Refined game-theoretic approach to improve authenticity of outsourced databases

Eltayesh, Faryed; Mizouni, Rabeb; Otrok, Hadi; Shakshuki, Elhadi M.

doi:10.1007/s12652-017-0448-x

Cited by 5 publications

(2 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to reach the security goals, the proposed solution is designed to reduce the information losses and secure sensitive communication systems as well. In [27], Eltayesh et al formulated a Bayesian game to study the inaccurate, inconsistent, missing data in a database caused by the most common and dangerous cyber threats. In the same vein, the authors in [28] take into account the computational costs and misbehavior activities of malicious nodes and construct a dynamic Bayesian game to maximize the individual utility of each node in underwater acoustic sensor networks (UASNs).…”

Section: Related Workmentioning

confidence: 99%

Stackelberg Security Game for Optimizing Cybersecurity Decisions in Cloud Computing

Ait Temghart,

Marwan,

Baslam

2023

Security and Communication Networks

View full text Add to dashboard Cite

As it is difficult to cover all cybersecurity threats, an optimal defense strategy is one of the focal issues in cloud computing due to its dynamic abstraction and scalability. On this basis, Stackelberg security games (SSG) have received significant attention for their better deployment of limited security. To deal with uncertainty and incomplete information, we introduce a modified quantal response (Mod-QR) approach that incorporates bounded rationality and preference into the decision-making process. Formally, this can be done by using the quantal response equilibrium (QRE) framework to find a trade-off between the effectiveness and operating costs of cloud computing. In this case, the most effective countermeasures to defend the cloud can be viewed as a mixed strategy in which all the actions of the defender are played with a nonzero probability. This framework has been evaluated using an experimental study on MATLAB optimization toolbox to understand the behavioral aspects of cybersecurity actors and then to proactively protect cloud computing.

show abstract

Section: Related Workmentioning

confidence: 99%

Stackelberg Security Game for Optimizing Cybersecurity Decisions in Cloud Computing

Ait Temghart,

Marwan,

Baslam

2023

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…For example, Cisco approximates that the amount of IoT endpoints will hit 30 billion devices by 2030 [21]. Cloud computing [14,51,25,20] has long been the first choice of IoT manufacturers and providers for accommodating their storage and analytical needs [31] due to the unlimited and high-performance computing and storage capabilities that this technology provides. Nonetheless, the fact that cloud data-centers are usually deployed in locations that are quite far from the IoT devices entails high response time for high-end systems due to the long-distance and multi-hops communications.…”

Section: Introduction 11 Motivation and Problem Statementmentioning

confidence: 99%

FoGMatch. (c2019)

Arisdakessian¹

View full text Add to dashboard Cite

Cloud computing has long been the main backbone that IoT devices rely on to accommodate their storage and analytical needs. However, the fact that cloud systems are often deployed in locations that are quite far from the IoT devices and the emergence of delay-critical IoT applications (e.g., health monitoring, real-time machine learning, etc.) urged the need for extending the cloud architecture to support delay-critical services. In this context, the notion of fog computing has been projected to furnish data analytics and decision-making closer to the IoT devices. Given that fog nodes are characterized by small resource capabilities compared to the cloud systems, the problem of matching the IoT services to the appropriate fog nodes while guaranteeing minimal delay for the IoT services and efficient resource utilization on the fog nodes becomes quite challenging. Several approaches have been proposed in the literature in an attempt to address this challenge. The main limitation of these approaches is that they address the scheduling problem from one side point of view, i.e., either fog nodes or IoT devices. This results in an unfair situation wherein the needs of one of the parties are ignored in the scheduling process. To address this problem, we propose in this paper a multi-criteria intelligent IoT scheduling approach in fog computing environments using matching game theory. Our solution consists of (1) two optimization problems, one for the IoT devices and one for the fog nodes, (2) preference functions for both the IoT and fog layers to help them rank each other on the basis of several criteria such latency and resource utilization, and (3) centralized and distributed intelligent scheduling algorithms that consider the preferences of both the fog and IoT layers to improve the performance of the overall IoT ecosystem. Simulation results reveal that our solution outperforms the two common scheduling algorithms (i.e., Min-Min and Max-Min) in terms of IoT services execution makespan, fog nodes resource utilization efficiency and execution time.

show abstract

A game-theoretic approach for channel security against active time-varying attacks based on artificial noise

Chen

Qin

et al. 2019

J Ambient Intell Human Comput

View full text Add to dashboard Cite

Refined game-theoretic approach to improve authenticity of outsourced databases

Cited by 5 publications

References 25 publications

Stackelberg Security Game for Optimizing Cybersecurity Decisions in Cloud Computing

Stackelberg Security Game for Optimizing Cybersecurity Decisions in Cloud Computing

FoGMatch. (c2019)

A game-theoretic approach for channel security against active time-varying attacks based on artificial noise

Contact Info

Product

Resources

About