Software Quality and Infrastructure Protection for

Diffuse Computing

FY2001 ONR CIP/SW URI

Principal Investigator: Andre ScedrovInstitution: University of Pennsylvania

URL: http://www.cis.upenn.edu/spyce

OPTION STARTED IN MAY 2004

The SPYCE Team

Joan Feigenbaum (Yale)Joseph Y. Halpern (Cornell)Patrick D. Lincoln John C. Mitchell (Stanford)Andre Scedrov (U Penn)Jonathan M. Smith (U Penn) (until December 2003)

External Collaborators

Cynthia Dwork (Microsoft)Tim Griffin (Intel)Vitaly Shmatikov (SRI)Paul Syverson (NRL)

URI ObjectiveAlgorithms to model, manage and maintain Algorithms to model, manage and maintain a computational a computational infrastuctureinfrastucture, distributed , distributed among many heterogeneous nodes that do among many heterogeneous nodes that do not trust each other completely and maynot trust each other completely and mayhave incentives (needs, priorities).have incentives (needs, priorities).

DoD Capabilities

Reduced cost, improved performance, and higher reliability for networked operations across untrusted networks

Scientific/Technical ApproachesComputing and networking elements

diffusing into the environment need:• Local incentive-compatibility

in global distributed computing• Scalable authorization mechanisms• Assured communication• Experimental evidence

URI, May 2001 August 17, 2004

Software Quality and Infrastructure Protection for Diffuse ComputingU Penn, Stanford, Cornell, Yale

Smart devices diffuse into the environment….

… with control and assurance

Desktop ‘80s

Room ‘40s

Wearable ‘90s

Pervasive ‘00s

Email: scedrov@cis.upenn.edu WWW: http://www.cis.upenn.edu/spyce/

Secure services through heterogeneous overlay networks

Communication CooperationIncentivesDelivery

MissionAnalysis5.3.1

JFHQ

DevelopCOAE

5.3.4

JFHQ

PlanningGuidance

5.3.2

CDR

EndState 5.3.3

CDR

AnalyzeCOAE

5.3.5

JFHQ

RedTeamInputs

0.0Red

Team

SelectCOAE

5.3.7

CDR

PrepareETO

5.3.9

JFHQ

JFHQFunctional

Inputs 5.3.4

JFHQ

Collaborative Planning Environment

externalFunctional

Inputs0.0

COE

ReviseONA JFHQ

TaskMission CINC

PrepareONA JFHQ

PrepareCONPLAN

w/FDOs5.3.9JFHQ

DetermineDesired

End State CINC

SharpenONA JIC

DevelopLogisticsSupport JFHQ

Command

5.4JFHQ

ProjectFuture

OperationsJFHQ

CompareMoE

0.0JFHQ

CompareMoP 0.0

JFHQ

5.3.6

JFHQ

5.3.8

CDR

JPOTF

DIA

NAVFOR Element

MARFOR Element

JF HQ

JPG

AFFOR Element

ARFOR Element

JFACC

JFLCC

DOCC

JFMCC

JSOTF

POC

JCSNMCC

SPSTF

COC

Theater JIC/JAC

NMJIC

NCAUnified CINC

USAF

SupportCommands

Theater

USMCNavy

Army

JCCC

JLRC

JOCJISE

JPRC

JPRC

ACE

JISE (JFLCC)

JISE/J2 (JSOTF)

JISE/J2 Watch (JFACC)

MTACC/ACE

JFHQ OPFAC Interfaces in Wartime Scenario

TRANSCOM

SPACECOM

STRATCOM

SPOC

JIOC

JWAC

AFSPOCARSPOC

NAVSPOC

MI

CP Main

CP Fwd

CINC IMO

JCCCJCCC

NOC

NOCNOC

NOC

TCCCIO Cell

DISAGNOSC

RNOSC RNOSC

Other AgenciesNRO

NSA

NSA

JMCGAOC

JAOC

JISE/J2 (JFMCC)JMOC

CVIC/CDCTFCC

JCCC

JOC (JFLCC)

JCCC

TOC

JRTOC

JOC

JLRC

JPGJCCC

JISENIST

NRO

JOC (JSOTF)

JF HQ

JFLCC

JFMCC

JFACC

Unified CINC

AFFOR Element

MARFOR Element

NAVFOR Element

ARFOR Element

JSOTF

Theater JIC/JAC

National CINC JFHQ Staff JF Component Service Component

NCA

DIA

NRO

NSA

JCS

NIMA

SOCOM

TacticalAssets

TRANSCOM

SPACECOM

STRATCOM

JWAC

DLA

CIA

Academia

Coast Guard Element

JFHQ CINC Plug

C4ISR ArchitectureCommand, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance

Diffuse Computing

Paradigm developing rapidly as a result of - commercial computing markets - now-recognized potential of

peer-to-peer computing and grid computing- the need for distributed network-centric systems

Raises challenges for - system design- software production - the development of mechanisms ensuring stable

equilibria of diffuse systems

SPYCE Objective:Scalable Distributed Assurance

Develop fundamental understanding, models, algorithms, and network testbed, in order to reduce cost, improve performance, and provide higher reliability for networked operations across untrusted networks.

Incentives, Privacy, and Anonymity

Protocol Design and Analysis

Trust Management

Network Architecture

Smart devices diffuse into the environment….

… with control and assurance

Desktop ‘80s

Room ‘40s

Wearable ‘90s

Pervasive ‘00s

Software Quality and Infrastructure Protection for Diffuse ComputingU Penn, Stanford, Cornell, Yale

Scientific Accomplishments• Interdomain routing

Path vector protocols [Penn-Yale-Intel]Local conditions for stable routes [Yale]

• Analysis of cryptographic protocolsFormal methods for cryptography [Penn-Stanford]Kerberos 5 analysis [Penn-NRL]

• Logic for reasoning about policies [Cornell]• SPAM reduction algorithms [Microsoft-Stanford]• Privacy in databases [SRI-Microsoft]• Anonymity and information hiding [Cornell-NRL]• Content transcoding for heterogeneous clients [Penn]• Flexible Lightweight Active Measuring Environment [Penn]

Project Contact Information• PI: Prof. Andre Scedrov

co-PIs: Prof. Joan Feigenbaum, Prof. Joseph Halpern, Dr. Patrick Lincoln, Prof. John Mitchell

• Prof. Andre ScedrovDepartment of MathematicsUniversity of Pennsylvania209 South 33rd StreetPhiladelphia, PA, 19104-6395

Educational Accomplishments• Enhanced the ability to educate and train students in science

and engineering and perform CIP/SW relevant research

• 10 refereed journal publications

• 55 refereed conference proceedings

• 5 prototypes

• 7 PhD students graduated, 16 PhD students supported

• Members of NAS Computer Science and Telecommunications Board, Defense Science Board Task Force on Science and Technology, ACM Fellows, AAAI Fellows, …

August 17, 2004WWW: http://www.cis.upenn.edu/spyceEmail: scedrov@cis.upenn.eduURI, May 2001

Sample Plans for Option (1)

Secure, reliable network infrastructure- Combine security mechanism and incentives- Examples: BGP, DNS, NTP, …

General theory of computational mechanism- Mechanism specification and verification- Computational complexity analysis combining

network communication and incentivesDiscrete information management- Multicentric information delivery and retrieval- Access control, anonymity, and privacy

Sample Plans for Option (2)Further investigation of practical protocolsAutomating verificationAdding utilities to specifications Verifying mechanisms- mechanism = set of rules for playing a game,

designed to encourage “good” behaviore.g., tax system, type of auction

Sample Plans for Option (3)

• Combine the study of incentives, privacy, and anonymity

• Derive hardness results in diffuse computing • Hardness stems from interplay of computational

requirements and incentive-compatibility requirements (as in budget-balanced MCS).

• Use hardness as a building block in private algorithmic mechanisms or anonymous algorithmic mechanisms.

SPYCE Objective:Scalable Distributed Assurance

Develop fundamental understanding, models, algorithms, and network testbed, in order to reduce cost, improve performance, and provide higher reliability for networked operations across untrusted networks.

Incentives, Privacy, and Anonymity

Protocol Design and Analysis

Trust Management

Network Architecture

Smart devices diffuse into the environment….

… with control and assurance

Desktop ‘80s

Room ‘40s

Wearable ‘90s

Pervasive ‘00s