slides - ICPE 2012

| 1

Assuring the Trustworthiness of the Smarter Electric Grid

Bill Sanders University of Illinois at Urbana-‐Champaign

www.tcipg.org [email protected]

ICPE 2012

Building Interdisciplinary Excellence with Societal Impact

Coordinated Science Laboratory

•  Excellence in: -  Computing and Networks -  Circuits, Electronics & Surface

Science -  Communications & Signal

Processing -  Decision & Control -  Remote Sensing

•  Affiliated Institutes: -  ITI: Information Trust Institute -  ADSC: Advanced Digital Sciences

Center (Singapore) -  PCI: Parallel Computing Institute

•  Major Centers: -  Illinois Center for Wireless Systems -  NSF National Center for Professional

and Research Ethics -  NSF Science of Information Science

and Technology Center -  DOE/DHS Trustworthy Cyber

Infrastructure for the Power Grid (TCIPG) Center

-  Boeing Trusted Software Center -  HHS SHARPS Health Care IT Security

Center -  NSA Science of Security Center -  Illinois Center for a Smarter Electric

Grid

•  Initiatives: -  Computer Vision -  SRC Focus Center Research Program -  Neuroengineering IGERT -  Human-Machine Adversarial Network MURI

•  Statistics: -  60 years as a premier national interdisciplinary

research facility -  550 Researchers: 110 professors, 330 graduate

students, 60 undergraduate students, & 50 professionals

-  Over $300M in active research projects as of Jan. 2011

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Outline

•  A Quick Primer on the Modern Electric Grid •  VulnerabiliKes and Threats •  Challenges to Achieving Trustworthy OperaKon •  TCIPG’s Research Mission and Results

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Outline


| 5

Power Grid Trust Dynamics Span Two Interdependent Infrastructures

Electrical (Physical) Infrastructure

Cyber Infrastructure

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The Challenge: Providing Trustworthy Smart Grid OperaKon in Possibly HosKle Environments

•  Trustworthy –  A system which does what is supposed to do, and nothing else –  Availability, Security, Safety, …

•  HosKle Environment –  Accidental Failures –  Design Flaws –  Malicious AUacks

•  Cyber Physical –  Must make the whole system trustworthy, including both physical & cyber components, and their interacKon.

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•  Need to create secure and reliable computing base

•  Multiparty interactions with partial & changing trust requirements •  Regulatory limits on information sharing

•  Support large # of devices •  Timeliness, security, and reliability required of data and control information

Next-Generation Power Grid Cyber Infrastructure Challenges

Control Area

Other Coordinators

Market Operator

Market Par4cipant

Load Following AGC

Day Ahead Market

Coordinator Cross Cutting Issues •  Large-scale, rapid propagation of effects •  Need for adaptive operation •  Need to have confidence in trustworthiness of resulting approach

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Infrastructure must provide control at mulKple levels

² Mul4-‐layer Control Loops ² Mul9-‐domain Control Loops

²  Demand Response ²  Wide-‐area Real-‐Kme control ²  Distributed Electric Storage ²  Distributed GeneraKon

²  Intra-‐domain Control Loops ²  Home controls for smart heaKng, cooling, appliances ²  Home controls for distributed generaKon ²  UKlity distribuKon AutomaKon

²  Resilient and Secure Control ²  Secure and real-‐9me communica9on substrate ²  Integrity, authenKcaKon, confidenKality ²  Trust and key management ²  End-‐to-‐end Quality of Service ²  Automated a@ack response systems ²  Risk and security assessment ²  Model-‐based, quanKtaKve validaKon tools

Distribution and Generation

Transmission and Distribution

Generation and Transmission

Resilient and Secure Control Loops

Note: the underlying Smart Grid Architecture has been developed by EPRI/NIST.

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The Power Grid of Tomorrow: Smart Control of Electrical Equipment and an Open Grid

Consumer Portal: •  Security issues are huge

–  Privacy, Billing integrity, Mischief, vandalism, intrusion, Consumer manipulaKon of system

•  Customer educaKon –  Understanding impact of

choices, Home user technical abiliKes, Home user security knowledge Who is responsible for security?

•  Consumer? UKlity? –  Who would accept responsibility?

•  Will be decided by regulators –  PoliKcal decision, but may be influenced by technology

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Power Grid of Tomorrow: North American SynchroPhasor IniKaKve

•  IniKaKve, funded by DOE and industry, to invesKgate pu_ng Phasor Measurement Units (PMUs) throughout physical power infrastructure

•  Need significant changes in power cyber infrastructure to support PMUs.

•  “Class A” service requires low latency, data integrity & availability (“no gaps”)

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Trustworthiness through Cyber-‐Physical Resiliency

•  Physical infrastructure has been engineered for resiliency (“n-‐1”), but

•  Cyber infrastructure must also be made resilient: –  Protect the best you can (using classical cyber security methods opKmized for grid characterisKcs), but

–  Detect and Respond when intrusions succeed •  Resiliency of overall infrastructure dependent on both cyber

and physical components •  Approaches must be developed that make use of sound

mathemaKcal techniques whose quality can be proven (need a science of cyber-‐physical resilience)

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Outline


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VulnerabiliKes in Current Power Systems

•  Systems are designed to be robust in the face of single failures but are at risk for certain kinds of multiple failures –  While secure against single points of

failure, analysis may reveal combinations of faults that would have severe consequences

•  The tools to find such combinations are not difficult to construct

•  In a couple hours, using a commercially available Power simulator, and publicly available power flow data, TCIP researchers found a small set of breakers who’s tripping would lead to a blackout almost the scale of the August 2003 blackout

Golf Mill

River

Westville

Idle

Junction

Plano

Mole

Island

109 MW

Niles

Evanston

71%

Devon

Skokie

Ford CitySawyer

Northridge

HigginsDes Plaines

77%

78%Franklin Park

Oak Park

Ridgeland

D799

Galewood

76%

74%

76%

74%

Y450

Congress

Rockwell

Clint

Dekov

Fisk

Crawford

Alt GE

Natoma

Alsip

Oakbrook

Downers Groove

Woodridge

W604

W603

Bolingbrook

Sugar Grove

N Aurora

Elgin

Hanover

Spaulding

Bartlett

S. Schaumberg

Tonne

Landm

Busse

Howard

Berkeley

Bellwood

La Grange

Church

Addison

Nordi

Glendale

Glen Ellyn

Butte

York CenterD775

Bedford Park

Clearning

Sayre

Bridgeview

Roberts

Palos

Romeo

Willow

Burr Ridge

South Elgin Cedarburg

West Chicago

Aurora

Warrenville

Montgomery

Oswego

Wolf Creek

Frontenac

W600 (Naperville)

W601

J307

Will Co.

Orlan

-0.40 deg

2.35 deg

-7.10 deg -7.36 deg

McCook

4.49 deg

Grafton

UIUC

70%

Golf Mill

River

Westville

Idle

Junction

Plano

Mole

Island

109 MW

Niles

Evanston

Devon

Skokie

Ford CitySawyer

Northridge

HigginsDes Plaines

71%

Franklin Park

Oak Park

Ridgeland

D799

Galewood

Y450

Congress

Rockwell

84%

80% 84%

80%

Clint

Dekov

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Natoma

Alsip

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Downers Groove

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W604

W603

Bolingbrook

Sugar Grove

N Aurora

Elgin

75%

Hanover

Spaulding

Bartlett

S. Schaumberg

Tonne

Landm

Busse

Howard

Berkeley

Bellwood

La Grange

Church

Addison

Nordi

Glendale

Glen Ellyn

Butte

York CenterD775

81%

72%

79%

Bedford Park

Clearning

Sayre

Bridgeview

Roberts

Palos

Romeo

Willow

Burr Ridge

72%

South Elgin Cedarburg

West Chicago

Aurora

Warrenville

Montgomery

Oswego

Wolf Creek

Frontenac

W600 (Naperville)

74%

W601

J307

Will Co.

Orlan

-0.40 deg

2.35 deg

-7.10 deg -7.36 deg

McCook

4.49 deg

Grafton

UIUC

88%

110%

119%

113%106%

113%

106%

93%100% 111%

88%

99% 93%

93%

86%

89%

98%

168%177%

170%179%

179%175%

225%220%

82%

71%

74%

Golf Mill

River

Westville

Idle

Junction

Plano

Mole

Island

109 MW

Niles

72%

Devon

Skokie

79%

76%

82%

Ford CitySawyer

Northridge

76%

HigginsDes Plaines

71%Franklin Park

Oak Park

Ridgeland

D799

Galewood

Y450

Congress

Rockwell

75%

77%

Clint

Dekov

Fisk

Crawford

Alt GE

Natoma

Alsip

Oakbrook

Downers Groove

Woodridge

W604

W603

Bolingbrook

Sugar Grove

N Aurora

78%

Elgin

78% 72%

Hanover

Spaulding

Bartlett

S. Schaumberg

Tonne

Landm

Busse

Howard

Berkeley

Bellwood

La Grange

Church

Addison

Nordi

Glendale

Glen Ellyn

Butte

York CenterD775

Bedford Park

Clearning

Sayre

Bridgeview

Roberts

Palos

Romeo

Willow

Burr Ridge

South Elgin

71%

71%

Cedarburg

West Chicago

Aurora

Warrenville

Montgomery

Oswego

Wolf Creek

Frontenac

W600 (Naperville)

74%

W601

J307

Will Co.

Orlan

-0.40 deg

2.35 deg

-7.10 deg -7.36 deg

McCook

4.49 deg

Grafton

UIUC

108%

133%

114%

91% 89%

101%

92%

131%139%

118%126%

119%128%

90%

85%

94%

109%

122%

89%

146%

144%

154%146%

153%

145%

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Classical (Physical) AUack Approaches

•  Physical attacks on lines, buses and other equipment can also be effective: –  “low tech” attacks may be easy, and are also difficult to

defend against –  Requires physical proximity of attacker –  Particularly effective if multiple facilities are attacked in

a coordinated manner •  But coordination may be much easier in a cyber attack

J.D. Konopka (a.k.a. Dr. Chaos) Alleged to have caused $800K in damage in disrupting power in 13 Wisconsin counties, directing teenaged accomplices to throw barbed wire into power stations. (From Milwaukee Journal Sentinel) http://www.jsonline.com/news/Metro/may02/41693.asp

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Intelligent Electronic Devices

•  Intelligent Electronic Devices (IEDs) monitor and control devices, relays, and breakers

•  IEDs may be subject to cyber tampering given access to the substaKon network and knowledge of a password. –  Publicly accessible informaKon contains the default passwords for some IEDs

•  AUacks on mulKple grid locaKons, whether physical or cyber, would need to be well synchronized to be effecKve (<10 minutes)

PASSWORD Shows or sets passwords. Command pulses ALARM contacts closed momentarily aier password entry. PAS 1 OTTER sets Level 1 password to OTTER. PAS 2 TAIL sets Level 2 password to TAIL.

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PotenKal Cyber AUack Strategies

•  Tripping Breakers •  Changing Values Breaker Settings

–  Lower settings can destabilize a system by inducing a large number of false trips

–  Lowering trip settings can cause extraneous other breakers, causing overloading of other transmission lines and/or loss of system stability

•  Fuzzing of Power System Components •  Life Cycle Attacks •  Insider Threats

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Combined Cyber-‐Physical AUack

•  The physical element could be aimed at destabilizing the system and inflicting some lasting damage

•  The cyber element could: –  Focus on blinding the operator to the true nature of the problem, inhibiting defensive responses, and spreading the extent of an outage

–  Be the cause of the physical damage •  INL Generator Demonstration •  Stuxnet computer worm

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PotenKal for Long-‐Term (Physical) Damage

•  Unclear how likely it could be achieved in pracKce, but researchers at Idaho NaKonal Labs have shown physical damage by cyber means

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Outline

•  A Quick Primer on the Modern Electric Grid •  VulnerabiliKes and Threats •  Challenges to Achieving Trustworthy OperaKon •  TCIPG’s Research Mission and Research Results

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•  Published in January 2006/updated 2011 •  Energy Sector’s synthesis of criKcal control system security challenges, R&D needs, and implementaKon milestones

•  Provides strategic framework to

–  align acKviKes to sector needs –  coordinate public and private programs

–  sKmulate investments in control systems security

Roadmap – A Framework for Public-‐Private CollaboraKon

Roadmap Vision By 2020, resilient energy delivery systems are designed, installed,

operated, and maintained to survive a cyber incident while sustaining criKcal funcKons.

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American Recovery and Reinvestment Act of 2009

•  DOE-‐OE ($4.5B) –  Smart Grid Investment Grants ($3400M) –  Smart Grid DemonstraKons ($615M) –  State Electricity Regulators Assistance ($46M) –  Enhancing State Government Energy Assurance CapabiliKes and Planning for Smart Grid Resiliency ($39.5M)

–  Local Energy Assurance Planning IniKaKve ($10.5M) –  Resource Assessment and InterconnecKon-‐Level Transmission Analysis and Planning ($60 M)

–  Workforce Training for the Electric Power Sector ($100M)

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Summary of Smart Grid Investment Grant Awards

Topic Area Number of ApplicaKons

Selected/ Conforming

Federal Funding ($)

Applicant Funding ($)

Applicant Cost Share (%)

Equipment Manufacturing

2/14 25,786,501 25,807,502 50.02

Customer Systems 5/27 32,402,210 34,933,413 51.88

Advanced Metering

Infrastructure

31/138 818,245,749 1,194,272,137 59.34

Electric DistribuKon

13/39 254,260,753 254,738,977 50.05

Electric Transmission

10/28 147,990,985 150,454,793 50.41

Integrated and Crosscu_ng

39/143 2,150,505,323 3,082,366,420 59.09

Total 100/389 3,429,191,521 4,742,573,246 58.04

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Challenge 1: Trustworthy technologies for wide-‐area monitoring and control

•  Smart Grid vision for the wide area (primarily transmission) is:

–  Vastly more sensing at high, synchronous rates (example: PMUs)

–  New applicaKons that use these data to improve

•  Reliability •  Efficiency •  Ability to integrate renewables

•  Achieving the vision requires secure and reliable communicaKons between sensors, control devices, and monitoring and control applicaKons all owned and operated by the many enKKes that make up the grid

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Challenge 1 Problem Areas

•  Smart grid technologies bring new vulnerabiliKes along with benefits –  Need improvements in security of wide-‐area communicaKon technologies

–  Need ways to understand and miKgate the impacts of vulnerabiliKes

•  What data delivery infrastructure design will provide the integrity, confiden9ality, availability, and real-‐9me performance needed for wide-‐area smart grid operaKons?

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36299/36026 XF

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| 25

Challenge Area 1 Problem Areas, cont’d

•  What is the relaKonship between security (or lack of security) of communicaKons for wide-‐area monitoring and control and the power-‐system’s behavior?

•  What kinds of hardware and soiware components will provide a beUer foundaKon on which to build the wide-‐area monitoring and control infrastructure?

| 26

Specific Area 1 Research Challenges

•  Secure wide-‐area data and communicaKon networks for PMU-‐based power system applicaKons – Hierarchical gateway-‐based architecture

•  CooperaKve congesKon avoidance and end-‐to-‐end real-‐Kme scheduling to achieve real Kme informaKon delivery

•  Real-‐Kme, secure, and converged power grid cyber-‐physical networks

•  Algorithm-‐based intrusion-‐tolerant energy applicaKons

| 27

Challenge 2: Trustworthy technologies for local area management, monitoring, and control

•  Electric grid can be divided into three groups: the generaKon, the wires (T&D), and the demand. This challenge focuses on the demand and the nearby distribuKon –  GeneraKon must track load

•  For a grid with more renewable, but less controllable generaKon (e.g., wind and solar PV), more load control will be needed –  Distributed generaKon may be embedded in “demand” –  New loads (electric vehicles) could drasKcally change demand profile

| 28

MoKvaKon: PV Output VariaKon with Clouds

Image Source: Secretary Chu, “InvesKng in our Energy Future” GridWeek PresentaKon, Sept. 21, 2009

| 29


•  This challenge focuses on making the demand more known and/or controllable

•  Must address many of the Smart Grid core issues –  Great advances over years in generaKon and T&D, but end user has been mostly lei out

–  Customers require targeted informaKon to help them opKmize their electricity usage

– Making a smarter distribuKon system and more “acKve” load could greatly enhance system operaKons and control, but adds cyber issues

| 30

Specific Area 2 Research Challenges

•  Cyber-‐Enabled management of distribuKon (physical) infrastructure –  Smart-‐grid-‐enabled distributed voltage support – Agent technologies for acKve control applicaKons in the grid

•  Trustworthy integraKon of new distribuKon side technologies, e.g., vehicle-‐to-‐grid (V2G)

•  Non-‐intrusive, privacy-‐preserving, pracKcal demand-‐response management

| 31

Challenge 3: Responding to and managing cyber events

•  Combined cyber and physical aUack detecKon, response to detected aUacks, and recovery from aUack consequences is essenKal to providing resilience

•  ExisKng detecKon and response methods are ad hoc, at best, and rely on assumpKons that may not hold

•  Aim to detect and respond to cyber and physical events, providing resilience to parKally successful aUacks that may occur: – Making use of cyber and physical state informaKon to detect aUacks

–  Determine appropriate response acKons in order to maintain conKnuous operaKon

– Minimize recovery Kme when disrupKons do occur

| 32

Challenge 3 Scope

•  Sensors – Monitor both physical and cyber state – Make use of applicaKon characterisKcs improve sensing

•  Actuators –  Not just in generaKon, transmission, and distribuKon, but in every outlet, car, parking garage, DER

•  Response algorithms and engines that are: –  Have provable bounds on the quality of decisions that they recommend

–  Cannot cause harm in the hands of an adversary –  Are scalable (and almost surely) hierarchical –  Are wide in their end-‐to-‐end scope

| 33


Create complete detecKon, response, and recovery environment, at all necessary levels of abstracKon: •  Physical level

–  Taking into account noise and malicious manipulaKon of values

•  Hardware level –  RespecKng embedded and cost sensiKve

nature of power system components •  OS / Plaworm level

–  Dealing with lack of source code other observability limitaKons

•  Computer network level –  AccommodaKng observability

limitaKons due to encrypKon and protocols

| 34

Challenge 4: Trust and Risk Assessment

•  Define appropriate security metrics –  Integrated at mulKple levels –  Applied throughout system lifecycle –  Be both “process” and “product” oriented

•  Determine methods for esKmaKng metrics –  To choose appropriate architectural configuraKon –  To test implementaKon flaws, e.g., fuzzing, firewall rule analysis

–  Can be applied in cost effecKve manner before an audit •  Which link technical and business concerns

| 35

Example Challenge 4 Research Topics

•  Provide methods and tools that use simulaKon, modeling and experimentaKon to –  Characterize system resiliency in presence of malicious aUacks and accidental errors

–  Measure and quanKfy the system security/reliability –  Evaluate effecKveness and performance of novel mechanisms for conKnuous monitoring and defense against potenKal intruders and failures

–  Analyze and assess interplay between economics, renewable energy sources and demand response

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Outline

•  A Quick Primer of the Modern Electric Grid •  VulnerabiliKes and Threats •  Challenges to Achieving Trustworthy OperaKon •  TCIPG’s Research Mission and Results

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TCIPG Vision & Research Focus

Vision: Drive the design of an adaptive, resilient, and trustworthy cyber infrastructure for transmission & distribution of electric power, which operates through attacks

Research focus: Resilient and Secure Smart Grid Systems –  Protecting the cyber infrastructure – Making use of cyber and physical state information to detect, respond, and recover from attacks

–  Supporting greatly increased throughput and timeliness requirements for next generation energy applications

– Quantifying security and resilience

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TCIPG StaKsKcs

•  Builds upon $7.5M NSF TCIP CyberTrust Center 2005-‐2010 •  $18.8M over 5 years, starKng Oct 1, 2009 (including 20% cost

share from partner schools) •  Funded by Department of Energy, Office of Electricity and

Department of Homeland Security •  5 UniversiKes

–  University of Illinois at Urbana-‐Champaign –  Washington State University –  University of California at Davis –  Dartmouth College –  Cornell University

•  20 Faculty, 20 Senior Technical Staff, 37 Graduate Students, 5 Undergraduate Students, and 1 Admin

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Industry InteracKon: Vendors and UKliKes that have parKcipated in TCIPG Events

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Industry InteracKon: Other organizaKons that have parKcipated in TCIPG Events

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TCIPG Impacts all aspects of the 2011 Roadmap to Achieve Energy Delivery Systems Cybersecurity

Build a Culture of Security

Conduct summer schools for industry

Develop K-‐12 power/cyber curriculum

Develop public energy literacy

Directly interact with industry

Educate next-‐genera4on cyber-‐power aware workforce

Assess and Monitor Risk

Analyze security of protocols (e.g. DNP3, Zigbee, ICCP, C12.22)

Create tools for assessing security of devices, systems, &

use cases

Create integrated scalable cyber/

physical modeling infrastructure

Distribute NetAPT for use by u4li4es

and auditors

Create fuzzing tools for SCADA

protocols

Protec4ve Measures/Risk Reduc4on

Build secure, real-‐4me, & flexible communica4on mechanisms for

WAMS

Design secure informa4on layer

for V2G

Provide malicious power system data

detec4on and protec4on

Par4cipate in industry-‐led CEDS

projects

Manage Incidents

Build game-‐theore4c Response

and recovery engine

Develop forensic data analysis to support response

Create effec4ve Intrusion detec4on approach for AMI

Sustain Security Improvements

Offer Testbed and Exper4se as a

Service to Industry

An4cipate/address issues of scale: PKI, data avalanche,

PMU data compression

Act as repository for cyber-‐security-‐related power system data

TCIPG Eff

orts

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Selected TCIPG AcKviKes: PracKcal Vulnerability Assessment Tools for Industry

•  NetAPT –  In evaluaKon by SERC as an

audit tool –  Used in pilot assessments by

uKliKes •  LZ-‐Fuzz has been used in a

power environment to test ICCP connecKons

•  Api-‐DO ZigBee Self-‐assessment framework –  More than 50% of KillerBee

code base is now contributed by TCIPG Dartmouth team

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Selected TCIPG AcKviKes: Embedded System and AMI Security

•  Autoscopy Jr.: Lightweight kernel-‐based intrusion detecKon system –  Ongoing Discussions with

SE •  SpecificaKon-‐based IDS for

AMI –  Discussions with Itron,

Fujitsu, EPRI •  Hardware-‐based IDS for

meters –  Signal-‐level IDS detects

meter tampering •  Security specificaKon

development and review for industry

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Selected TCIPG AcKviKes: Efforts to Secure Wide-‐Area Measurement Infrastructures

•  GridStat Secure Middleware CommunicaKon Framework –  Used in test with INL

•  CONES: Converged Networks for SCADA –  Algorithms formed basis of

DOE-‐funded SIEGate (System InformaKon Gateway) appliance

•  Analysis of GPS spoofing aUacks against PMU synchronizaKon –  Demonstrated, using MatLab

simulaKon, spoofing aUack on GPS

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To Learn More

•  www.tcipg.org •  Bill Sanders

[email protected]

•  Request to be on our mailing list

•  AUend Monthly Public Webinars

•  AUend our Industry/Govt. workshop Oct. 30-‐31, 2012

Documents

slides - ICPE 2012