Near-Optimal Evasion of Convex-Inducing Classifiers

Details Near-Optimal Evasion of Convex-Inducing Classifiers Near-Optimal Evasion of Convex-Inducing Classifiers

2010-03-14

arxiv.org/abs/1003.2751v1

Computer Science

Learning

8 pages; to appear at AISTATS'2010

Scientific paper

Classifiers are often used to detect miscreant activities. We study how an adversary can efficiently query a classifier to elicit information that allows the adversary to evade detection at near-minimal cost. We generalize results of Lowd and Meek (2005) to convex-inducing classifiers. We present algorithms that construct undetected instances of near-minimal cost using only polynomially many queries in the dimension of the space and without reverse engineering the decision boundary.

Affiliated with

Also associated with

No associations

Rating

Near-Optimal Evasion of Convex-Inducing Classifiers does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Near-Optimal Evasion of Convex-Inducing Classifiers, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Near-Optimal Evasion of Convex-Inducing Classifiers will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-443383