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Privacy Strategies in Smart Metering Source: http://abstrusegoose.com/553 Tobias Klenze: Privacy Strategies in Smart Metering 1 Privacy Strategies in Smart Metering Tobias Klenze Chair for Network Architectures and Services Department for

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Privacy Strategies in Smart Metering

Source: http://abstrusegoose.com/553

Tobias Klenze: Privacy Strategies in Smart Metering 1

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Privacy Strategies in Smart Metering

Tobias Klenze

Chair for Network Architectures and Services Department for Computer Science Technische Universit¨ at M¨ unchen

June 13, 2014

Tobias Klenze: Privacy Strategies in Smart Metering 2

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Outline

1

Smart Meters

2

Real-time data aggregation

3

Billing protocols

4

Conclusions

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Outline

1

Smart Meters

2

Real-time data aggregation

3

Billing protocols

4

Conclusions

Tobias Klenze: Privacy Strategies in Smart Metering 4

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What’s a “Smart Meter”?

Normal Meter

Kristoferb, CC-BY-SA 3.0

Smart Meter

EVB Energy, CC-BY-SA 3.0

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(Supposed) Advantages of Smart Meters

Smart Meters! What are they good for?

1 Automated billing (no physical inspections) 2 Complex tariffs (e.g. electricity costs more in peak times) 3 “Smart” devices take tariffs into account 4 Grid / plant management – forecasting of consumption

demand

5 Leak detection

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Smart Meter Deployment

EU directive: 80% deployment by 2020. Investments: 3.15 billion Euro in the EU already. Smart Meters will come to you as well

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Smart Meter Deployment

EU directive: 80% deployment by 2020. Investments: 3.15 billion Euro in the EU already. Smart Meters will come to you as well

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The Problem: High-frequency data

Readings intervals Normal Meters: once per month. Low frequency, no problem Smart Meters: once per 15 minutes. High frequency, problematic

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The Problem: High-frequency data

Readings intervals Normal Meters: once per month. Low frequency, no problem Smart Meters: once per 15 minutes. High frequency, problematic

Source: Private Memoirs of a Smart Meter, 2010, Molina-Markham, Shenoy, Prashant et al

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Outline

1

Smart Meters

2

Real-time data aggregation

3

Billing protocols

4

Conclusions

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Aggregating real-time data

Goal: Provide real-time usage data to grid & utility provider AND respect privacy. Problem: Providers poorly define what data they need.

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Approaches for real-time data sharing

Idea: Preprocess (obfuscate) consumption data. Quantization works well, Down-sampling not as much. Problem: Still some predictions are possible. Idea: Aggregate data of different households (without trusted third party).

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Approaches for real-time data sharing

Idea: Preprocess (obfuscate) consumption data. Quantization works well, Down-sampling not as much. Problem: Still some predictions are possible. Idea: Aggregate data of different households (without trusted third party).

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Homomorphic encryption

Homomorphic encryption = Messing with ciphertext Allows modification of ciphertext yielding meaningful ciphertext. We use: enc(m1) ∗ enc(m2) = enc(m1 + m2)

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Protocol flow (1)

Local Station M1 Record consumption m1 M2 M3 M4

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Protocol flow (2)

Local Station M1 Choose random aj,1 s.t. m1 = a1,1 + a2,1 + a3,1 + a4,1 M2 M3 M4

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Protocol flow (3)

Local Station M1 For all j encpkj(a1j) M2 M3 M4

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Protocol flow (4)

Local Station M1 M2 M3 M4 encpkj(a1j)

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Protocol flow (5)

Local Station For all i, j: encpkj(aij) M1 M2 M3 M4

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Protocol flow (6)

Local Station For all j:

encpkj(aij) = encpkj(

i=j

aij) M1 M2 M3 M4

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Protocol flow (7)

Local Station M1 M2 M3 M4 encpk3(

i=3

ai3)

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Protocol flow (8)

Local Station M1 M2 M3 decsk3encpk3(

i=3

ai3) M4

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Protocol flow (9)

Local Station M1 M2 M3 M4 r3 :=

i=3

ai3 + a33

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Protocol flow (10)

Local Station

j rj

M1 M2 M3 M4

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Outline

1

Smart Meters

2

Real-time data aggregation

3

Billing protocols

4

Conclusions

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Privacy-sensitive Billing protocols

Security in the protocol is a must Ideally: Allows for different tariffs No centralized trust – neither the consumer can cheat, nor the utility Utility has no direct access on smart meter No physical inspections required → Complex problem but protocols exist.

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Outline

1

Smart Meters

2

Real-time data aggregation

3

Billing protocols

4

Conclusions

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Summary & Conclusions

Lessons learned:

1 Privacy is a big problem with current smart meters. 2 Protocols for real-time data and secure billing. 3 Privacy in Smart Meters is possible.

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