GameSec 2018

Conference on Decision and Game Theory for Security

October 29 - 31, 2018, Seattle, WA, USA

2018 Conference on Decision and Game Theory for Security

GameSec 2018, the 9th Conference on Decision and Game Theory for Security will take place in Seattle, WA, USA, on October 29 - 31, 2018.

The conference proceedings will be published by Springer as part of the LNCS series.

Description

Recent advances in information and communication technologies pose significant security challenges that impact all aspects of modern society. The 9th Conference on Decision and Game Theory for Security in Seattle, Washington, USA, focuses on protection of heterogeneous, large-scale and dynamic systems as well as managing security risks faced by critical infrastructures through rigorous and practically-relevant analytical methods. GameSec 2018 invites novel, high-quality theoretical and practical-relevant contributions, which apply decision and game theory, as well as related techniques such as distributed optimization, dynamic control and mechanism design, to build resilient, secure, and dependable networked systems. The goal of GameSec 2018 is to bring together academic and industrial researchers in an effort to identify and discuss the major technical challenges and recent results that highlight the connections between game theory, control, distributed optimization, economic incentives and real-world security, reputation, trust and privacy problems.

Conference Topics include (but are not restricted to):

The goal of GameSec is to bring together academic and indus- trial researchers in an effort to identify and discuss the major technical challenges and recent results that highlight the connection between game theory, control, distributed optimization, economic incentives and real world security, reputation, trust and privacy problems in a variety of technological systems. Submissions should solely be original research papers that have neither been published nor submitted for publication elsewhere.

  • Game theory, control, and mechanism design for security and privacy
  • Decision making for cybersecurity and security requirements engineering
  • Security and privacy for the Internet-of-Things, cyber-physical systems, cloud computing, resilient control systems, and critical infrastructure
  • Pricing, economic incentives, security investments, and cyber insurance for dependable and secure systems
  • Risk assessment and security risk management
  • Security and privacy of wireless and mobile communications, including user location privacy
  • Socio-technological and behavioral approaches to security
  • Empirical and experimental studies with game, control, or optimization theory-based analysis for security and privacy
  • Adversarial Machine Learning and the role of AI in system security

Special Track on "Adversarial AI"

Day 2, Afternoon session. AI techniques have made significant inroads into security applications, such as crime prediction and detection in physical security, and intrusion and malware detection in cybersecurity. An important challenge in such adversarial applications of AI is that sophisticated malicious parties can manipulate the AI decision process, for example, by changing the decision environment or poisoning data used for learning, in order to degrade its effectiveness. The research area of Adversarial AI aims to understand vulnerabilities of AI systems to such adversarial tampering, as well as to develop techniques which make intelligent autonomous decision making robust to adversarial subversion. This special track invites submissions on approaches for attacking and defending AI systems, including research on adversarial machine learning, planning in adversarial settings, adversarial crowdsourcing, and more broadly on the use of AI in security and privacy. Please submit to the special track under the topic "Adversarial AI".

Tutorial Session on "Game-Theoretic Security"

Day 1, Morning session. Cyber attacks on both databases and critical infrastructure have threatened public and private sectors. Meanwhile, ubiquitous tracking and wearable computing have infringed upon privacy. Advocates and engineers have recently proposed using defensive deception as a means to leverage the information asymmetry typically enjoyed by attackers as a tool for defenders. In this tutorial, we give the audience an overview on the application of game theory to model deception for cybersecurity and privacy.  The goal of this tutorial is to elaborate the taxonomy of deception, to provide the state-of-art literature, and to discuss recent advances in deceptive technologies in cybersecurity and privacy.

Plenary Speakers

Plenary Speaker

Photo: Professor João Hespanha
Professor
João Hespanha
João P. Hespanha received his Ph.D. degree in electrical engineering and applied science from Yale University, New Haven, Connecticut in 1998. From 1999 to 2001, he was a Professor at the University of Southern California, Los Angeles. He moved to the University of California, Santa Barbara in 2002, where he currently holds a Professor position with the Department of Electrical and Computer Engineering. Dr. Hespanha is the recipient of the Yale University’s Henry Prentiss Becton Graduate Prize for exceptional achievement in research in Engineering and Applied Science, a National Science Foundation CAREER Award, the 2005 best paper award at the 2nd Int. Conf. on Intelligent Sensing and Information Processing, the 2005 Automatica Theory/Methodology best paper prize, the 2006 George S. Axelby Outstanding Paper Award, and the 2009 Ruberti Young Researcher Prize. Dr. Hespanha is a Fellow of the IEEE and he was an IEEE distinguished lecturer from 2007 to 2013. His current research interests include multi-agent control systems, distributed control over communication networks (also known as networked control systems), optimization, hybrid and switched systems, stochastic modeling in biology, and network security.
Abstract: TBD

Conference Sponsors and Supporters

We thank all our sponsors for their kind support.