Decision and Game Theory for Security: 6th International by Arman (MHR) Khouzani, Emmanouil Panaousis, George

By Arman (MHR) Khouzani, Emmanouil Panaousis, George Theodorakopoulos

This e-book constitutes the refereed complaints of the sixth foreign convention on choice and video game idea for safeguard, GameSec 2015, held in London, united kingdom, in November 2015.

The sixteen revised complete papers awarded including five brief papers have been rigorously reviewed and chosen from 37 submissions. video game and choice concept has emerged as a worthy systematic framework with strong analytical instruments in facing the intricacies all in favour of making sound and brilliant safeguard judgements. for example, online game concept presents methodical techniques to account for interdependencies of safeguard judgements, the function of hidden and uneven details, the belief of hazards and prices in human behaviour, the incentives/limitations of the attackers, and masses extra. mixed with our classical method of computing device and community protection, and drawing from quite a few fields equivalent to fiscal, social and behavioural sciences, online game and determination conception is taking part in a basic position within the improvement of the pillars of the "science of security".

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Additional info for Decision and Game Theory for Security: 6th International Conference, GameSec 2015, London, UK, November 4-5, 2015, Proceedings

Sample text

As previously discussed, the amount of field experiments that can be conducted (and thus the amount of training data available for learning) is limited; it is important to know whether the model with superior prediction accuracy will actually result in higher defender gains than a model with worse prediction accuracy (especially when training data is limited). ” We first lay the groundwork for determining whether our proposed construct of predictive reliability is valid in SSGs. As such, we first (i) conduct an empirical evaluation of predictive reliability in SSGs in situations where there is a large amount of training data.

The Perfectly Rational Model In NSG literature, the adversary is often assumed to be perfectly rational and will always maximize his expected utility. , Aopt = argmaxAj EUa (x, Aj ). 2 The Quantal Response Model The Quantal Response (QR) model for NSGs was first introduced by Yang et al. [18]. However, their formulation only works under the assumption that there is one defender resource available, and as a result, we present a revised version of the QR model for a zero-sum NSG with multiple defender resources.

Humans do not behave with perfect rationality [3]. Gutfraind et al. [8] address one type of boundedly rational adversary, an unreactive Markovian evader, in their work. , attacker) is unreactive to the defender’s actions, the relaxation of the rational adversary assumption still results in an NP-hard problem. Positing that humans will rely on heuristics due to the complex nature of solving an NSG, Yang et al. [18] address bounded rationality in a non-zero sum NSG setting by modeling the adversary’s stochastic decision making with the Quantal Response (QR) model and various heuristic based variants of the QR model.

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