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Adversarial Attacks

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Version vom 2. Mai 2019, 10:44 Uhr von Dawid (Diskussion | Beiträge) (Videolink hinzugefügt)

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WHITE BOX ATTACKS


Untargeted Adversarial Attacks

Adversarial attacks that just want your model to be confused and predict a wrong class are called Untargeted Adversarial Attacks.

  • nicht zielgerichtet

Fast Gradient Sign Method(FGSM)

FGSM is a single step attack, ie.. the perturbation is added in a single step instead of adding it over a loop (Iterative attack).

Basic Iterative Method

Störung, anstatt in einem einzelnen Schritt in mehrere kleinen Schrittgrößen anwenden

Iterative Least-Likely Class Method

ein Bild erstellen, welches in der Vorhersage den niedrigsten Score trägt


Targeted Adversarial Attacks

Attacks which compel the model to predict a (wrong) desired output are called Targeted Adversarial attacks

  • zielgerichtet

(Un-)Targeted Adversarial Attacks

kann beides...

Projected Gradient Descent (PGD)

Eine Störung finden die den Verlust eines Modells bei einer bestimmten Eingabe maximiert:

WHITE/BLACK BOX ATTACKS

on voice (ASR)

Psychoacoustic Hiding (Attacking Speech Recognition)


BLACK BOX ATTACKS


on computer vision

propose zeroth order optimization (ZOO)

Black-Box Attacks using Adversarial Samples

  • a technique that uses the victim model as an oracle to label a synthetic training set for the substitute, so the attacker need not even collect a training set to mount the attack

new Tesla Hack


on voice (ASR)

hidden voice commands

BLACK BOX / WHITE BOX ATTACKS

on voice (ASR)

Psychoacoustic Hiding (Attacking Speech Recognition)


on written text (NLP)

paraphrasing attacks


Anti Surveillance

http://dismagazine.com/dystopia/evolved-lifestyles/8115/anti-surveillance-how-to-hide-from-machines/

How to Disappear Completely

https://www.youtube.com/watch?v=LOulCAz4S0M talk by Lilly Ryan at linux.conf.au 2019 — Christchurch, New Zealand


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