Download A Smart Metering Scenario

A Smart Metering Scenario
Jorge Cuellar, Jan Stijohann, Santiago Suppan
Siemens AG
14. 05. 2013
Agenda
General Context: Smart Grid Security
 Common Terminology
Description of the Scenario Environment
 Case Overview
Tomorrow: Possible worst case scenarios
 Threat and Attack Analysis
2
General Context: Smart Grid Security I
Motivation
 70% of urban population will live in cities by 2050
 Current energy supply affected by:
• Blackouts
• Power overloads
• High costs
 Upcoming challenges:
• Distributed power supply
…Regenerative sources in many places
• Scarcity of resources
…Intermittent power supply
3
Properties of the Smart Grid
Self-monitoring
Auto-balancing
Self-Regulating
Efficient
Cost reducing
Those properties are necessary to cope with
the requirements of future power supply
 Energy is flowing in both directions
 Amount of energy must be carefully
controlled
 Incentives must be provided
• to consume / store energy
• only when production is high
• in real-time
4
Entities (Roles)
Energy Generators
Energy Suppliers
 Data Communication Network
 Network Gateway
 Energy Supply Server
Prosumer & Home Domain
 Smart Appliances
 Smart Meter
 (Wireless) Home Area Network
 Home Gateway
 Home Energy Management System
Meter Point Operator
5
Data Flow
REMS:
Remote device
for Control &
Usage Display
Energy
Generation („SA“)
ESS: Energy
Supplier Server
S&C
S&C
EMS:
Control &
Usage Display
BDF
Data
Energy
20°C
SA: Smart
Appliances SA: Thermostat
S&C
Vehicle
Charging
(„SA“)
ABD
Third
Parties:
PDD
Energy
Generator
etc
DCN
NG: NW
Gateway
Internet
HG: Home
Gateway
SA: TV
SA
BD
HAN: Home
Area
Network
ABD
Solar
SM: Smart Meter
TN: Transmission
Node
Raw BD
6
Data Flow
Raw BD (Raw Billing Data)
REMS
 All data related to energy
consumption, storage and
production
ESS
 Gathered by the SM
3P PDD
BD (Billing Data)
 Processed and stored by the
SM and the (local) EMS.
S&C
BDF
S&C
EMS
S&C
ABD
HG
TV
BD
DCN
NG
HAN
ABD
Solar
TN
Raw BD
SM
ABD (Aggregated Billing Data)
 Sent to the NG over the
public Data Communication
Network and forwarded to the
Energy Supplier
PDD (data for power generation
and distribution purposes)
 Aggregated by ES from ABD
of several households
 Purpose: usage forecasts for
certain sectors
7
Data Flow
BDF (Billing Data Feedback
Information)
 Every ± 5 minutes
 Users are informed
 Energy usage, generation
volume, costs, revenues, and
current rates
REMS
S&C
ESS
BDF
RS&C
S&C
ABD
HG
3P PDD
 View the smart appliances’
status
 Control of the Smart
Appliances or modification of
the energy management
policies
TV
BD
DCN
NG
HAN
ABD
S&C (Status and Control)
 Local logon to the EMS
EMS
Solar
TN
Raw BD
SM
RS&C (Remote S&C)
 Remotely logon to the EMS
 Using e.g., a cellular phone
or a remote PC
 From external hot spots (e.g.,
internet café)
8
Suggestions for Worst
Cases
Threat and Attack Analysis
Jorge Cuellar, Jan Stijohann, Santiago Suppan
Siemens AG
14. 05. 2013
Questions / Tasks
Assume a variety of home environments
 Some clever, some less clever devices
 Legacy and not legacy systems
 From a variety of vendors
Describe attackers & attacks in some detail:
 External attackers
 Insiders which are either malicious or careless
• Employees, family members, neighbours, installers, manufacturers
Identify security requirements
Identify security controls and measures to provide
 First line of defence
 Defence in depth or redundancies
10
1: Family with children
 Which information could
the attacker obtain?
• What can he deduce?
Possible weak point
…How many persons
live?
 Possible tracing?
• Combination of
information useful for
burglary or … ?
Attacker: insider / outsider
11
2: Smart Appliances
Which appliances are
“smart”?
What kind of information
(R/S&C) do they process?
What are the appliances’
functionalities?
Can a successful attack to
an appliance lead to a
compromise of the AMI?
Attacker: insider / outsider
12
3: Privacy
Initial assumption: all
communication is encrypted
 Possible to read / disclose /
etc. information regardless
of encryption?
 Time / Communication
Parties / Message length
etc., help disclose the
payload data?
 Possible to misuse insider
status (Prosumer / Energy
Supplier)?
Attacker: insider / outsider
13
4: Impersonation
 How to impersonate another
customer for accounting fraud?
 Possible to impersonate a
server?
 With which results?
X
Possible
impersonation
or
interference
Attacker: insider / outsider
14
5: Encryption & Key mgmt
Assume: Communication is
encrypted
 Possible to bypass the
communication
encryption?
Possible weak point
 Possible to extract keys or
to intercept key exchanges
or key updates?
 Possible to exploit
implementation
weaknesses at the
network / transport /
application layer?
 Possible to exploit insider
status?
Attacker: insider / outsider
15
6: Electric Mobility
Assumption: Electric
vehicles share an unique
vehicle ID
 Possible impersonation?
 Possible fraud?
uvID
uvID
 Possible tracing?
 Possible theft?
 …
Attacker: insider / outsider
16
Thank You!
Any questions?
eRise Challenge 2013
14. 05. 2013
REMS
S&C
ESS
S&C
BDF
EMS
S&C
ABD
3P
HG
PDD
TV
BD
DCN
HAN
NG
ABD
Solar
TN
Raw BD
SM
18