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.

Filter by
Sorted by
Tagged with
-1
votes
0answers
41 views

How to fool a CNN Feature extraction network?

Are Universal Adversarial Perturbations able to fool a neural network which performs Feature Detection?
1
vote
1answer
49 views

Can the addition of unnoticeable noise to images be used to create subliminals?

I was reading this report: https://www.theverge.com/2017/4/12/15271874/ai-adversarial-images-fooling-attacks-artificial-intelligence Researchers used noise to trick machine learning algorithms to ...
1
vote
0answers
17 views

How can transition models in RL be trained adversarially?

To give a little background, I've been reading the COBRA paper, and I've reached the section that talks about the exploration policy, in particular. We figure that a uniformly random policy won't do ...
2
votes
1answer
30 views

Adversarial Q Learning should use the same Q Table?

I'm creating a RF Q-Learning agent for a two player fully-observable board game and wondered, if I was to train the Q Table using adversarial training, should I let both 'players' use, and update, the ...
1
vote
0answers
19 views

To perform a white box adversarial attack, would the use of a numerical gradient suffice?

I am trying to perform a white box attack on a model. Would it be possible to simply use the numerical gradient of the output wrt input directly rather than computing each subgradient of the network ...
1
vote
0answers
9 views

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 ...
0
votes
1answer
37 views

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 ...
3
votes
1answer
91 views

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 ...
2
votes
1answer
48 views

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 "...
5
votes
1answer
57 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 ...
2
votes
1answer
160 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 ...
5
votes
1answer
86 views

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 ...
2
votes
3answers
69 views

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 ...
2
votes
1answer
74 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 ...
24
votes
8answers
4k views

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 ...
5
votes
3answers
399 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?
9
votes
1answer
379 views

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 ...
30
votes
9answers
5k views

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. ...