Privacy Issues in Smart Grid

1. Privacy Issues in Smart Grid R. Newman

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

3. Smart Grid • 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

4. 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

5. Smart Grid Threats • 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!

6. Consumer Load Data • 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

7. Load Balancing • 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

8. Utility Sensor Information • 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

9. Hiding Auction 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

10. Auction Model • 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

11. 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

12. Auction Protocol • 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

13. 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

14. 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

15. 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

16. Take-away • 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