Adversarial attacks on Ai

Nowadays I has been rapidly influencing all the industries as fast as possible suggest help space was sleeping mask just buses the people who have build and investing space have curious about AI what next and how they can use it for their purpose but we are now living in the beginning stage of a i most of us now thinking that I could do everything which human can do. Assumption is now we haven't achieved the peak of AI. There are some Pessimistic point in Ai which we are using today.

We can easily confused AI systems today. For example if you take any computer vision based face detection system to detect your face, open PC system it just put a glass in your face the AI system will confuse to predict fees this cold physical attacks on AI system.

What is adversarial attack?

Adversarial attacks are manipulate that aim to machine learning performance, course error in the model performance

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Adversarial attacks against computer vision

In the beginning of this article I have mentioned about physical adversarial attacks on visual data.
In 2018, group of researchers showed that by adding sticker on stop sign good able to fool computer vision system of a self driving car to mistake it for speed limit sign.
How To Deter Adversarial Attacks In Computer Vision Models
(picture from Google)

In real case adversarial attacks against for facial recognition system in protest where demonstrators use makeup and stickers to fool the surveillance cameras powered by machine learning algorithms.

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The adversarial attack against the text to speech

Text-based adversarial attacks involve making changes in the sequence of words the piece of text article, will cause miss classification errors in machine learning algorithms. Adversarial Attacks on Deep-learning Models in Natural Language Processing

(Picture from Google)

Adversarial attacks against speech recognition systems

In a hypothetical adversarial attack, a malicious actor will carefully handle an audio file – say, a song posted on YouTube – to deem a hidden voice command. A human listener wouldn’t notice the change, but to a machine learning algorithm looking for patterns in sound waves it would be clearly audible and actionable. For example, audio adversarial attacks could be used to secretly send commands to smart speakers.

(picture from Google) Language Log » Adversarial attacks on modern speech-to-text