This document summarizes a student's master's thesis on using blockchain technology to improve cyber security for smart metering systems transactions. The thesis addresses motivation for securing smart metering systems, describing smart cities/grids and AMI architecture. It reviews related works applying blockchain for grid monitoring security and databases. The student proposes a private/public permissioned blockchain architecture called AMI-BC using a hybrid proof-of-efficiency consensus algorithm across cloud, fog and IoT tiers. It would secure smart meter readings and detect energy fraud/anomalies using machine learning models to predict consumption and power quality.

1. Cyber Security on Transactions in
Smart Metering Systems using
Blockchain
Student: M.C. Juan Carlos Olivares Rojas
Advisors: Dr. Enrique Reyes Archundia,
Dr. José Antonio Gutiérrez Gnecchi
October 2019

2. Motivation
Source: IEEE
The Data Revolution

3. Smart City / Smart Grid
Source: WebNMS

4. Smart Metering System
Source: PGE

5. AMI Architecture
Source: ELP (Electric Light Power)

6. Non-Technical Losses
PSG 2017-2031
Reduce loss level to 13.38%

7. Tampering SMI
Source: Maxim

8. Cyber Security Issues in
SMS
Source: self-made

9. Related works

10. Blockchain
Source:Tien Tuan Anh Dinh, et al. (2017). “DOI 10.1109/TKDE.2017.2781227

11. Literature Review
Work Features BC Type Algoritmo
Consenso
Processing Smart
Contr
act
Chain Type Others
Priwatt Comercialization Private
permisioned
Proof-of-
concept*
Cloud S Simple Multi-Signatures
Helios Comercialization Private
permisioned
PoS Cloud S Simple
BC IoT Security Smart
Home
Private/Public PoW Cloud N Double External Storage
Server
Grid
Monitoring
Security SG Private
permisioned
PoW* Cloud N Simple Different data
structures on BC
Phantom Criptocurrencies
BC General
Public/Privated Double: Proof-of-
reputation and
Proof-of-
computingWork
Cloud N Multi-tier BlockDAG
Fluree Databases BC Public* PoW* Cloud N Simple Databases on BC
Blok4Forensi
c
Forensic Audit Private
permisioned and
permisionless
PoS Cloud N Simple Data
Fragmentation on
BC
Arq. Dist. BC
Cloud
Distributed
Computing
Architecture
Public
permisioned and
permisionless
PoW* Cloud/Fog N Double SDN
Consortium Malware
Detection
Private/Public Hybrid:
PoW/PoS
Cloud Partial Double Legal Prose
Proposal:
AMI-BC
Security on SMS
Transactions
Private
permisioned
and
permisionless
Hybrid per each
tier
Proof-of-
Efficiency
Cloud/Fog/ IoT
(medidores y
dispositivos)
Partia
l
(Pros
a)
Multi-tier External BC
Interconection
Data Frag. on
BC

12. Cloud-Fog-Edge
Source: self-made

13. 1
2
Arquitecture Proposed
PoEf:
Proof-of-
Efficiency
Source: self-made

14. SM
readings
Forecast
model
DC
Predicting
and
adjusting
A,
SAs,
DER*
Trained
Forecast
model
Feeding
the model
Data for
other SMs:
Day, week,
Month, year
Lightweight
Time-Series Algorithm
Intermediate weight
Time-Series Algorithm
PoEf: Consumption Prediction
Source: self-made

15. SM
measurements
Classification
and
Prediction
Model
DC
Predicting and
Checking power quality events
In real-time
A,
SAs,
DER
Trained
Forecast
model
Events occured
of
Power quality
Data for
other SMs
K-means and decision tree
K-means Algorithm variation
PoEf: Power Quality Estimation
Source: self-made

16. SM
measurements Consumption/
Production
Patterns
DC
Predicting annomaly events
in real-time
A,
SAs,
DER
Trained
model
Annomaly
Events
Data for
other SMs
Rules validator
Bayessian classificator
Behavior
Rules
Alarms to the
Utility and SM
PoEf: Energy Fraud Detection
Source: self-made

17. Agent
Lower level
1
Agent
Upper level
2
34
PoEf: Energy Fraud Detection
Source: self-made
Reinforcement Learnig Approach

18. Smart Pi

19. State of the Research

20. Questions?
Thank you!
jcolivares@itmorelia.edu.mx
http://dsc.itmorelia.edu.mx/msc
http://sagitario.itmorelia.edu.mx/pelectron
http://sagitario.itmorelia.edu.mx/dci