Modified stacking ensemble approach to detect network intrusion

Demir, Necati; Dalkılıç, Gökhan

doi:10.3906/elk-1702-279

Cited by 19 publications

(11 citation statements)

References 25 publications

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“…Not only comparing the performance of the proposed methods, but also investigating whether feature selection may further improve the results. In detail, the features chosen by our proposed method are 3,6,9,10,11,13,18,19,21,22,23,26,27,29,30,32,35,36,38, and 39, a total of 20 features. And the optimal parameters of SVM, C and γ obtained from our experiment, are (219, 28).…”

Section: Resultsmentioning

confidence: 99%

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Intrusion detection system based on improved abc algorithm with tabu search

Chen

Chang

et al. 2019

IEEJ Transactions Elec Engng

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An intrusion detection system (IDS) plays an important role in cyber security to detect network attacks. To improve the effectiveness of IDS, a new intrusion detection approach based on the support vector machine and improved Artificial Bee Colony algorithm (ABC) with Tabu Search (TS) is proposed. In the new method, to solve the problem of redundant network data and insufficient model parameters, a synchronous optimization strategy for feature selection and parameter calculation is proposed. At the same time, the idea of TS is a substitute for the greedy selection property of ABC, and two different selection probability formulas are provided in the early and later evolution of the ABC algorithm. The experimental results show that the newly proposed method performs better than other existing methods, especially in terms of detection accuracy and false negative rate. Besides, the detection rate of Probe attack and DoS attack reached 99.987 and 99.687%, respectively.

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Section: Resultsmentioning

confidence: 99%

“…To better evaluate our proposed intrusion detection model, we compare the performance of TABC-SVM with other existing methods [26][27][28] using the same KDDCup99 corrected dataset. The comparison results are shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

Intrusion detection system based on improved abc algorithm with tabu search

Chen

Chang

et al. 2019

IEEJ Transactions Elec Engng

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“…Stacking was recently proposed as one popular ensemble learning method which has been proved to be efficient and powerful in Kaggle competition, sentiment classification and many other areas. In recent years, many researchers chose the stacking method to finish their prediction work, like [19][20][21][22]. Bagging is a good way to reduce variance in the training process, since it uses repeated sampling to ensure that each subnet of bagging can cover training sample space well.…”

Section: Stacking Modelmentioning

confidence: 99%

Power Optimization for Wind Turbines Based on Stacking Model and Pitch Angle Adjustment

Luo

Sun

et al. 2020

Energies

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As we know, power optimization for wind turbines has great significance in the area of wind power generation, which means to make use of wind resources more efficiently. Especially nowadays, wind power generation has become more and more important. Generally speaking, many parameters could be optimized to enhance power output, including blade pitch angle, which is usually ignored. In this article, a stacking model composed of Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBOOST) and Light Gradient Boosting Machine (LGBM) is trained based on historical data exported from the Supervisory Control and Data Acquisition (SCADA) system for output power prediction. Then, we carry out power optimization through pitch angle adjustment based on the obtained prediction model. Our research results indicate that power output could be enhanced by adjusting pitch angle appropriately.

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“…Besides there are studies on attack detection and prevention in 5G mobile networks [17][18][19]. Demir et al proposed an intrusion detection system by combining different classification models, but their study did not have a mitigation system [20]. Patil Flowspec, which also requires BGP (RFC 5575), is an attack information sharing system between ISPs.…”

Section: Background and Related Workmentioning

confidence: 99%

An Inter-Domain Attack Mitigating Solution

Akin¹,

Bük²,

Uçar³

2020

Turk J Elec Eng & Comp Sci

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Online services on the Internet are increasing day by day, and in parallel, the number of cyber-attacks is rapidly increasing. These attacks are not always about data theft, but they can cause severe damage by denial of service attacks. Intrusion Prevention System products that many organizations use at the border of their enterprise networks are not strong enough to protect against DoS attacks. The typical way to mitigate such attacks is to get support from a service provider. However, a service provider only provides solutions for the traffic originating from itself. If the source of attack is in another ISP domain, it is possible to inform that ISP via phone or e-mail. As a result, the source of the attack is blocked by the manual intervention of the service provider whose domain hosts it. Border Gateway Protocol (BGP) based solutions are also available for automating a blocking system, but not all enterprise networks support BGP. In this research, we have developed a centralized automation solution for software defined network (SDN) environments that is capable of preventing cyber-attacks at the source of attack. This solution does not require any BGP support. Non-SDN environments can also use this attack mitigation and notification system. In the long run, we may use this system to create a national protection shield in order to mitigate Cybersecurity attacks.

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Modified stacking ensemble approach to detect network intrusion

Cited by 19 publications

References 25 publications

Intrusion detection system based on improved abc algorithm with tabu search

Intrusion detection system based on improved abc algorithm with tabu search

Power Optimization for Wind Turbines Based on Stacking Model and Pitch Angle Adjustment

An Inter-Domain Attack Mitigating Solution

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