Outlier Detection in IoT Using Generative Adversarial Network
DOI:
https://doi.org/10.32628/CSEIT206452Keywords:
IoT, Botnets, Deep Learning, GAN, OutlierAbstract
Usage of IoT products have been rapidly increased in past few years. The large number of insecure Internet of Things (IoT) devices with low computation power makes them an easy and attractive target for attackers seeking to compromise these devices and use them to create large-scale attacks. Detecting those attacks is a time consuming task and it needs to be identified shortly since it keeps on spreading. Various detection methods are used for detecting these attacks but attack mechanism keeps on evolving so a new detection approach must be introduced to detect their presence and thus blocking their spreading. In this paper a deep learning approach called GAN – Generative Adversarial Network can be used to detect this outlier and achieve 85% accuracy.
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