scholarly journals GLIDE: A Game Theory and Data-Driven Mimicking Linkage Intrusion Detection for Edge Computing Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
Qianmu Li ◽  
Jun Hou ◽  
Shunmei Meng ◽  
Huaqiu Long
Keyword(s):  
Game Theory ◽  
Intrusion Detection ◽  
Real Time ◽  
Dynamic Game ◽  
Complex Problem ◽  
Computing Methods ◽  
Edge Computing ◽  
Data Driven ◽  
Active Defence ◽  
The Game Theory

The real-time and high-continuity requirements of the edge computing network gain more and more attention because of its active defence problem, that is, a data-driven complex problem. Due to the dual constraints of the hybrid feature of edge computing networks and the uncertainty of new attack features, implementing active defence measures such as detection, evasion, trap, and control is essential for the security protection of edge computing networks with high real-time and continuity requirements. The basic idea of safe active defence is to make the defence gain more significant than the attack loss. To encounter the new attacks with uncertain features introduced by the ubiquitous transmission network in the edge computing network, this paper investigates the attack behaviour and presents an attack-defence mechanism based on game theory. Based on the idea of dynamic intrusion detection, we utilize the game theory in the field of edge computing network and suggest a data-driven mimicry intrusion detection game model-based technique called GLIDE. The game income of participants and utility computing methods under different deployment strategies are analysed in detail. According to the proof analysis of the Nash equilibrium condition in the model, the contradictory dynamic game relationship is described. Therefore, the optimal deployment strategy of the multiredundancy edge computing terminal intrusion detection service in the edge computing network is obtained by solving the game balance point. The detection probability of the edge computing network for network attacks is improved, and the cost of intrusion detection of the edge computing network is reduced.

scholarly journals An edge based hybrid intrusion detection framework for mobile edge computing

2021 ◽  
Author(s):  
Ashish Singh ◽  
Kakali Chatterjee ◽  
Suresh Chandra Satapathy
Keyword(s):  
Intrusion Detection ◽  
Real Time ◽  
Network Architecture ◽  
Denial Of Service ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Hybrid Detection ◽  
Game Theoretical Approach ◽  
Improved Performance ◽  
Edge Based

AbstractThe Mobile Edge Computing (MEC) model attracts more users to its services due to its characteristics and rapid delivery approach. This network architecture capability enables users to access the information from the edge of the network. But, the security of this edge network architecture is a big challenge. All the MEC services are available in a shared manner and accessed by users via the Internet. Attacks like the user to root, remote login, Denial of Service (DoS), snooping, port scanning, etc., can be possible in this computing environment due to Internet-based remote service. Intrusion detection is an approach to protect the network by detecting attacks. Existing detection models can detect only the known attacks and the efficiency for monitoring the real-time network traffic is low. The existing intrusion detection solutions cannot identify new unknown attacks. Hence, there is a need of an Edge-based Hybrid Intrusion Detection Framework (EHIDF) that not only detects known attacks but also capable of detecting unknown attacks in real time with low False Alarm Rate (FAR). This paper aims to propose an EHIDF which is mainly considered the Machine Learning (ML) approach for detecting intrusive traffics in the MEC environment. The proposed framework consists of three intrusion detection modules with three different classifiers. The Signature Detection Module (SDM) uses a C4.5 classifier, Anomaly Detection Module (ADM) uses Naive-based classifier, and Hybrid Detection Module (HDM) uses the Meta-AdaboostM1 algorithm. The developed EHIDF can solve the present detection problems by detecting new unknown attacks with low FAR. The implementation results illustrate that EHIDF accuracy is 90.25% and FAR is 1.1%. These results are compared with previous works and found improved performance. The accuracy is improved up to 10.78% and FAR is reduced up to 93%. A game-theoretical approach is also discussed to analyze the security strength of the proposed framework.

scholarly journals Multi-Robot Searching using Game-Theory Based Approach

10.5772/6232 ◽  
2008 ◽  
Vol 5 (4) ◽  
pp. 44 ◽  
Author(s):  
Yan Meng
Keyword(s):  
Game Theory ◽  
Dynamic Programming ◽  
Utility Function ◽  
Real Time ◽  
Dynamic Environment ◽  
Equilibrium Solutions ◽  
Strategy Equilibrium ◽  
The Game Theory ◽  
Target Searching ◽  
Multi Robot

This paper proposes a game-theory based approach in a multi–target searching using a multi-robot system in a dynamic environment. It is assumed that a rough priori probability map of the targets' distribution within the environment is given. To consider the interaction between the robots, a dynamic-programming equation is proposed to estimate the utility function for each robot. Based on this utility function, a cooperative nonzero-sum game is generated, where both pure Nash Equilibrium and mixed-strategy Equilibrium solutions are presented to achieve an optimal overall robot behaviors. A special consideration has been taken to improve the real-time performance of the game-theory based approach. Several mechanisms, such as event-driven discretization, one-step dynamic programming, and decision buffer, have been proposed to reduce the computational complexity. The main advantage of the algorithm lies in its real-time capabilities whilst being efficient and robust to dynamic environments.

Intrusion Detection Based on the Game Theory

2021 ◽  
Author(s):  
Yuqing Cheng ◽  
HaiYan Fu ◽  
Xuechao Sun
Keyword(s):  
Game Theory ◽  
Intrusion Detection ◽  
The Game Theory

Model of Intrusion Detection Based on the Game Theory

2013 ◽  
Vol 347-350 ◽  
pp. 3971-3974 ◽  
Author(s):  
Heng Xiao ◽  
Cao Fang Long
Keyword(s):  
Game Theory ◽  
Nash Equilibrium ◽  
Network Security ◽  
Intrusion Detection ◽  
Working Group ◽  
Ad Hoc ◽  
Game Model ◽  
The Game Theory ◽  
Network Application ◽  
Stage Game

With the development of network application, network security is facing greater pressure. Based on the characteristics of intrusion detection in the wireless network of the Ad hoc working group, the article introduces the game theory, proposes a game model of network security, concluds the Nash equilibrium in the stage game, repeats game, the pareto Nash equilibrium, more attack both income and payment, so that they get the best choice.

scholarly journals Robust Nash Dynamic Game Strategy for User Cooperation Energy Efficiency in Wireless Cellular Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Shuhuan Wen ◽  
Baozhu Hu ◽  
Ahmad B. Rad ◽  
Xinbin Li ◽  
Huibin Lu ◽  
...  
Keyword(s):  
Game Theory ◽  
Energy Efficiency ◽  
Imperfect Information ◽  
Dynamic Game ◽  
Base Station ◽  
Mobile Users ◽  
User Cooperation ◽  
Decode And Forward ◽  
Data Rates ◽  
The Game Theory

Recently, there is an emerging trend of addressing “energy efficiency” aspect of wireless communications. It has been shown that cooperating users relay each other's information to improve data rates. The energy is limited in the wireless cellular network, but the mobile users refuse to relay. This paper presents an approach that encourages user cooperation in order to improve the energy efficiency. The game theory is an efficient method to solve such conflicts. We present a cellular framework in which two mobile users, who desire to communicate with a common base station, may cooperate via decode-and-forward relaying. In the case of imperfect information assumption, cooperative Nash dynamic game is used between the two users' cooperation to tackle the decision making problems: whether to cooperate and how to cooperate in wireless networks. The scheme based on “cooperative game theory” can achieve general pareto-optimal performance for cooperative games, and thus, maximize the entire system payoff while maintaining fairness.

scholarly journals Performance Evaluation of Game Theory Based Efficient Task Scheduling For Edge Computing

2020 ◽  
Vol 2 (1) ◽  
pp. 50-61
Author(s):  
Dr. Smys S. ◽  
Dr. Ranganathan G.
Keyword(s):  
Game Theory ◽  
Performance Evaluation ◽  
Task Scheduling ◽  
Waiting Time ◽  
Resource Availability ◽  
Edge Computing ◽  
Theory Approach ◽  
User Perception ◽  
The Game Theory ◽  
Multiple Issues

The edge paradigm that is intended as prominent computing due to its low computation latencies faces multiple issues and challenges due to the restrictions in the computing capabilities and its resource availability especially in the huge populace scenarios. To examine the problems faced during the task scheduling when the edge computing is called up by multiple users at time, the paper puts forward the game theory approach. Utilizing the game theory strategy the paper puts forth the a novel multi-tasking scheduling in the edge computing from the user perception developing an algorithm taking into consideration the consistency of the stable tasks. The analysis of the proposed algorithm used in the allocation of the tasks is done on terms of average time consumed for the execution of the task and the waiting time. The results acquired showed that the proposed method provides a maximized throughput, minimizing the waiting time compared to the conventional methods used in optimizing the parameters of scheduling.

scholarly journals Computing Unloading Strategy of Massive Internet of Things Devices Based on Game Theory in Mobile Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xinhui Ding ◽  
Wenjuan Zhang
Keyword(s):  
Game Theory ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Transmission Rate ◽  
Mobile User ◽  
Edge Computing ◽  
Communication Model ◽  
Mobile Edge Computing ◽  
Computing Model ◽  
The Game Theory

Due to the limited computing resources of the mobile edge computing (MEC) server, a massive Internet of things device computing unloading strategy using game theory in mobile edge computing is proposed. First of all, in order to make full use of the massive local Internet of things equipment resources, a new MEC system computing an unloading system model based on device-to-device (D2D) communication is designed and modeled, including communication model, task model, and computing model. Then, by using the utility function, the parameters are substituted into it, and the optimization problem with the goal of maximizing the number of CPU cycles and minimizing the energy consumption is constructed with the unloading strategy and power as constraints. Finally, the game theory is used to solve the problem of computing offload. Based on the proposed beneficial task offload theory, combined with the mobile user device computing offload task amount, transmission rate, idle device performance, and other factors, the computing offload scheme suitable for their own situation is selected. The simulation results show that the proposed scheme has better convergence characteristics, and, compared with other schemes, the proposed scheme significantly improves the amount of data transmission and reduces the energy consumption of the task.

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