Title: ADVANCEMENT OF ATTACK AND DEFENSE TECHNIQUES IN ADVERSARIAL MACHINELEARNING
Abstract: Machine Learning, these days, is helping make decisions about real-world problems and its use in almost every
field signifies that it is quite effective. But, it is prone to some serious threats which are known as adversarial
examples and, using these adversarial examples to attack machine learning is called adversarial machine
learning. Adversaries have started to develop various methods to infiltrate machine learning models and modify
them such that the models start working for their benefit or start behaving absurdly. Adversarial machine
learning poses a grave threat to all the sectors in which machine learning is being used. Here, the vulnerabilities
in machine learning models, major types of attacks that avail these vulnerabilities to weaken the models using
adversarial examples and,defenses against these adversarial attacks are discussed.
Publication Year: 2020
Publication Date: 2020-01-01
Language: en
Type: article
Access and Citation
Cited By Count: 1
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