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Whos In Control of Your Control System? Device Fingerprin<ng for Cyber-Physical Systems David Formby 1 , Preethi Srinivasan 1 , Andrew Leonard 2 , Jonathan Rogers 2 , Raheem Beyah 1 Communica<ons Assurance and Performance (CAP) Group


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SLIDE 1

Who’s In Control of Your Control System? Device Fingerprin<ng for Cyber-Physical Systems

David Formby1, Preethi Srinivasan1, Andrew Leonard2, Jonathan Rogers2, Raheem Beyah1 Communica<ons Assurance and Performance (CAP) Group School of Electrical and Computer Engineering1 School of Mechanical Engineering2 Georgia Ins<tute of Technology

@GTCAPGROUP

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SLIDE 2
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Cyber-Physical Systems (CPS)

Cyber

Personal Computers Mobile Phones Embedded Devices

Physical

Motors, pumps, Generators, Valves, Relays…

CPS

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SLIDE 3
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Cyber-Physical Systems

  • Industrial control systems (ICS)

– Power grid, water/sewage, oil/gas, manufacturing, supervisory control and data acquisi<on (SCADA)

  • Home automa<on

– Ligh<ng, locks, thermostat, security system

Vulnerabilities can lead to physical harm ICS filled with vulnerable, legacy devices

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ICSA-15-041-02 ICSA-15-006-01 ICSA-15-169-01B https://ics-cert.us-cert.gov/advisories

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SLIDE 4
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Mo<va<on

  • ICS vulnerable to false

data injec<on and false command responses

– Can push system into unsafe state, cause physical harm – Previous fingerprin<ng work not suited for ICS – False data detec<on and IDS have limita<ons

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Illustration of simple false data injection

  • CPS fingerprin<ng helps defend against these a\acks
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SLIDE 5
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

A\acker Model

  • Two cases

– Compromised PLC

  • Stuxnet

– Physical access

  • Insider
  • Weak physical security
  • Goal

– Inject false data and command responses while masquerading as a different device

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SLIDE 6
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

CPS Fingerprin<ng

  • Data Acquisi<on

– Cross Layer Response Time (CLRT) – Es<mate device processing <me – Black Box Model fingerprints

  • Control

– Physical fingerprin<ng – Es<mate physical

  • pera<on <me

– Black Box Model fingerprints – New class of fingerprin<ng - White Box Modeling

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SLIDE 7
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Cross-Layer Response Time (CLRT)

  • Fingerprints devices

from data acquisi<on traffic

  • Es<mates device

processing <me

– Time between TCP ACK and SCADA response – Fast links (100Mbps) with slow devices, slow and regular traffic

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Adversary cannot simply respond faster to beat IED, must match the CLRT fingerprint

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SLIDE 8
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

CLRT Clusters

Same hardware, different software

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SLIDE 9
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Cross-Layer Response Time

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  • Network Architecture

– 100Mbps fiber links – Path distance ranged from 1 switch at 10 yards, to roughly 30 switches around 10 miles away

  • Devices s<ll had same signature no ma\er the distance
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SLIDE 10
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Cross-Layer Response Time

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Detection time – Time to gather samples before making a decision Precision

​𝑈𝑄/𝑈𝑄+𝐺𝑄

Recall

​𝑈𝑄/𝑈𝑄+𝐺𝑂

Accuracy

​𝑈𝑄+𝑈𝑂/𝑈𝑄+𝑈𝑂+𝐺𝑄+𝐺𝑂

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SLIDE 11
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Cross-Layer Response Time

Training Data – Original dataset Testing Data – Upgraded network Training Data – Original dataset Testing Data – Different substation

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  • Network architecture found to have minimal effect
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SLIDE 12
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Physical Fingerprin<ng

  • Fingerprint devices

from control traffic

  • Es<mate physical
  • pera<on <me

– Time between command packet and event <mestamp

  • Black Box and White

Box Methods

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Adversary must guess what event timestamp to respond with

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SLIDE 13
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Physical Fingerprin<ng Setup

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  • Relays – Typically used to open or close higher voltage circuits

with a lower voltage signal. Common device in ICS and analogous to large scale circuit breakers

Relays used in testbed, nearly identical specifications Testbed setup

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SLIDE 14
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Physical Fingerprin<ng Results

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No obvious differences between Open operations due to nearly identical ratings. Clear differences in Close

  • perations allow for device

fingerprinting.

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SLIDE 15
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Physical Fingerprin<ng Results

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SLIDE 16
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

White Box Modeling

  • Black Box Modeling

some<mes infeasible

– Operate infrequently, no physical access

  • Construct physical

model and es<mate parameters

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SLIDE 17
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

White Box Modeling

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Current in coil Magnetic field Permanent magnet force Equation of motion Coil Force Armature displacement Armature angular velocity

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SLIDE 18
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

White Box Modeling Results

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Reduced accuracy, but could be refined as true samples become available

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SLIDE 19
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Discussion

  • Assump<ons

– TCP Quick ACKs for CLRT and <mestamps for physical

  • Accuracy: 99% and 92%

– Not high enough for stand-alone IDS, but can complement tradi<onal IDS

  • White Box Modeling

– Reduced accuracy and requires some exper<se, combine with “gray box” modeling to overcome

  • Strength Under Mimicry A\ack

– Skilled adversary would evade detec<on, countermeasures could randomize requests, send extra

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SLIDE 20
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Conclusion

  • Novel passive fingerprin<ng techniques for ICS

– Data acquisi<on and control – 99% and 92% classifica<on accuracy – Inventory and complemen<ng tradi<onal IDS – Resistant to simple mimicry a\acks

  • New class of fingerprin<ng – White Box Models
  • Future work

– Internet of Things, developing white box methods

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SLIDE 21
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Backup – Across Substa<ons

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SLIDE 22
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Backup - Soqware

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SLIDE 23
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Backup – White Box

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SLIDE 24
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Backup – Mimicry A\acks

  • Weak Adversary

– Simulate compromised PLC – BeagleBone Black at 300MHz, 512MB RAM

  • Strong Adversary

– Simulate on-site a\acker – Desktop with 3.4 GHz quad-core i7, 16GB RAM

  • Goal

– Given the target distribu<ons, masquerade as target device while responding to read requests

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SLIDE 25
  • D. Formby, P. Srinivasan, A. Leonard, J. Rogers, and R. Beyah

Who’s In Control of Your Control System?

Backup – Mimicry A\acks

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