hide load information Mechanisms to allow grid synchronization Mechanisms to support anonymous auctions and other economic activities Take-away