Prospect Pricing in Cognitive Radio Networks

Yang, Yuli; Park, Leonard T.; Mandayam, Narayan B.; Seskar, Ivan; Glass, Arnold L.; Sinha, Neha

doi:10.1109/tccn.2015.2488636

Cited by 62 publications

(33 citation statements)

References 42 publications

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“…In [15], Manuscript submitted to ACM L. Xiao et al have claimed that prospect theory can model these kinds of attacks more accurately than expected utility theory since these attacks have a similar behaviour as human beings. Furthermore, prospect theory has been applied to analyze wireless communications and traffic routing [16][17][18].…”

Section: Related Work and Motivationmentioning

confidence: 99%

“…In [16], a random access game is formulated using prospect theory to study channel access between two subjective end-users in wireless networks. In [17], Y. Yang et al have proposed to use prospect theory for resource allocation in cognitive radio networks and pricing which increases the revenue of service providers in presence of subjective users.…”

Section: Related Work and Motivationmentioning

confidence: 99%

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A Prospect Theoretic Approach for Trust Management in IoT Networks under Manipulation Attacks

Salimitari¹,

Bhattacharjee²,

Chatterjee³

et al. 2020

Preprint

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As Internet of Things (IoT) and Cyber-Physical systems become more ubiquitous and an integral part of our daily lives, it is important that we are able to trust the data aggregate from such systems. However, the interpretation of trustworthiness is contextual and varies according to the risk tolerance attitude of the concerned application and varying levels of uncertainty associated with the evidence upon which trust models act. Hence, the data integrity scoring mechanisms should have provisions to adapt to varying risk attitudes and uncertainties.In this paper, we propose a Bayesian inference model and a prospect theoretic framework for data integrity scoring that quantify the trustworthiness of data collected from IoT devices in the presence of adversaries who manipulate the data. We consider an imperfect anomaly monitoring mechanism that monitors the data being sent from each device and classifies the outcome as not compromised, compromised, and cannot be inferred. These outcomes are conceptualized as a multinomial hypothesis of a Bayesian inference model with three parameters which are then used for calculating a utility value on how reliable the aggregate data is. We use a prospect theory inspired approach to quantify this data integrity score and evaluate the trustworthiness of the aggregate data from the IoT framework. Furthermore, we also model the system using the traditionally used expected utility theory and compare the results with that obtained using prospect theory. As decisions are based on how the data is fused, we propose two measuring models-one optimistic and another conservative. The proposed framework is validated using extensive simulation experiments. We show how data integrity scores vary under a variety of system factors like attack intensity and inaccurate detection.

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Section: Related Work and Motivationmentioning

confidence: 99%

Section: Related Work and Motivationmentioning

confidence: 99%

A Prospect Theoretic Approach for Trust Management in IoT Networks under Manipulation Attacks

Salimitari¹,

Bhattacharjee²,

Chatterjee³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The corresponding model allows a user to balance the attributes, such as channel capacity, monetary cost, and interference potential. Further, in [28], the impact of end-user decision-making on pricing and management of radio resources in CRN was studied.…”

Section: Related Work and Our Focusmentioning

confidence: 99%

Dynamic Resource Sharing in 5G with LSA: Criteria‐Based Management Framework

Sadreddini

Mašek

Çavdar

et al. 2018

Wireless Communications and Mobile Computing

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Owing to a steadily increasing demand for efficient spectrum utilization as part of the fifth-generation (5G) cellular concept, it becomes crucial to revise the existing radio spectrum management techniques and provide more flexible solutions for the corresponding challenges. A new wave of spectrum policy reforms can thus be envisaged by producing a paradigm shift from static to dynamic orchestration of shared resources. The emerging Licensed Shared Access (LSA) regulatory framework enables flexible spectrum sharing between a limited number of users that access the same frequency bands, while guaranteeing better interference mitigation. In this work, an advanced user satisfaction-aware spectrum management strategy for dynamic LSA management in 5G networks is proposed to balance both the connected user satisfaction and the Mobile Network Operator (MNO) resource utilization. The approach is based on the MNO decision policy that combines both pricing and rejection rules in the implemented processes. Our study offers a classification built over several types of users, different corresponding attributes, and a number of MNO's decision scenarios. Our investigations are built on Criteria-Based Resource Management (CBRM) framework, which has been specifically designed to facilitate dynamic LSA management in 5G mobile networks. To verify the proposed model, the results (spectrum utilization, estimated Secondary User price for the future connection, and user selection methodology in case of user rejection process) are validated numerically as we yield important conclusions on the applicability of our approach, which may offer valuable guidelines for efficient radio spectrum management in highly dynamic and heterogeneous 5G environments.

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“…A seminal model capturing such deviations is prospect theory (introduced by Kahneman and Tversky in [14]), which shows that humans perceive gains, losses, and probabilities in a skewed (nonlinear) manner, typically overweighting low probabilities and underweighting high probabilities. Recent papers have studied the implications of prospect theoretic preferences in the context of CPS security and robustness [17][18][19], energy consumption decisions in the smart grid [20,21], pricing in communication networks [22], and network interdiction games [23].…”

Section: Introductionmentioning

confidence: 99%

Behavioral and Game-Theoretic Security Investments in Interdependent Systems Modeled by Attack Graphs

Abdallah

Naghizadeh²,

Hota

et al. 2020

IEEE Trans. Control Netw. Syst.

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We consider a system consisting of multiple interdependent assets, and a set of defenders, each responsible for securing a subset of the assets against an attacker. The interdependencies between the assets are captured by an attack graph, where an edge from one asset to another indicates that if the former asset is compromised, an attack can be launched on the latter asset. Each edge has an associated probability of successful attack, which can be reduced via security investments by the defenders. In such scenarios, we investigate the security investments that arise under certain features of human decision-making that have been identified in behavioral economics. In particular, humans have been shown to perceive probabilities in a nonlinear manner, typically overweighting low probabilities and underweighting high probabilities. We show that suboptimal investments can arise under such weighting in certain network topologies. We also show that pure strategy Nash equilibria exist in settings with multiple (behavioral) defenders, and study the inefficiency of the equilibrium investments by behavioral defenders compared to a centralized socially optimal solution.

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Prospect Pricing in Cognitive Radio Networks

Cited by 62 publications

References 42 publications

A Prospect Theoretic Approach for Trust Management in IoT Networks under Manipulation Attacks

A Prospect Theoretic Approach for Trust Management in IoT Networks under Manipulation Attacks

Dynamic Resource Sharing in 5G with LSA: Criteria‐Based Management Framework

Behavioral and Game-Theoretic Security Investments in Interdependent Systems Modeled by Attack Graphs

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