Poison Attacks Against Machine Learning - Slashdot - 1 views
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Support Vector Machines (SVMs) are fairly simple but powerful machine learning systems. They learn from data and are usually trained before being deployed.
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In many cases they need to continue to learn as they do the job and this raised the possibility of feeding it with data that causes it to make bad decisions. Three researchers have recently demonstrated how to do this with the minimum poisoned data to maximum effect. What they discovered is that their method was capable of having a surprisingly large impact on the performance of the SVMs tested. They also point out that it could be possible to direct the induced errors so as to produce particular types of error.
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http://arxiv.org/abs/1206.6389v2 for Guido; an interesting example of "takeover" research