Questions tagged [adversarial-ml]

For questions related to adversarial machine learning, which is a branch of machine learning focused on the study of adversarial examples, which are malicious inputs designed to fool machine learning models.

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How do I decide which norm to use for placing a constraint on my adversarial perturbation?

I am performing an adversarial machine learning attack on a neural network for network traffic classification. For adding adversarial perturbations in features such as packet interarrival times and ...
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How do you perform a gradient based adversarial attack on an SVM based model?

I have an SVM currently and want to perform a gradient based attack on it similar to FGSM discussed in Explaining And Harnessing Adversarial Examples. I am struggling to actually calculate the ...
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How do I poison an SVM with manifold regularization?

I'm working on Adversarial Machine Learning, and have read multiple papers on this topic, some of them are mentioned as follows: Poisoning Attacks on SVMs: https://arxiv.org/pdf/1206.6389.pdf ...
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Can a trained object detection model deal with variations of the input?

Suppose an object detection algorithm is good at detecting objects and people when an object and person is close to a camera and upright. If the person walks farther away from the camera and is "...
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54 views

What is the relationship between robustness and adversarial machine learning?

I have been reading a lot of articles on adversarial machine learning and there are mentions of "best practices for robust machine learning". A specific example of this would be when there are ...
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1answer
97 views

What are causative and exploratory attacks in Adversarial Machine Learning?

I've been researching Adversarial Machine Learning and I know that causative attacks are when an attacker manipulates training data. An exploratory attack is when the attacker wants to find out about ...
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Isn't deep fake detection bound to fail?

Deep fakes are a growing concern: the ability to credibly alter a video may have great (negative) impacts on our society. It is so much of a concern, that the biggest tech companies launched a ...
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3answers
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In adversarial machine learning, how does an attacker have access to the test and training dataset in order to poison it?

In the field of adversarial machine learning, machine learning models are vulnerable to attacks both on the test and training data set. However, how does the attacker get access to these datasets? How ...
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1answer
62 views

In what ways can financial markets be hacked? [Algorithmic Trading]

There was a recent question on adversarial AI applications, which led me to start digging around. Here my interest is not general, but specific: What are the vulnerabilities of automated trading ...
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Is there any research on the development of attacks against artificial intelligence systems?

Is there any research on the development of attacks against artificial intelligence systems? For example, is there a way to generate a letter "A", which every human being in this world can recognize ...
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381 views

Can artificial intelligence applications be hacked? [duplicate]

Can artificial intelligence (or machine learning) applications or agents be hacked, given that they are software applications, or are all AI applications secure?
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What tools are used to deal with adversarial examples problem?

The problem of adversarial examples is known to be critical for neural networks. For example, an image classifier can be manipulated by additively superimposing a different low amplitude image to each ...
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Is artificial intelligence vulnerable to hacking?

The paper The Limitations of Deep Learning in Adversarial Settings explores how neural networks might be corrupted by an attacker who can manipulate the data set that the neural network trains with. ...