# Game Theory Meets Network Security

A Tutorial

Quanyan Zhu  New York University5 MetroTech CenterBrooklynNew York11201
<EMAIL_ADDRESS>and  Stefan Rass  Universitaet KlagenfurtUniversitaetsstr.
65-67, A-9020 KlagenfurtAustria<EMAIL_ADDRESS>
(2018)

###### Abstract.

The increasingly pervasive connectivity of today’s information systems brings
up new challenges to security. Traditional security has accomplished a long
way toward protecting well-defined goals such as confidentiality, integrity,
availability, and authenticity. However, with the growing sophistication of
the attacks and the complexity of the system, the protection using traditional
methods could be cost-prohibitive. A new perspective and a new theoretical
foundation are needed to understand security from a strategic and decision-
making perspective. Game theory provides a natural framework to capture the
adversarial and defensive interactions between an attacker and a defender. It
provides a quantitative assessment of security, prediction of security
outcomes, and a mechanism design tool that can enable security-by-design and
reverse the attacker’s advantage. This tutorial provides an overview of
diverse methodologies from game theory that includes games of incomplete
information, dynamic games, mechanism design theory to offer a modern
theoretic underpinning of a science of cybersecurity. The tutorial will also
discuss open problems and research challenges that the CCS community can
address and contribute with an objective to build a multidisciplinary bridge
between cybersecurity, economics, game and decision theory.

Game theory, Network security, Defense strategy, Mechanism design, Decision
theory, Security economics

††journalyear: 2018††copyright: acmcopyright††conference: 2018 ACM SIGSAC
Conference on Computer & Communications Security; October 15–19, 2018;
Toronto, ON, Canada††booktitle: CCS ’18: 2018 ACM SIGSAC Conference on
Computer & Communications Security Oct. 15–19, 2018, Toronto, ON,
Canada††price: 15.00††doi: 10.1145/3243734.3264421††isbn:
978-1-4503-5693-0/18/10††copyright: rightsretained††article: 4††price:
15.00††ccs: Security and privacy Network security††ccs: Mathematics of
computing††ccs: Theory of computation Algorithmic game theory and mechanism
design

##  1\. Tutorial Description

Contemporary information and communication technology evolves fast not only in
terms of the level of sophistication but also regarding its diversity. The
increasing complexity, pervasiveness, and connectivity of today’s information
systems brings up new challenges to security, and the cyberspace has become a
playground for people with all levels of skills and all kinds of intention
(positive and negative). With 24/7 connectivity having become an integral part
of people’s daily life, protecting information, identities, and assets has
gained more importance than ever. Traditional security has accomplished a long
way toward protecting well-defined goals such as confidentiality, integrity,
availability, and authenticity (CIA+). Cryptography is a solid theoretic
foundation for security which relies on the secrecy of cryptographic keys.
However, for attackers who can steal full cryptographic keys as in advanced
persistent threats (APTs) or social engineering attacks, the assumption of key
secrecy fails, and they can penetrate the system. A new perspective and a new
theoretical foundation are needed to capture scenarios where an attacker can
completely compromise a system, and a defender aims to protect the system
without the assumption of key secrecy.

Game-theoretic models are natural frameworks to capture the adversarial and
defensive interactions between players (zhu2018multi, ; rass2017physical, ;
zhuang2010modeling, ; miao2018hybrid, ; farhang2014dynamic, ;
manshaei2013game, ; zhu2013deployment, ; zhang2017strategic, ;
horak2017manipulating, ; huang2017large, ). Game theory can provide a
quantitative measure of the quality of protection with the concept of Nash
equilibrium where both defender and an attacker seek optimal strategies, and
no one has an incentive to deviate unilaterally from their equilibrium
strategies despite their conflict for security objectives. The equilibrium
concept also provides a quantitative prediction of the security outcomes of
the scenario the game model captures. With the quantitative measures of
security, game theory makes security manageable beyond the strong qualitative
assurances of cryptographic protections. Extending this approach to mechanism
design provides system designers freedom to shift the equilibrium and the
predicted outcomes toward ones that are favored by the defender or the system
designer via an elaborate design of the game structure.

For more than a decade now, the interest in the field has proliferated, and
game- and decision theory has become a systematic and well proven powerful
theoretic underpinning of today’s security research. Somewhat different from
standard security definitions, game- and decision theory adopts a different
and more economic viewpoint: security is not the absence of threats, but the
point where attacking a system has become more expensive than not attacking.
Starting from a game- and decision-theoretic root thus achieves the most
elegant type of self-enforcing security, by analyzing and creating incentives
to encourage actively honest behaviors rather than preventing maliciousness.
At the same time, the economic approach to security is also essential as it
parallels the evolution of today’s attackers. Cybercrime has grown into a
full-featured economy, maintaining black markets, supply chains, and widely
resembling an illegal counterpart of the of the official software market.
Traditional security remains an important foundation to tackle the issue from
below, but game- and decision theory offers a top-down view by adopting the
economic and strategic view of the attackers too, and as such complements
purely technological security means. The optimum is achieved when both routes
are taken towards meeting in the middle, which is what game and decision
theory aims to achieve.

The objective of this tutorial is to introduce diverse methodologies from game
theory that include mechanism design, incentive analysis, decision-making
under incomplete information, and dynamic games to provide solid underpinnings
of a science of cybersecurity. The tutorial will be organized to connect
different classes of games with different sets of security problems. For
example (1) Stackelberg and multi-layer games for proactive defense
(pawlick_stackelberg_2016, ; zhu2013game, ; zhu2013deployment, ;
zhu2013hybrid, ; zhu2012interference, ; clark2012deceptive, ; zhu2012game, ;
zhu2012deceptive, ; zhu2010stochastic, ), (2) network games for cyber-physical
security that deals with critical infrastructure protection and information
assurance (xu2017secure, ; xu_game-theoretic_2017, ; xu_cross-layer_2016, ;
xu2015cyber, ; huang2017large, ; chen2017dynamic, ; miao2018hybrid, ;
yuan2013resilient, ; Rass&Zhu2016, ; Rass.2017b, ), (3) dynamic games for
adaptive defense for network security (zhu2010dynamic, ; zhang2017strategic, ;
huang2018gamesec, ; huang2018PER, ; pawlick2015flip, ; farhang2014dynamic, ;
zhu2009dynamic, ; zhu2010network, ; zhu2010heterogeneous, ), (4) mechanism
design theory for economics of network security that investigates resource
allocation methodologies (chen_security_2017, ; zhang_bi-level_2017, ;
zhang_attack-aware_2016, ; casey2015compliance, ; hayel2015attack, ;
hayel2017epidemic, ; zhu2012guidex, ; zhu2012tragedy, ; zhu2009game, ), and
(5) game-theoretic analysis of cryptographic concepts, such as perfectly
confidentiality and authentication (in classical and quantum networks)
(Rass&Schartner2009, ; Rass&Schartner2010, ; Rass&Schartner2011c, ;
Rass&Schartner2011, ), network design and -provisioning
(Rass&Wiegele&Schartner2010, ; Rass&Rainer2015, ; Rass&Rainer2013, ; Rass2011,
; Rass2013c, ; Rass2014, ) and quantitative security risk management
(Rass2015b, ; Rass2015c, ; Rass.20171102, ; Rass.2018, ; Rass.2017d, ;
Rass.2018b, ; Rass&Konig&Schauer2015b, ; Rass&Konig&Schauer2016, ;
Rass&Konig&Schauer2017, ; Rass&Konig2016, ; Rass&Rainer2014, ;
Rass&Schartner&Wigoutschnigg2010, )

From the perspective of cybersecurity, the topics of this tutorial will cover
recent applications of game theory to several emerging topics such as cross-
layer cyber-physical security (miao2018hybrid, ; zhu2018multi, ;
pawlick2017strategic, ; chen2017security, ; zhu2015game, ; xu2017secure, ),
cyber deception (pawlick2018modeling, ; zhang2017strategic, ;
horak2017manipulating, ; pawlick2017game, ; pawlick2015deception, ;
zhuang2010modeling, ), moving target defense (zhu2013game, ;
jajodia2011moving, ; maleki2016markov, ), critical infrastructure protection
(chen2017dynamic, ; rass2017physical, ; huang2017large, ;
pawlick2017proactive, ; chen_interdependent_2016, ; hayel2015resilient, ;
huang2018PER, ), adversarial machine learning (zhang2018game, ;
wang2017detection, ; zhang2017game, ; pawlick_stackelberg_2016, ;
pawlick_mean-field_2017, ), insider threats (casey_compliance_2016, ;
casey2015compliance, ), and cyber risk management (zhang2017bi, ;
hayel2017epidemic, ; fung2016facid, ; chen2018security, ). The tutorial will
also discuss open problems and research challenges that the CCS community can
address and contribute. With the objective to build a multidisciplinary bridge
between cybersecurity, economics, game and decision theory, this tutorial will
review basic concepts and provide an overview of recent advances in the field
to CCS community with the hope to establish a community interest in the
science of security and cross-disciplinary researches.

The potential audience includes researchers from academia and industry,
including PhD and graduate students. Some background in network security and
knowledge of basic optimization and data science is helpful but not necessary.
The tutorial takes 1.5 hours.

##  2\. Author Biography

Quanyan Zhu received B. Eng. in Honors Electrical Engineering from McGill
University in 2006, M.A.Sc. from University of Toronto in 2008, and Ph.D. from
the University of Illinois at Urbana-Champaign (UIUC) in 2013. After stints at
Princeton University, he is currently an assistant professor at the Department
of Electrical and Computer Engineering, New York University. He is a recipient
of many awards including NSERC Canada Graduate Scholarship (CGS), Mavis Future
Faculty Fellowships, and NSERC Postdoctoral Fellowship (PDF). He spearheaded
and chaired INFOCOM Workshop on Communications and Control on Smart Energy
Systems (CCSES), and Midwest Workshop on Control and Game Theory (WCGT). His
current research interests include resilient and secure interdependent
critical infrastructures, energy systems, cyber-physical systems, and cyber-
enabled sustainability. He is a recipient of best paper awards at 5th
International Conference on Resilient Control Systems, and 18th International
Conference on Information Fusion. He has served as the general chair of the
7th Conference on Decision and Game Theory for Security (GameSec) in 2016 and
International Conference on NETwork Games, COntrol and OPtimisation (NETGCOOP)
in 2018. Website: http://wp.nyu.edu/quanyan

Stefan Rass graduated with a double master degree in mathematics and computer
science from the Universitaet Klagenfurt in 2005. He received a PhD degree in
mathematics in 2009, and habilitated on applied computer science and system
security in 2014. His research interests cover decision theory and game-theory
with applications in system security, as well as complexity theory, statistics
and information-theoretic security. He authored numerous papers related to
security and applied statistics and decision theory in security. He (co-
authored) the book “Cryptography for Security and Privacy in Cloud Computing”,
published by Artech House, and edited the Birkhäuser Book “Game Theory for
Security and Risk Management: From Theory to Practice” in the series on Static
& Dynamic Game Theory: Foundations & Applications. He participated in various
nationally and internationally funded research projects, as well as being a
contributing researcher in many EU projects and offering consultancy services
to the industry. Currently, he is an associate professor at the AAU, teaching
courses on algorithms and data structures, theoretical computer science,
complexity theory, security and cryptography. Website:
https://www.syssec.at/en/team/rass

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