A Cumulative Prospect Theory Based Counterterrorism Resource Allocation Method under Interval Values

Ge, Bingfeng; Zhang, Xiaoxiong; Zhou, Xiaolei; Yue-jin, Tan

doi:10.1007/s11518-019-5423-y

Cited by 7 publications

(5 citation statements)

References 32 publications

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“…Different from the expected utility theory focus on the outcome, CPT gives weight parameters based on risk attitude and calculates the cumulative prospect value. Several studies have investigated optimal resource allocation for the defender based on the attack–defense game and cumulative prospect value (Gao & Yan, 2021; Ge, Zhang, Zhou, & Tan, 2019; Peng, Wu, Sun, & Wu, 2020; Xiaoxiong, Kun, Hui, & Guoquan, 2020). The CPT applied in those studies could well‐adapt to the risky and uncertain behavior of the defender.…”

Section: Case Studies and Discussionmentioning

confidence: 99%

Multistage Attack–Defense Graph Game Analysis for Protection Resources Allocation Optimization Against Cyber Attacks Considering Rationality Evolution

Shao

2021

Risk Analysis

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Cyber vulnerabilities become ever more critical in modern industrial systems since the attacker can utilize the vulnerabilities to degrade their performance or even cause disasters. In 2015, a series of sequential and well‐organized cyber attacks intruded into the Ukrainian power grid, compromised access to the control system, and interrupted the power supply system, finally causing a widespread power outage. To assist the defender, e.g., power grid operator, to allocate protection resources against cyber attacks, existing studies have devoted considerable efforts to risk and reliability analysis and interaction analysis using game theory. The defender's protection strategy includes preevent defense strategy and postevent repair strategy. The strategy spaces of both players were static in previous studies. However, facing Ukrainian‐style cyber attacks, the strategy spaces could variate during the attacker–defender confrontation. In other words, the vulnerability compromised by the attacker in one stage could expose the subsequential vulnerabilities, leading to the change of strategy spaces. In this work, a multistage attack–defense graph game model is proposed to assist the defender in allocating protection resources optimally against sequential cyber attacks during multiple stages. In addition, we consider the existence of the rationality evolution of the attacker, which mainly results from asymmetric information, capacity limitation, and progressive learning during the confrontation. Compared to previous studies based on static strategy spaces and static rationalities, our model is more practical and effective in dealing with Ukrainian‐style cyber attacks. The simulation results show the superiority of our approach, and some notable observations and practical suggestions are summarized for the defender.

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Section: Case Studies and Discussionmentioning

confidence: 99%

Multistage Attack–Defense Graph Game Analysis for Protection Resources Allocation Optimization Against Cyber Attacks Considering Rationality Evolution

Shao

2021

Risk Analysis

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“…Note that as more than one attribute is considered, different outcomes on each attribute need to be normalized before aggregation [28]. Therefore, the following process is carried out to normalize each attribute value as where v * k = max m∈M, n∈N {|v mnk |}.…”

Section: Prospect Value Calculationmentioning

confidence: 99%

“…Such a problem is neither the major concern in our study, nor a key factor for our emergency decision-making model. In practice, however, these values can be determined by expert elicitation, historical statistics, or experiments [28].…”

Section: Basic Modelmentioning

confidence: 99%

A cumulative prospect theory-based method for group medical emergency decision-making with interval uncertainty

Sun

Zhang

et al. 2022

BMC Med Inform Decis Mak

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Background An emergency response to a medical situation is generally considered to be a risk decision-making problem. When an emergency event occurs, it makes sense to take into account more than one decision maker’s opinions and psychological behaviors. The existing research tends to ignore these multidimensional aspects. To fill this literature gap, we propose a multi-attribute model. Methods The model is based on cumulative prospect theory (CPT), considering multiple experts’ psychological factors. By not assuming full rationality, we extend existing models to allow multiple experts’ risk preferences to be incorporated into the decision-making process in the case of an emergency. Then, traditional CPT is extended by allowing for multiple attributes. In addition, rather than using crisp data, interval values are adopted to tackle the usual uncertainties in reality. Results The multi-attribute CPT based model proposed can deal with the selection of potential emergency alternatives. The model incorporates interval values to allow more uncertainty and the comparative studies show that the optimal solution changes under different scenarios. Conclusions Our illustrative example and comparative study show that considering multiple experts and multiple attributes is more reasonable, especially in complicated situations under an emergency. In addition, decision-makers’ risk preferences highly affect the selection outcomes, highlighting their importance in the medical decision-making process. Our proposed model can be applied to similar fields with appropriate modifications.

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“…Prospect theory, proposed by Kahneman [23] and Tversky [24], effectively captures the psychological behavioral characteristics of decision makers, such as their aversion to losses, distortion in probability judgments, and risk aversion, and explains the phenomena that cannot be accounted for by expected utility theory [25]. Scholars have further developed prospect theory [15,[26][27][28][29][30] to enhance its applicability across various domains, including financial investment [28], supplier evaluation [30], emergency decision-making related to gas explosions [31], geological disasters [15], and incidents like oil pipeline explosion accidents [32]. However, most existing prospect theories assume certain preferences on the part of decision-makers without fully considering the individual risk preferences of different decision-makers.…”

Section: Introductionmentioning

confidence: 99%

An Emergency Decision-Making Method for Coal Spontaneous Combustion Based on Improved Prospect Theory

Zeng,

Jing,

Zhu

2024

Processes

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In response to the limited available information during the initial stages of coal spontaneous combustion and the influence of decision makers’ risk preferences on decision-making, this paper proposes an emergency decision-making method for coal spontaneous combustion that integrates grey correlation degree and TOPSIS with an enhanced prospect theory. Firstly, a normalized weighted evaluation matrix is established for the emergency response plan of coal spontaneous combustion, and the entropy method is utilized to determine the weights of various indexes. Then, considering the imperfect rationality of decision makers and their diverse individual risk preferences, they are categorized into three types: risk-seeking type, risk-neutral type, and risk-averse type. The corresponding risk coefficients are determined based on these different types. Positive and negative ideal solutions are taken as reference points, and matrices representing gains and losses are constructed. The grey correlation degree is introduced to calculate both positive and negative prospect values based on these matrices. Moreover, the prospect value for each emergency response plan is calculated, respectively, based on different types of decision makers, and the entropy method is used to assign weights to decision makers according to their respective risk preferences. Consequently, based on these prospect values and the weights, comprehensive prospect values for each emergency response plan are obtained and ranked to identify the optimal one. Finally, in order to validate the effectiveness of our proposed approach, a case study is conducted, and the results obtained from this case study are discussed and compared with those from other methods.

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A Cumulative Prospect Theory Based Counterterrorism Resource Allocation Method under Interval Values

Cited by 7 publications

References 32 publications

Multistage Attack–Defense Graph Game Analysis for Protection Resources Allocation Optimization Against Cyber Attacks Considering Rationality Evolution

Multistage Attack–Defense Graph Game Analysis for Protection Resources Allocation Optimization Against Cyber Attacks Considering Rationality Evolution

A cumulative prospect theory-based method for group medical emergency decision-making with interval uncertainty

An Emergency Decision-Making Method for Coal Spontaneous Combustion Based on Improved Prospect Theory

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