TRUST Research on Physical
Infrastructure Control, Monitoring,
and Security
Prof. Stephen Wicker
Cornell University
Physical Infrastructure

Power Grid, Telecom Infrastructure, Water Transport
System, Interstate Highways
◦ Immense Investment
 Financial: Sunk costs and ongoing development and maintenance
 Human: Established development, maintenance, and regulatory
organizations at state and federal level
◦ Critical to National Economy
 National modes of production depend on functionality of critical
infrastructures with embedded sensing and control
 Multiple positive externalities have created secondary and tertiary
dependencies (e.g. air traffic control dependence on power and
telecom infrastructure)

Increasing complexity and 21st century security
requirements demand new approaches to control,
security, and long-term maintenance.
TRUST Infrastructure Research

Science and Technology
◦
◦
◦
◦

Low-power processors
Self-configuration algorithms
Taxonomy of network attacks
Information theory of privacy
Testbeds
◦ Sensor networking and privacy
◦ SCADA/plant security

Policy
◦ Smart meters and privacy intrusion
◦ Privacy-aware design
Nugget:
TRUST Sensor Platform Technologies



CU Asynchronous Processor
– Event-driven execution is
ideal for sensor platforms
– Low power consumption
useful for large-scale and/or
long-term deploment
Clockless logic
– Spurious signal transitions
(wasted power) eliminated
– Hardware only active if it is
used for the computation
MIPS: high-performance
– 24pJ/ins and 28 MIPS @
0.6V
Processor
Bus
Year
E/op
Ops/sec
Atmel
8
200?
1-4 nJ
4 MIPS
StrongARM
32
200?
1.9 nJ
130 MIPS
MiniMIPS
32
1998
2.3 nJ*
22 MIPS
Amulet3i
32
2000
1.6 nJ*
80 MIPS
80C51 (P)
8
1998
1 nJ**
4 MIPS
Lutonium
8
2003
43 pJ
4 MIPS
SNAP
16
2003
24 pJ
28 MIPS
Nugget: Smart Metering Provides
Data Equivalent to a Search
Electrical Data (Seconds Plot)
Estimated Presence/SleepWake Intervals
2500
1600
Reference SleepWake:
1400
0
1
0
1
0
1
1
0
1
0
1
0
0
1
0
Estimated SleepWake:
2000
1200
1
0
0
1
Reference Presence:
1000
1500
1
0
1
1
Estimated Presence:
800
1
0
1
1
1000
600
400
500
200
0
0
Day 1
0.5
Day 2
1
1.5
Day 3
2
2.5
Day 4
3
5
0
0
Day 1
0.5
Day 2
1
1.5
Day 3
2
2.5
Day 4
x 10
• Algorithm Performs well in determining presence and sleep cycles.
Over 90% of total interval length was correctly classified.
Power consumption data falls within the ambit of EU Directive 2002/58/EC
concerning the processing of personal data.
3
5
x 10