1. Smart Meter Data Privacy: A Survey
Authors: Muhammad Rizwan Asghar, György Dán, Daniele Miorandi, Imrich
Chlamtac
Source: IEEE Communications Surveys & Tutorials, Vol. 19, pp , 27 Jun 2017
Speaker: KaiFan Chien
Date: 3/16/2019

2. Outline Introduction Smart Meter Data and Privacy
Requirements of Privacy and Security
Privacy Protection for Smart Meter Data under the Trusted Operator Model
Service-Specific Privacy Protection Under the Non-Trusted Operator Model
Conclusions

3. Introduction(1/2) Smart grid Smart meters Demand response Real-time
Optimise the supply of electricity
Primary sources of data

4. Introduction(2/2)
Data collected by smart meters may also serve for invading consumers’ privacy.
In this survey
Regulatory and policy context
Overview of state-of-the-art solutions
Provide recommendations
Billing
Operations
Alue-added services

5. Smart Meter Data and Privacy(1/4)
Automated meters and smart meters
Consumption of electric energy with a variable time granularity
Meter Data Management System (MDMS)
Receive pricing information and load control commands
Exchange information with smart home appliances
Intervals of 15 minutes

6. Smart Meter Data and Privacy(2/4)
Different domains of the smart
metering infrastructure
Customer
Communication
MDMS
Data

7. Smart Meter Data and Privacy(3/4)
Billing, Operations, and Value-Added Services
Billing  Not be real-time
Operations  Real-time
The second use of smart meter data
State Estimation (SE) / Volt and Var Control (VVC) / Fault Location, Isolation and Service Restoration (FLISR)
Value-Added Services  Real-time or Batch

8. Smart Meter Data and Privacy(4/4)
Automated and smart meters collect personal data.
Greveler et al. fine enough measurements could reveal consumers’ interests as well

9. Requirements of Privacy and Security(1/4)
Privacy legislation for smart meter data EU
Data are necessary
Cannot be used for a different purpose
NIST

10. Requirements of Privacy and Security(2/4)
Two notions of privacy
Cryptographic privacy
Statistical privacy
Differential privacy
k -anonymity

11. Requirements of Privacy and Security(3/4)
Requirements for privacy-preserving protocols for smart meter data management
Confidentiality
Integrity
Authenticity
Non-Repudiation
Auditability

12. Requirements of Privacy and Security(4/4)
Preserving privacy depends significantly on the attacker model
Honest-but-curious, also called semi-honest
Malicious attacker

13. Privacy Protection for Smart Meter Data under the Trusted Operator Model(1/4)
Summary of the problems, existing solutions and remaining research issues under the trusted operator model

14. Privacy Protection for Smart Meter Data under the Trusted Operator Model(2/4)
Tamper-resistance of smart meters
Trusted Platform Module (TPM)
Electricity theft
McLaughlin, Podkuiko and McDaniel describe methods, including password extraction and storage tampering
Automated meters for electricity and for gas were recently found tampered within the U.K

15. Privacy Protection for Smart Meter Data under the Trusted Operator Model(3/4)
Data confidentiality and trust models
Public Key Infrastructure (PKI)
Baumeister investigated what PKI architecture would be most suitable to meet the requirements
Main issue with the PKI is efficient certificate revocation
By adding random noise to the data
???

16. Privacy Protection for Smart Meter Data under the Trusted Operator Model(4/4)
Consent and Access Control
Mandatory Access Control (MAC).
Discretionary Access Control (DAC).
Role-Based Access Control (RBAC).
eXtensible Access Control Markup Language (XACML)
Data Integrity and Auditing

17. Service-Specific Privacy Protection Under the Non-Trusted Operator Model(1/5)
Summary of the issues, privacy-preserving solutions and research directions discussed

18. Service-Specific Privacy Protection Under the Non-Trusted Operator Model(2/5)
Provides a detailed comparative analysis of privacy-preserving solutions for smart meter data
Are (c)onfidentiality
(i)ntegrity
(AUTH)etication
No(NM)alleability
No(NR)epudiation
(AUD)itability
(ANO)onymity
(SY)bil Attack
Billing (BL)
Operations (OP)
Value-Added Services (VAS)

19. Service-Specific Privacy Protection Under the Non-Trusted Operator Model(3/5)
Privacy-Preserving Billing
Filtering With Energy Storage for Statistical Privacy
The energy storage protects customers’ privacy by hiding the use of individual appliances
Secure Computation for Cryptographic Privacy
Jawurek et al. propose a scheme based on Pedersen commitments
Non-Interactive Zero-Knowledge proof (NIZK)
Anonymous credential system

20. Service-Specific Privacy Protection Under the Non-Trusted Operator Model(4/5)
Privacy-preserving operations
With a trusted third party
Aggregation algorithms for cryptographic privacy
Without a trusted third party
Homomorphic encryption
Providing Statistical Privacy
Privacy Economics

21. Service-Specific Privacy Protection Under the Non-Trusted Operator Model(5/5)
Value-Added Services
Demand-response
Identifying appliance level anomalies
Optimise the electricity consumption of a household

22. Conclusions Privacy-preserving meter data delivery and management
Meter data collection for the three application areas
Billing
Operations
Alue-added services
Trusted Operator Model and non-Trusted Operator Model