Backdoors in Machine Learning Models
Clean-Label Attacks
One disadvantage of the approach described in this article is that the manipulations are easy to detect. First, the trigger could be found in the training examples. Second, the training examples with triggers have an incorrect label, the one that the attacker wants the model to provide as a response when the trigger is present. Some more advanced approaches might try to hide the manipulations. In clean-label attacks, only the image data is manipulated. The labels remain unchanged so that the label still matches the image. And the image data can even be manipulated in a way that it is imperceptible to the people reviewing the data set.
To inject a backdoor into a model, you do not necessarily need to manipulate an existing data set or create a new, manipulated, labeled data set. Instead, all you need to do is post manipulated images at certain places on the Internet, where they will presumably be accessed by someone at some point, in order to create a model from them. In this case, the images would be labeled by other people (for example, via crowdsourcing) who would not notice the manipulations.
Conclusions
Machine learning and smart systems are currently making giant inroads into every area of daily life. The potential is enormous, and impressive results are repeatedly achieved. But progress always goes hand in hand with new risks. Although the security properties of machine learning models have now been far more thoroughly investigated than a few years ago, still very little is known about them. The AI community will need to develop more effective protections against data poisoning attacks before we can truly trust our smart systems.
Infos
- Szegedy, Christian, et al. "Intriguing properties of neural networks." arXiv:1312.6199, Dec. 2013
- Athalye, Anish, Logan Engstrom, Andrew Ilyas, and Kevin Kwok. "Synthesizing robust adversarial examples." Proceedings of the 35th International Conference on Machine Learning (2018), PMLR 80:284-293
- Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. "Explaining and harnessing adversarial examples." arXiv:1412.6572 [stat.ML], Dec. 2014
- Fredrikson, Matt, Somesh Jha, and Thomas Ristenpart. "Model inversion attacks that exploit confidence information and basic countermeasures." Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (2015), pg. 1322-1333
- Amazon's Mechanical Turk: https://www.mturk.com
- Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg. "Badnets: Identifying vulnerabilities in the machine learning model supply chain." arXiv:1708.06733 [cs.CR], Aug. 2017
- Deng, L. "The MNIST Database of Handwritten Digit Images for Machine Learning Research." IEEE Signal Processing Magazine, 2012;29(6):141-142
- Jupyter Notebook: https://github.com/daniel-e/secml/blob/master/examples/backdoors/mnist.ipynb
« Previous 1 2 3 4
Buy this article as PDF
(incl. VAT)
Buy Linux Magazine
Subscribe to our Linux Newsletters
Find Linux and Open Source Jobs
Subscribe to our ADMIN Newsletters
Support Our Work
Linux Magazine content is made possible with support from readers like you. Please consider contributing when you’ve found an article to be beneficial.
News
-
TUXEDO Computers Unveils Linux Laptop Featuring AMD Ryzen CPU
This latest release is the first laptop to include the new CPU from Ryzen and Linux preinstalled.
-
XZ Gets the All-Clear
The back door xz vulnerability has been officially reverted for Fedora 40 and versions 38 and 39 were never affected.
-
Canonical Collaborates with Qualcomm on New Venture
This new joint effort is geared toward bringing Ubuntu and Ubuntu Core to Qualcomm-powered devices.
-
Kodi 21.0 Open-Source Entertainment Hub Released
After a year of development, the award-winning Kodi cross-platform, media center software is now available with many new additions and improvements.
-
Linux Usage Increases in Two Key Areas
If market share is your thing, you'll be happy to know that Linux is on the rise in two areas that, if they keep climbing, could have serious meaning for Linux's future.
-
Vulnerability Discovered in xz Libraries
An urgent alert for Fedora 40 has been posted and users should pay attention.
-
Canonical Bumps LTS Support to 12 years
If you're worried that your Ubuntu LTS release won't be supported long enough to last, Canonical has a surprise for you in the form of 12 years of security coverage.
-
Fedora 40 Beta Released Soon
With the official release of Fedora 40 coming in April, it's almost time to download the beta and see what's new.
-
New Pentesting Distribution to Compete with Kali Linux
SnoopGod is now available for your testing needs
-
Juno Computers Launches Another Linux Laptop
If you're looking for a powerhouse laptop that runs Ubuntu, the Juno Computers Neptune 17 v6 should be on your radar.