Intrusion Detection and Prevention Systems in Wireless Networks

In the process of applying deep learning to intrusion detection, in order to ensure the recognition accuracy of the model, a large number of data sets need to be classified manually, and then the model training is carried out after labeling. In practice, the efficiency of manual label designation for enough data sets is extremely low. This paper aims at the experimental data set encountered in the intrusion detection of intelligent network vehicles The problem of classification difficulty is proposed, and a method of vehicle intrusion detection based on Generative Adversarial Networks is proposed. Firstly, the vehicle driving data is collected, the collected data are put into the Generative Adversarial Networks for data classification, and the data set after training classification is used for model training. The experimental results show that the data classification can effectively improve work efficiency and reduce the resource overhead, which is practical in the application field.

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Intrusion Detection of Vehicle Based on Generative Adversarial Networks

Liu

Wang

Zhao

2021

J. Phys.: Conf. Ser.

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Exploring Wi-Fi Security Challenges and Proposing Solutions: The case of Afghanistan

Mosawi,

Qasimi,

Wadeed

et al. 2023

EJECE

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Wireless networks are the most developed progress than other technologies because of cost-effective, flexibility, mobility, and easy deployment. Despite these benefits, wireless networks suffer from different types of challenges and vulnerabilities. During past decades, IEEE, IETF and, Wi-Fi Alliance Institute developed a lot of wireless security protocols including WEP, WPA, WPA2, WPA3, 802.1x standards. Besides, these protocols bring the most solutions for wireless security challenges, still, these protocols are vulnerable against the different types of attacks and threats (Dictionary attacks and Rogue access points). Thus, in this paper after doing a survey and finding the challenges in the case of Afghanistan, I propose solutions regarding specific challenges. The proposed solutions are Kismet and Snort for rogue-AP and dictionary attack detection and prevention. Since these proposed solutions are implemented in the least cost due to open source and free attitude, the proposed solutions are implementable in every Wi-Fi environment in Afghanistan.

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Intrusion Detection and Prevention Systems in Wireless Networks

Cited by 2 publications

References 21 publications

Intrusion Detection of Vehicle Based on Generative Adversarial Networks

Intrusion Detection of Vehicle Based on Generative Adversarial Networks

Exploring Wi-Fi Security Challenges and Proposing Solutions: The case of Afghanistan

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