Self-Fulfilling Mechanisms in Bayesian Games

1998 ◽  
Vol 25 (2) ◽  
pp. 292-310 ◽  
Author(s):  
Françoise Forges ◽  
Enrico Minelli
Keyword(s):  
Bayesian Games

scholarly journals Game-Theoretic Decision Support for Cyber Forensic Investigations

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5300
Author(s):  
Antonia Nisioti ◽  
George Loukas ◽  
Stefan Rass ◽  
Emmanouil Panaousis
Keyword(s):  
Cyber Security ◽  
Strategic Decisions ◽  
Bayesian Games ◽  
Bayesian Game ◽  
Cyber Forensics ◽  
Detection And Attribution ◽  
Different Types ◽  
Game Theoretic ◽  
The Cost

The use of anti-forensic techniques is a very common practice that stealthy adversaries may deploy to minimise their traces and make the investigation of an incident harder by evading detection and attribution. In this paper, we study the interaction between a cyber forensic Investigator and a strategic Attacker using a game-theoretic framework. This is based on a Bayesian game of incomplete information played on a multi-host cyber forensics investigation graph of actions traversed by both players. The edges of the graph represent players’ actions across different hosts in a network. In alignment with the concept of Bayesian games, we define two Attacker types to represent their ability of deploying anti-forensic techniques to conceal their activities. In this way, our model allows the Investigator to identify the optimal investigating policy taking into consideration the cost and impact of the available actions, while coping with the uncertainty of the Attacker’s type and strategic decisions. To evaluate our model, we construct a realistic case study based on threat reports and data extracted from the MITRE ATT&CK STIX repository, Common Vulnerability Scoring System (CVSS), and interviews with cyber-security practitioners. We use the case study to compare the performance of the proposed method against two other investigative methods and three different types of Attackers.

Ex-ante Agent Transformation of Bayesian Games

2021 ◽  
pp. 1-1
Author(s):  
Yuhu Wu ◽  
Shuting Le ◽  
Kuize Zhang ◽  
Xi-Ming Sun
Keyword(s):  
Bayesian Games ◽  
Ex Ante

Static Bayesian games

2021 ◽  
pp. 445-472
Author(s):  
Harald Wiese
Keyword(s):  
Bayesian Games

A Research on Battlefield Situation Assessment with Bayesian Games

2014 ◽  
Vol 13 (11) ◽  
pp. 1878-1882
Author(s):  
J.J. Yan ◽  
Y. Wang ◽  
H. Cheng
Keyword(s):  
Bayesian Games ◽  
Situation Assessment

scholarly journals On games without approximate equilibria

2020 ◽  
Vol 49 (4) ◽  
pp. 1125-1128
Author(s):  
Yehuda John Levy
Keyword(s):  
Game Theory ◽  
Bayesian Games ◽  
Open Question

AbstractThis note shows that the work by Simon and Tomkowicz (Israel J Math 227(1):215–231, 2018) answers another outstanding open question in game theory in addition to the non-existence of approximate Harsányi equilibrium in Bayesian games: it shows that strategic form games with bounded and separately continuous payoffs need not possess approximate equilibria.

scholarly journals Bayesian games with intentions

2020 ◽  
Vol 123 ◽  
pp. 54-67
Author(s):  
Adam Bjorndahl ◽  
Joseph Y. Halpern ◽  
Rafael Pass
Keyword(s):  
Bayesian Games

LEARNING IN BAYESIAN GAMES BY BOUNDED RATIONAL PLAYERS II: NONMYOPIA

1998 ◽  
Vol 2 (2) ◽  
pp. 141-155 ◽  
Author(s):  
Konstantinos Serfes ◽  
Nicholas C. Yannelis
Keyword(s):  
Nash Equilibrium ◽  
Arbitrary Number ◽  
Bayesian Learning ◽  
Full Information ◽  
Bayesian Games ◽  
Response Strategies ◽  
Bayesian Nash Equilibrium ◽  
Current Period ◽  
Best Response ◽  
Rational Players

We generalize results of earlier work on learning in Bayesian games by allowing players to make decisions in a nonmyopic fashion. In particular, we address the issue of nonmyopic Bayesian learning with an arbitrary number of bounded rational players, i.e., players who choose approximate best-response strategies for the entire horizon (rather than the current period). We show that, by repetition, nonmyopic bounded rational players can reach a limit full-information nonmyopic Bayesian Nash equilibrium (NBNE) strategy. The converse is also proved: Given a limit full-information NBNE strategy, one can find a sequence of nonmyopic bounded rational plays that converges to that strategy.

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