1. A Practical Smart Metering System Supporting Privacy Preserving Billing and Load Monitoring Hsiao-Ying Lin National Chiao Tung University Joint work with Wen-Guey Tzeng, Shiuan-Tzuo Shen, Bao-Shuh P. Lin

2. Smart Grid =Intelligence + Automation + Power Grid ▫ Increase energy efficiency ▫ Improve system reliability & quality Massive electricity generator Grid operator Meter Electricity transmission & distribution Substation Resident area Renewable energy generator Intra/Internet Power flow Communication flow 2

3. Smart Grid Features Features ▫ Two-way power flows ▫ Communication systems among electricity entities Automatic Meter Reading Advanced Meter Infrastructure Smart Grid Application 3

4. Meter & Meter Reading Measurement of power consumption ▫ Traditional: manually record per month ▫ Smart meter: automatically record per minute ~ millisecond 4

5. Smart Grid Applications Automatic billing ▫ Support many price policies Load monitoring ▫ Monitor current state of smart grid Electricity Service Provider(ESP) Price information Time Price Power consumption Bill Power consumption Load Monitoring Center(LMC) 5

6. Example: Ontario Time-of-use Pricing During Winter Midnight Noon A.M. P.M. 7 5 11 7 Off-Peak 6.5 ￠ /kWh Mid-Peak 10 ￠ /kWh On-Peak 11.7 ￠ /kWh 6

7. Privacy Issue Detailed meter readings reveal daily activities ▫ When and what appliances are used 7 Hart, G.W: Nonintrusive appliance load monitoring, IEEE Proceedings 1992 Refrigerator Stove Burner Time(Min)

8. Privacy Preserving Automatic Billing Trusted third party computes the bill ▫ The grid operator Homomorphic commitment + zero knowledge proof (ZKP) ▫ Meter readings are committed ▫ The bill is computed by the consumer ▫ Only the bill is opened to ESP ▫ ESP verifies correctness of the bill by using ZKP 8

9. Privacy Preserving Load Monitoring Trusted third party aggregates the power consumption Secret shares of 0 among meters ▫ Need handling meter leaving and joining Random noises on meter readings ▫ LMC gets approximate sum of meter readings LMC E LMC (reading1) E LMC (reading3) E LMC (reading2) E LMC (sum of readings) TTP sum of readings Reading1+secret share1 Reading3+secret share3 Reading2+secret share2sum of readings LMC 9

10. Our Contribution A smart metering system ▫ Supporting automatic billing & load monitoring ▫ Privacy preserving against service providers  Electricity service provider (ESP)  Load monitoring center (LMC)  Storage service provider ▫ Using pseudo-random numbers & TPM ▫ Without a trusted third party ▫ Without mutual communication among meters 10

11. System Model display Barcode ID TPM module Meter Meter readings Area 1 Area 2 Time … … … … … … Area 2 Area 1 Storage system Load monitoring center (LMC) H1 M1H1 M1 H2 M2H2 M2 Electricity Service Provider (ESP) 11

12. Meter Model A meter has a trusted platform module Power consumption is measured in Wh per 5 min Present meter readings in integers 12

13. Arrange Encrypted Meter Readings Area 1 Area 2 H2 M2H2 M2 H3 M3H3 M3 H4 M4H4 M4 H 5 M 5 H6 M6H6 M6 H7 M7H7 M7 H8 M8H8 M8 Current time unit Current time window W (L time units) Area 3 H9 M9H9 M9 H1 M1H1 M1 13 L = 4

14. Requirements Assume all entities are semi-honest ESP can only query a meter for power consumption of aL continuous time units (each query) LMC can only query meters for meter readings at a time unit in a current time window W 14

15. Arrange Encrypted Meter Readings Area 1 Area 2 H2 M2H2 M2 H3 M3H3 M3 H4 M4H4 M4 H 5 M 5 H6 M6H6 M6 H7 M7H7 M7 H8 M8H8 M8 LMC Current time unit ESP Area 3 H9 M9H9 M9 H1 M1H1 M1 15 L = 4

16. Main Idea Encrypt meter readings: Let ESP know  16 Power consumption of Meter 1 during t 1 to t 4

17. Main Idea Encrypt meter readings: Service providers interact with meters ▫ ESP queries a meter for a sum of random numbers spanning over aL time units (horizontal block) ▫ LMC queries a set of meters for noised random numbers at a time unit in current time window W (vertical block) A meter has to remember all used random numbers 17

18. Arranging Random Numbers of a Meter TPM generates random numbers Driver computes random numbers … … … 18 L FIFO memory slots

19. Construction System parameter: A large number p Meter Initialization ▫ Pseudorandom number generator g ▫ Hash functions h and h’ Seed s i Master key k i =h’(s i ||SN i ) MiMi SN i L FIFO memory slots g(k i,t 1 ) g(k i,t 2 ) g(k i,t L-1 ) 19

20. Storage of meter readings At time unit t j ▫ Encrypt current reading d by using current r and store c ▫ Generate a new R: ▫ Compute a new r from R and store it in a memory slot r i,j r i,j+1 r i,j+L-2 r i,j+L r i,j+L-1 r i,j+L-2 r i,j+L-1 r i,j+1 20

21. Supporting Automatic Billing ESP accesses the storage system ESP queries M i for L continuous time units M i returns R i,j where ESP computes the power consumption ESP can query aL continuous time units for any integer a>0 Area 1 H1 M1H1 M1 21

22. Privacy Requirement We consider honest-but-curious ESP ESP cannot get individual meter readings of a household We prove that ESP cannot distinguish two sets of meter readings which have the same sum The proof relies on pseudorandom number generator g 22

23. Supporting Load Monitoring LMC accesses the storage system W is the current time window containing L time units LMC queries meters in an area for data in time unit t j in W A meter cannot directly return the random number r 23

24. Supporting Load Monitoring A meter returns [random number + noise] ▫ Normal distribution ▫ Select a random noise according to ▫ Read the random number from the FIFO memory slot ▫ Compute LMC computes [meter reading – noise] ▫ random number + noisePrevent overflowing 24

25. Correctness & Privacy LMC gets an approximate sum of m meter readings ▫ Real sum ▫ Define error ratio ▫ ▫ By Chebyshev inequality LMC gets only an approximate value Average of meter reading per time unit Tradeoff : correctness and privacy A smaller a better approximate 25

26. Performance Analysis |p|=64, a time unit is 5 min Commercial TPM chip ▫ 1024-bit RSA signature: 100ms Assumption ▫ 1024-bit random number generation:100ms ▫ 64-bit random number is about 7ms ▫ 64-bit modular addition: 7ms Computation can be done in a time unit 26

27. Summary Design a smart metering system ▫ Using external storage service ▫ Supporting privacy preserving billing & load monitoring ▫ W/O a trusted third party and heavy crypto-operation 27

28. Future Work Consider integrity of meter readings Evaluate performance by prototype systems Eliminate interactions between meters & providers Consider a bidirectional smart meter model 28