Abstract
With the technological advancement, the world is going through, at such a high pace, new challenges arise that might require new approaches. ML is, without a doubt, on the lead of technology, as it is evolving with minimal human intervention. However, new models of ML are crucial to preventing hackers from manipulating data. It is true that with new models, new gates for attacks are opened, which is why ML security must follow the same pace in evolving. In this paper, a brief introduction to ML and ML security will be discussed to give an insight on the topic, before going through a more specific point; the challenges faced by ML security. By introducing these terms, the reader will come to grasp the importance of ML security, and the huge role it plays when it comes to protecting data against hackers. However, this by no means indicates that it is flawless; on the contrary, there are flaws in the methods used in our present day, which is another topic this paper will give an insight on. Our main focus in this paper will be supervised learning due to its application in security. Algorithms used in ML models is the main gate that hackers use to breach the system, for this precise reason, engineers and experts are challenged to come with new algorithms, as we will conclude this work.
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