Adversarial Attacks and Defences: A Survey

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When AI Gets Tricked: Adversarial Attacks and Simple Defences

Today many apps use deep learning to do hard jobs fast, from photos to voice.
But tiny, almost invisible changes in input can make a model give the wrong answer — these are called adversarial attacks.
They look harmless but they can make systems misclassify things, and that can break services or risk our security.
Researchers try to make AI more robustness, yet real fixes that work everywhere are rare.
Some methods help in certain cases, other methods fail when the trick is changed a little.
The upshot: powerful AI is useful, yet still fragile, and attackers might exploit that if they want.
It means designers need to test models more, watch for sneaky inputs, and build layers of protection.
We can’t stop every trick now, but simple checks and careful design reduce chances of surprise.
Want to know more? Keep asking, stay curious, and hold apps to higher safety.
A small change in a picture can change a big decision, so people should care.