Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks

Shamshirband, Shahaboddin; Patel, Ahmed; Anuar, Nor Badrul; Kiah, Miss Laiha Mat; Abraham, Ajith

doi:10.1016/j.engappai.2014.02.001

Cited by 154 publications

(67 citation statements)

References 51 publications

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“…Despite the benefits offered by the use of cloud computing, it could be exploited or targeted by cybercriminals, including state-sponsored actors (see [3]). This is not surprising, as popular consumer technologies such as wireless sensor networks have also been reportedly targeted [4,5]. One common form of attacks targeting cloud computing is distributed denial of service (DDoS) attacks [6,7], and we refer to interested reader to [8] for other cloud-related security and privacy issues.…”

Section: Introductionmentioning

confidence: 99%

Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing

Osanaiye

Cai

Choo

et al. 2016

J Wireless Com Network

269

136

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Widespread adoption of cloud computing has increased the attractiveness of such services to cybercriminals. Distributed denial of service (DDoS) attacks targeting the cloud's bandwidth, services and resources to render the cloud unavailable to both cloud providers, and users are a common form of attacks. In recent times, feature selection has been identified as a pre-processing phase in cloud DDoS attack defence which can potentially increase classification accuracy and reduce computational complexity by identifying important features from the original dataset during supervised learning. In this work, we propose an ensemble-based multi-filter feature selection method that combines the output of four filter methods to achieve an optimum selection. We then perform an extensive experimental evaluation of our proposed method using intrusion detection benchmark dataset, NSL-KDD and decision tree classifier. The findings show that our proposed method can effectively reduce the number of features from 41 to 13 and has a high detection rate and classification accuracy when compared to other classification techniques.

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Section: Introductionmentioning

confidence: 99%

Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing

Osanaiye

Cai

Choo

et al. 2016

J Wireless Com Network

269

136

View full text Add to dashboard Cite

show abstract

“…An attacker attempts to breach security of the system to disrupt or cause damage to network services, whereas a defender obtains appropriate measures to enhance the system security design or response. In this case intrusion response systems (IRS) are necessary because intrusion prevention systems are unfeasible [17,18]. In previous work [19] game play method of finding the intruder were proposed based on the response and recovery method.…”

Section: Problem Definitionmentioning

confidence: 99%

Optimal Game Theory for Network Security using IPDRS Engine

P¹,

Nadu²

2015

International Journal of Advanced Research in Computer and Comm

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Abstract:With the tremendous growth of network technology, network attackers are also rationally increased to disrupt the activities and hacking the data from the network users by the intruder. To provide the security from the intruder is most important one. Many researchers were proposed a different approach for providing security they does not tackle the problem, it leads an untruthful in the network. In existing system they propose a game based intrusion request and response process by game play of header node to access the data by their correct play, from this if the real header play it in wrong method means all the client user under the header also suffer from the access of the data. To tackle this issue we enhanced the game theory based on the individual play in the network to avoid the suffering of misplayed game played by the header using the IPDRS Engine.

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“…The owner assumes that the (attackers) players know only their own payoff of accessing the data [18]. Furthermore, to be more efficient in responding to the noticing intrusion, it should be essential to trace down the attack source to avoid the denial of service to authorized users.…”

Section: (B) Irs Using Fuzzy Gamementioning

confidence: 99%

Survey on Automated Intrusion Response System Using Game Theory

Anuvarsha.¹,

Rajeshkumar²

2014

International Journal of Advanced Research in Computer and Comm

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Abstract:With the increasing number of network technology, intruders are also rationally increased. To provide the security to the network from the intruders is one of the vital one, this survey presents Intrusion Response System to handle the intruders by request and response process by using Game theory. This survey provides a better understanding of the different research approaches by applying game theory for the Automated Intrusion Response System (AIRS). It focuses on fictitious play, fuzzy game, and zero-sum game for automatic response system to the intruders. This survey helps to the researchers in various fields to develop game-theoretic solutions in current and emerging security problems in network security.

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Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks

Cited by 154 publications

References 51 publications

Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing

Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing

Optimal Game Theory for Network Security using IPDRS Engine

Survey on Automated Intrusion Response System Using Game Theory

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