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Run-timeAccessibleDRAMPUFsinCommodityDevices

WenjieXiong1,AndréSchaller2,NikolaosA.Anagnostopoulos2,MuhammadUmairSaleem2,SebastianGabmeyer2,

StefanKatzenbeisser2,andJakubSzefer1

1.YaleUniversity,USA2.Technische UniversitätDarmstadtandCASED,Germany

Aug18,2016

PhysicallyUnclonable Functions(PUF)

• Afunction,whichisembeddedintoaphysicalobjectWhenqueriedwithachallengex,thePUFgenerates aresponsey,whichdependson1)Challengexand2)specialphysicalpropertiesoftheobject

• SiliconPUFsusethemanufacturingprocessvariationse.g.ArbiterPUFs,SRAM-PUFsItisalmostimpossibletoclone,evenforthemanufacturer

• Authenticationandidentification

2CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Intrinsic PUF• NoextrachipsneededforPUF• Exploit hardwarewhichison-boardanyway

e.g.startupvaluesofSRAM

IsitpossibletoexploitDRAMasaPUF?• MostcomputingdevicesholdDRAM• ExploitintrinsicDRAMPUFtoderiveaunique

fingerprint&deriveakey• DRAMhaslargercapacitythanSRAM• RuntimePUFratherthanboot-uptime

IntrinsicDRAMPUF

3CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Experimentalplatforms:PandaBoard(top)andIntelGalileo(bottom).

Outline/Contributions• Extractdecay-basedDRAMPUFinstancesfromunmodifiedcommodity

devices duringrun-timeofthe Linuxsystem• IntroducenewmetricsforevaluatingDRAMPUFs,basedontheJaccard

index• Throughextensiveexperiments,weshowthatDRAMPUFsexhibit

robustness,uniqueness,andstability• Designprotocolsfordeviceauthenticationandsecurechannel

establishmentthatdrawtheirsecurityfromthetime-dependentdecayofDRAMcells

4

SS 2013 | Seminar: Physically Unclonable Functions and its Applications | André Schaller & Prof. Dr. Stefan Katzenbeisser |

CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

DRAMCellDecay• ADRAMcellconsistsofa

capacitorandatransistor• Bitisstoredascharge• DRAMaccessprocess• Chargeleakage

– DRAMrefresh– Accessawordwillrefresh

thewholerow• Duetothemanufacturing

variationsamongDRAMcells,somecellsdecayfasterthanothers,whichcanbeexploitedasaPUF

SchematicofaDRAMarray;arrowsindicateleakagepathsfor

dissipationofchargesthatleadtoPUFbehavior.

5CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

DRAMPUFAccess

(1)DRAMforordinaryuse

(2)PUFregion(ingrey)isinitializedandtheDRAM

(3)PUFcellsdecayfortimet

(4)ReadouttheDRAMtoextractthePUFmeasurement

(5)DRAMreturntonormalusage

DRAMPUFchallenge:LogicalPUF(addr andsize),initialvalue (0or1),decaytime

OS & App memory

OS & App memory

sizeaddr

LogicalPUF

OS & App memory

OS & App memory

OS & App memory

OS & App memory

OS & App memory

OS & App memory

refreshisdisabled

6

refreshisdisabled

CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

• Twoapproaches– Firmware

• DRAMisnotusedbyfirmware,sothewholeDRAMrefreshcanbedisabled

– Kernelmodule• SelectiveDRAMrefresh

– ReadawordineachDRAMrow,andthus,refreshtheDRAMusedbythesystemandapplications

• Twoplatforms– PandaboardESRevisionB3:TIOMAP4460,1GBELPIDADDR2– IntelGalileoGen2:IntelQuarkX1000,two128MBMicronDDR3

Implementations

7CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Outline/Contributions• Extractdecay-basedDRAMPUFinstancesfromunmodifiedcommodity

devicesduringrun-timeoftheLinuxsystem• IntroducenewmetricsforevaluatingDRAMPUFs,basedontheJaccard

index• Throughextensiveexperiments,weshowthatDRAMPUFsexhibit

robustness,uniqueness,andstability• Designprotocolsfordeviceauthenticationandsecurechannel

establishmentthatdrawtheirsecurityfromthetime-dependentdecayofDRAMcells

8CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

DRAMPUFCharacteristics

Iftx ≤tx+1andaddrx =addrx+1,sizex =sizex+1,weobservemx⊆mx+1,uptonoise.

Wemeasuredtwo 32KBlogicalPUFson4 PandaBoardsand5 IntelGalileos.EachlogicalPUFwasmeasuredatfive decaytimeswith50measurementseach.

AveragedecayrateofDRAMmodulesof(blue)PandaBoardand(purple)IntelGalileo.

120 180 240 300 3600

0.005

0.01

0.015

0.02

0.025

Decay time (sec)

Decay

rate

t1 t2 t3t0

9CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

DRAMPUFCharacteristics• PUFmeasurement:Astringof0’sand1’s

->Asetofbitflips• Hammingdistance->Jaccardindex

• IntraJaccardIndex:– PUFmeasurementsofthesame PUFchallenge.– Ideally,themeasurementsarethesame. Jintra ≈1.

• InterJaccardIndex:– PUFmeasurementsofdifferent PUFchallenges.– Ideally, themeasurementsarecompletelydifferent.Jinter ≈0.

J(v1,v2 ) =v1∩v2v1∪v2

10CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Maxfractionalintra-HD

Minfractionalinter-HD

0.0045 0.0038

0.0003 0.0012

0.0083 0.0139

0.0005 0.0032

0.0101 0.0244

0.0020 0.0057

0.0123 0.0238

0.0013 0.0080

0.0206 0.0279

0.0022 0.0124

DRAMPUFCharacteristicsRobustnessandUniqueness

• Robustness:ForthesamePUF,thesamechallengexshouldalwaysproducealmostthesameresponsey. Jintra ≈1

• Uniqueness:FordifferentPUF,thesamechallengexshouldalwaysproduceverydifferentresponsey. Jinter ≈0

• JaccardindexisbetteratdistinguishingDRAMPUFmeasurements.Decaytime

device MinJintra

MaxJinter

120sPandaBoard 0.4634 0.0102

Galileo 0.7712 0.0038

180sPandaBoard 0.4382 0.0168

Galileo 0.8361 0.0044

240sPandaBoard 0.4087 0.0258

Galileo 0.6261 0.0049

300sPandaBoard 0.4222 0.0405

Galileo 0.7944 0.0055

360sPandaBoard 0.3484 0.0342

Galileo 0.8276 0.0072 11

Jaccard index between pairs of measurements0 0.2 0.4 0.6 0.8 1

Pro

bab

ility

0

0.05

0.1

0.15

Jinter

Jintra

Jaccard index between pairs of measurements0 0.2 0.4 0.6 0.8 1

Pro

bab

ility

0

0.05

0.1

0.15

0.2

0.25

Jinter

Jintra

DRAMPUFCharacteristicsRobustnessandUniqueness

DistributionofJintra and Jinter valuesfor(left)PandaBoardand(right)IntelGalileo.

• Robustness:ForthesamePUF,thesamechallengexshouldalwaysproducealmostthesameresponsey. Jintra ≈1

• Uniqueness:FordifferentPUF,thesamechallengexshouldalwaysproduceverydifferentresponsey. Jinter ≈0

• ThereisacleargapbetweenJintra and Jinter.->Uniqueness

12CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

TemperatureDependency• DRAMdecayalsodependsontheambienttemperature.• WeconductedtemperatureexperimentswithaheaterontopoftheDRAM.

Temperature-dependentdecayof(left)PandaBoardand(right)IntelGalileo.

13

40 60 800

0.05

0.1

0.15

0.2

0.25

0.3

Temperature (◦C)

Decay

rate

t1 = 120st2 = 180st3 = 240st4 = 300st5 = 360s

40 60 800

0.05

0.1

0.15

0.2

Temperature (◦C)

Decay

rate

t1 = 120st2 = 180st3 = 240st4 = 300st5 = 360s

CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

TemperatureDependency

120 180 240 300 3600

0.005

0.01

0.015

0.02

0.025

Decay time (sec)

Decay

rate

120 180 240 300 3600

0.002

0.004

0.006

0.008

0.01

0.012

Decay time (sec)

Decay

rate

Temperature-dependentdecayof(left)PandaBoardand(right)IntelGalileo.

14

40 60 800

0.05

0.1

0.15

0.2

0.25

0.3

Temperature (◦C)

Decay

rate

t1 = 120st2 = 180st3 = 240st4 = 300st5 = 360s

40 60 800

0.05

0.1

0.15

0.2

Temperature (◦C)

Decay

rate

t1 = 120st2 = 180st3 = 240st4 = 300st5 = 360s

CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

• HightemperaturespeedsuptheDRAMcelldecay.t’T’=t*e-0.0662*(T’-T)

• Underdifferenttemperature,withequivalent decaytimethesamedecaycanbeobserved.

• ThetemperaturedependencydoesnotaffecttherobustnessofthePUF.

Jin

tra

0

0.2

0.4

0.6

0.8

1

t1 t 2 t 3 t 4 t 5 t 1 t 2 t 3 t 4 t 5 t 1 t 2 t 3 t 4 t 540/C 50/C 60/C

TemperatureDependency

Jintra (i.e.similarity)ofenrollmentmeasurementstakenat40oCandmeasurementsatT’={40oC,50oC,60oC}onIntelGalileo.

15CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Stability• WetookmeasurementsfromsamePUF4monthsapart.• TheminimumJaccardindexisnoworsethanJintra.

->ThePUFisstableover4months.

Jaccard index between pairs of measurements0.75 0.8 0.85 0.9 0.95

Pro

bab

ility

0

0.02

0.04

0.06

0.08

0.1

0.12

DistributionofJaccardindexofmeasurementstakenfromthesamelogicalPUFonIntelGalileoover4monthswithdecaytime200s.

16CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Outline/Contributions• Extractdecay-basedDRAMPUFinstancesfromunmodifiedcommodity

devicesduringrun-timeoftheLinuxsystem• IntroducenewmetricsforevaluatingDRAMPUFs,basedontheJaccard

index• Throughextensiveexperiments,weshowthatDRAMPUFsexhibit

robustness,uniqueness,andstability.• Designprotocolsfordeviceauthenticationandsecurechannel

establishmentthatdrawtheirsecurityfromthetime-dependentdecayofDRAMcells

17CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

ProtocolforAuthentication• Threatmodel:Apassiveattacker,whoisabletoobservethenetworktraffic• Enrollment:A definedsetofdecaytimes

T={t0,t1,...,tn}MeasurementsforeachlogicalPUF

M={mid,0,mid,1,...,mid,n }

• Authentication:Theserverchoosesthesmallestdecaytimetx notpreviouslyusedforthelogicalPUFid.

Client C Server S

D T ,M,W,Kauthreq, id

t

x

, id

m0id,x

m

0id,x

d = J(m0id,x

,mid,x

)

d > ✏

auth

: auth

d ✏

auth

: noauth

8><

>:auth / noauth

18CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

SecureChannelEstablishment

Client C Server S

D T ,M,W,Kchannelreq, id

tx

, wid,x

m0id,x

kid,x

kid,x

kid,x

IfthereexistsasecurefuzzyextractorforourDRAMPUF.• EnrollmentAdefinedsetofdecaytimes

T={t0,t1,...,tn}MeasurementsforeachlogicalPUF

M={mid,0,mid,1,...,mid,n }Asetofrandomkeys

K={kid,0,kid,1,...,kid,n }Helperdata

W={wid,0,wid,1,...,wid,n }

19CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Time Dependent Decay• HowtochoosethesetofdecaytimesT={t0,t1,...,tn}?

• Securityisinthenewlyflippedbitsintx+1comparedtotx.• Security parameterεbits :numberofnewlyflippedbits.

Knowingmx,theprobabilityofarandomguessofmx+1 beingsuccessfulissmallerthan2-128.

tx tx+1

120 180 240 300 3600

0.002

0.004

0.006

0.008

0.01

0.012

Decay time (sec)

Decay

rate

120 180 240 300 3600

0.005

0.01

0.015

0.02

0.025

Decay time (sec)

Decay

rate

Redlinesindicatepossibledecaytimechallenges.IntelGalileocanprovide7challenges,andPandaBoardcanprovide2challengeswith32KBlogicalPUFanddecaytimet<360s.

20CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Conclusions• Extractdecay-basedDRAMPUFinstancesfromunmodifiedcommodity

devices.– Twoplatforms:thePandaBoard andtheIntelGalileo– Twoapproaches:acustomizedfirmware,andakernelmodule

• IntroducednewmetricsforevaluatingDRAMPUFs,basedontheJaccardindex.

• ShowedthatDRAMPUFsexhibitrobustness,uniqueness,andstabilitywiththedecaytimeaspartofthePUFchallenge.

• Designedprotocolsfordeviceauthenticationandsecurechannelestablishmentthatdrawtheirsecurityfromthetime-dependentdecayofDRAMcells.

21CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Futurework• Construct fuzzy extractor forDRAMPUF

– Jaccard index– BiasedPUF

• BetterunderstandDRAMPUFcharacteristics– Temperature dependency– Voltagedependency

• Improveread out time– Intheorderofminutes

22CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Acknowledgements

Thisworkhasbeenco-fundedbytheDFGaspartofprojectP3withintheCRC1119CROSSING,andpartlyfundedbyCASED.

ThankstoKevinRyanandEthanWeinbergerfortheirhelpwithbuildingtheheatersetup.

ThankstoIntelfordonatingtheIntelGalileoboardsusedinthiswork.

ThankstoanonymousCHESreviewers,andespeciallyourshepherd,RoelMaes.

23CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

Q&A• Extractdecay-basedDRAMPUFinstancesfromunmodifiedcommodity

devices.– Twoplatforms:thePandaBoard andtheIntelGalileo– Twoapproaches:acustomizedfirmware,andakernelmodule

• IntroducednewmetricsforevaluatingDRAMPUFs,basedontheJaccardindex.

• ShowedthatDRAMPUFsexhibitrobustness,uniqueness,andstabilitywiththedecaytimeaspartofthePUFchallenge.

• Designedprotocolsfordeviceauthenticationandsecurechannelestablishmentthatdrawtheirsecurityfromthetime-dependentdecayofDRAMcells.

24CHES2016|Run-timeAccessibleDRAMPUFsinCommodityDevices| W. Xiong, et al.

25

DRAMcelldecay

Figure1:SchematicofaDRAMarray;arrowsindicateleakage

pathsfordissipationofchargesthatleadtoPUFbehavior.

26

tx

tx+1

RobustnessandUniqueness

27

Maxfractionalintra-HD

Minfractionalinter-HD

0.0045 0.0038

0.0003 0.0012

0.0083 0.0139

0.0005 0.0032

0.0101 0.0244

0.0020 0.0057

0.0123 0.0238

0.0013 0.0080

0.0206 0.0279

0.0022 0.0124

Decaytime

device MinJintra

MaxJinter

120sPandaBoard 0.4634 0.0102

Galileo 0.7712 0.0038

180sPandaBoard 0.4382 0.0168

Galileo 0.8361 0.0044

240sPandaBoard 0.4087 0.0258

Galileo 0.6261 0.0049

300sPandaBoard 0.4222 0.0405

Galileo 0.7944 0.0055

360sPandaBoard 0.3484 0.0342

Galileo 0.8276 0.0072

Jaccard index between pairs of measurements0 0.2 0.4 0.6 0.8 1

Pro

bab

ility

0

0.05

0.1

0.15

Jinter

Jintra

Jaccard index between pairs of measurements0 0.2 0.4 0.6 0.8 1

Pro

bab

ility

0

0.05

0.1

0.15

0.2

0.25

Jinter

Jintra

Figure3:DistributionofJintra and Jinter valuesfor(left)Pandaboardand(right)IntelGalileo.

• HightemperaturespeedsuptheDRAMcelldecay.t’T’=t*e-0.0662*(T’-T)

• Underdifferenttemperature,withequivalent decaytimethesamedecaycanbeobserved.

• ThetemperaturedependencydoesnotaffecttherobustnessofthePUF.

Jin

tra

0

0.2

0.4

0.6

0.8

1

t1 t 2 t 3 t 4 t 5 t 1 t 2 t 3 t 4 t 5 t 1 t 2 t 3 t 4 t 540/C 50/C 60/C

Temperaturedependency

Figure5:Jintra (i.e.similarity)ofenrollmentmeasurementstakenat40oCandmeasurementsatT’={40oC,50oC,60oC}onIntelGalileo.

28