Dynamic Games for Network Security

82 Pages·2018·4.202 MB·English

by  Xiaofan He,Huaiyu Dai (auth.)

SPRINGER BRIEFS IN
ELECTRICAL AND COMPUTER ENGINEERING
Xiaofan He · Huaiyu Dai
Dynamic Games
for Network
Security
123
SpringerBriefs in Electrical and Computer
Engineering
Serieseditors
Woon-SengGan
SchofElectrical&ElectronicEngg
NanyangTechnologicalUniversity
Singapore,Singapore
C.-C.JayKuo
UniversityofSouthernCalifornia
LosAngeles,California,USA
ThomasFangZheng
ResInstInfoTech
TsinghuaUniversity
Beijing,China
MauroBarni
DeptofInfoEngg&Mathematics
UniversityofSiena
Siena,Italy
Moreinformationaboutthisseriesathttp://www.springer.com/series/10059
Xiaofan He • Huaiyu Dai
Dynamic Games for Network
Security
123
XiaofanHe HuaiyuDai
DepartmentofElectricalEngineering DepartmentofElectricalandComputer
LamarUniversity Engineering
Beaumont,TX,USA NorthCarolinaStateUniversity
Raleigh,NC,USA
ISSN2191-8112 ISSN2191-8120 (electronic)
SpringerBriefsinElectricalandComputerEngineering
ISBN978-3-319-75870-1 ISBN978-3-319-75871-8 (eBook)
https://doi.org/10.1007/978-3-319-75871-8
LibraryofCongressControlNumber:2018933373
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HuaiyuDai
Preface
Therecentemergenceandadvancementofvariousinformationandcyber-physical
networks have brought unprecedented convenience to our daily lives. To ensure
effectiveandcontinuousoperationsofthesemodernnetworks,itisofcrucialimpor-
tancetodeployefficientandreliabledefensemechanismstoprotecttheirsecurity.
However, in the security battles, one challenge is that the adversary is constantly
upgrading their attacking tactics and becoming increasingly intelligent, making
conventional static security mechanisms outdated and incompetent. Considering
this,gametheory,whichisarichsetofanalytictoolsformodelingandanalyzingthe
strategic interactions among intelligent entities, has been widely employed by the
network security community for predicting the adversary’s attacking strategy and
designingthecorrespondingoptimaldefense.Despiteitscelebratedapplicationsin
addressingsomenetworksecurityproblems,theclassicgametheorymainlyfocuses
on static settings, while many practical security competitions often take place in
dynamicscenariosduetofrequentchangesinboththeambientenvironmentandthe
underlying networks. This motivates the recent exploration of the more advanced
stochasticgame(SG)theorythatcancapturenotonlytheinteractionsbetweenthe
defenderandtheattackerbutalsotheenvironmentaldynamics.Theobjectiveofthis
bookistocollectandsystematicallypresentthestateoftheartinthisresearchfield
andtheunderlyinggame-theoreticandlearningtoolstothebroaderaudiencewith
generalnetworksecurityandengineeringbackgrounds.
Our exposition of this book begins with a brief introduction of relevant back-
ground knowledge in Chap.1. Elementary game theory, Markov decision process
(MDP),andSGarecovered,includingthebasicconceptsandmathematicalmodels
aswellasthecorrespondingsolutiontechniques.Withthisnecessarybackground,
inChap.2,weproceedtoreviewexistingapplicationsofSGinaddressingvarious
dynamic security games, in the context of cyber networks, wireless networks, and
cyber-physical networks. In these applications, the defenders and the attackers are
assumedtoholdequalinformationaboutthecorrespondingsecuritycompetitions,
whereasinformationasymmetryoftenexistsinpractice.Consideringthis,wetakea
stepfurtherandexplorehowtodealwithdynamicsecuritygamesinthepresenceof
informationasymmetryinChaps.3–5.Inparticular,ourexplorationincludesthree
vii
viii Preface
aspects of this issue—dynamic security games with extra information, dynamic
security games with incomplete information, and dynamic security games with
deception. It is worth mentioning that, although we mainly take the defender’s
perspective in the discussions, the corresponding results and techniques may be
employedtopredicttheattacker’sbehaviorinsimilarsituations.Morespecifically,
dynamic security games with extra information discussed in Chap.3 concern
security competitions where the defender has an informational advantage over the
adversary.BasedontheexistingSGframework,wepresentanoveltechniquethat
enablesthedefendertofullyexploitsuchadvantagesoastoachievefasteradapta-
tion and learning indynamic security competitions. The complementary scenarios
wherethedefenderlacksinformationabouttheadversaryareexaminedinChap.4
throughthelensofincompleteinformationSG.Toaddressincompleteinformation
SGs, a new algorithm that integrates Bayesian learning and conventional learning
algorithms of SG is presented; the key idea is to allow the defender to gradually
inferthemissinginformationthroughrepeatedinteractionswiththeadversary.The
extra and the incomplete information considered in Chaps.3 and 4 is inherent to
thecorrespondingsecurityproblems.InChap.5,weswitchgearandfurtherexplore
how to proactively create information asymmetry for the defender’s benefit, and
the dynamic deception technique is investigated as an effective tool to achieve
thisobjective.Lastly,concludingremarksandourperspectiveforfutureworksare
presentedinChap.6.
TheauthorswouldliketoacknowledgeProf.RudraDutta,Prof.PengNing,and
Mr. Richeng Jin. Without their contribution, this book could not have been made
possible. We would also like to thank all the colleagues and researchers for their
pioneeringandinspiringworksthatlayoutthesolidfoundationofthisbook.
Wuhan,Hubei,China XiaofanHe
Raleigh,NC,USA HuaiyuDai
Contents
1 Preliminaries .................................................................. 1
1.1 Introduction .............................................................. 1
1.2 ElementaryofGameTheory ............................................ 2
1.3 TheMarkovDecisionProcess........................................... 4
1.3.1 TheMDPModel................................................. 4
1.3.2 SolvingtheMDP ................................................ 5
1.4 TheStochasticGames ................................................... 7
1.4.1 TheModelofSG ................................................ 7
1.4.2 SolvingtheSG................................................... 9
1.5 Summary ................................................................. 15
References...................................................................... 15
2 OverviewofDynamicNetworkSecurityGames .......................... 17
2.1 Introduction .............................................................. 17
2.2 ApplicationsinCyberNetworks ........................................ 18
2.3 ApplicationsinWirelessNetworks ..................................... 19
2.4 ApplicationsinCyber-PhysicalNetworks.............................. 20
2.5 Summary ................................................................. 22
References...................................................................... 22
3 DynamicSecurityGameswithExtraInformation........................ 25
3.1 Introduction .............................................................. 25
3.2 Post-decisionState....................................................... 26
3.3 Multi-AgentPDSLearning.............................................. 28
3.3.1 TheMinimax-PDSAlgorithm .................................. 30
3.3.2 WoLF-PDS....................................................... 32
3.4 SecurityApplications.................................................... 33
3.4.1 Anti-jamminginEnergyHarvestingCommunication
Systems........................................................... 34
3.4.2 Cloud-BasedSecurityGame.................................... 37
3.5 Summary ................................................................. 41
References...................................................................... 41
ix
x Contents
4 DynamicSecurityGameswithIncompleteInformation ................. 43
4.1 Introduction .............................................................. 43
4.2 BackgroundonRepeatedBayesianGame.............................. 44
4.3 BayesianSGs............................................................. 45
4.3.1 BayesianSGModel.............................................. 45
4.3.2 BayesianNashQ-Learning...................................... 47
4.4 SecurityApplications.................................................... 48
4.4.1 DynamicIntrusionDetectionSystemConfiguration........... 49
4.4.2 SpectrumAccessinAdversarialEnvironment ................. 54
4.5 Summary ................................................................. 59
References...................................................................... 59
5 DynamicSecurityGameswithDeception.................................. 61
5.1 Introduction .............................................................. 61
5.2 StochasticDeceptionGames ............................................ 62
5.2.1 TheSDGModel ................................................. 62
5.2.2 SolvingtheSDG................................................. 65
5.3 ASecurityApplication .................................................. 67
5.4 Summary ................................................................. 69
References...................................................................... 71
6 ConclusionandFutureWork................................................ 73
6.1 Summary ................................................................. 73
6.2 FutureWorks............................................................. 74