Coping with Digital Extortion: An Experimental Study of Benefit Appeals and Normative Appeals

Digital extortion has emerged as a significant threat to organizations that rely on information technologies for their operations. Using human subject experimentation, we study the effectiveness of message appeals in encouraging defenders to adopt two mitigation strategies, investment in security and refusal to pay ransoms, to digital extortion threats. We explore two types of appeals, benefit and normative, for this purpose. We find that the decisions of the defenders (representing any organization that can be a potential victim) deviate from the predictions of game theory. However, given the strategic interactions between the defenders and the attacker as well as noisy decision-making behaviors, it is challenging to untangle the influence of the appeals on the defenders. We develop a structural model based on the quantal response equilibrium framework to measure how message appeals change the defenders’ utilities of investment and payment refusal. Although the interventions may be successful in increasing the utilities of investment and/or payment refusal, their impacts on investment rate and payment rate are mitigated by the attacker reducing ransoms. Thus, it is challenging for an intervention to significantly boost a community’s investment rate or to suppress the ransom payment rate. We characterize how security outcomes of a community (including expected ransom, attack rate, investment rate, and payment rate) vary with the defenders’ utilities of investment and pay refusal. This paper was accepted by Chris Forman, information systems.

Bounded rational response equilibria in human sensorimotor interactions

The Nash equilibrium is one of the most central solution concepts to study strategic interactions between multiple players and has recently also been shown to capture sensorimotor interactions between players that are haptically coupled. While previous studies in behavioural economics have shown that systematic deviations from Nash equilibria in economic decision-making can be explained by the more general quantal response equilibria, such deviations have not been reported for the sensorimotor domain. Here we investigate haptically coupled dyads across three different sensorimotor games corresponding to the classic symmetric and asymmetric Prisoner's Dilemma, where the quantal response equilibrium predicts characteristic shifts across the three games, although the Nash equilibrium stays the same. We find that subjects exhibit the predicted deviations from the Nash solution. Furthermore, we show that taking into account subjects' priors for the games, we arrive at a more accurate description of bounded rational response equilibria that can be regarded as a quantal response equilibrium with non-uniform prior. Our results suggest that bounded rational response equilibria provide a general tool to explain sensorimotor interactions that include the Nash equilibrium as a special case in the absence of information processing limitations.

Mutual Cooperation and Tolerance to Defection in the Context of Socialization: The Theoretical Model and Experimental Evidence

The study of the nature of human cooperation still contains gaps needing investigation. Previous findings reveal that socialization effectively promotes cooperation in the well-known Prisoner’s dilemma (PD) game. However, theoretical concepts fail to describe high levels of cooperation (probability higher than 50%) that were observed empirically. In this paper, we derive a symmetrical quantal response equilibrium (QRE) in PD in Markov strategies and test it against experimental data. Our results indicate that for low levels of rationality, QRE manages to describe high cooperation. In contrast, for high rationality QRE converges to the Nash equilibrium and describes low-cooperation behavior of participants. In the area of middle rationality, QRE matches the curve that represents the set of Nash equilibrium in Markov strategies. Further, we find that QRE serves as a dividing line between behavior before and after socialization, according to the experimental data. Finally, we successfully highlight the theoretically-predicted intersection of the set of Nash equilibrium for PD in Markov strategies and the QRE curve.

A Credit-Based System for Traffic Routing in Support of Vehicular Networks

Network routing has a great impact on the efficiency and reliability of the traffic network system in a real-world scenario. To date, achieving network-consistent performance is the main goal of many traffic network research studies. In this research, a mixed strategy game-theory model for network routing is proposed that discovers the optimal strategies that can be adopted by network route players in a network graph. This model has been validated by measuring the model outcomes using quantal response equilibrium (QRE) technique, which explores the players' noisy decisions by comparing the utilized optimal strategies with Nash equilibrium. The experimental results demonstrate that there is an equilibrium with a mixed strategy of a given network.

A Generalization of Quantal Response Equilibrium via Perturbed Utility

We present a tractable generalization of quantal response equilibrium via non-expected utility preferences. In particular, we introduce concave perturbed utility games in which an individual has strategy-specific utility indices that depend on the outcome of the game and an additively separable preference to randomize. The preference to randomize can be viewed as a reduced form of limited attention. Using concave perturbed utility games, we show how to enrich models based on logit best response that are common from quantal response equilibrium. First, the desire to randomize can depend on opponents’ strategies. Second, we show how to derive a nested logit best response function. Lastly, we present tractable quadratic perturbed utility games that allow complementarity.