activity
20102022
most citedEvasion Attacks against Machine Learning at Test Time

889 citations · 1.9k across the 7 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG2022★ 227 cited

Support Vector Machines under Adversarial Label Contamination

Huang Xiao, Battista Biggio, Blaine Nelson +3

Machine learning algorithms are increasingly being applied in security-related tasks such as spam and malware detection, although their security properties against deliberate attac…

cs.LG2014★ 3 cited

Security Evaluation of Support Vector Machines in Adversarial Environments

Battista Biggio, Igino Corona, Blaine Nelson +5

Support Vector Machines (SVMs) are among the most popular classification techniques adopted in security applications like malware detection, intrusion detection, and spam filtering…

cs.LG2012★ 740 cited

Poisoning Attacks against Support Vector Machines

Battista Biggio, Blaine Nelson, Pavel Laskov

We investigate a family of poisoning attacks against Support Vector Machines (SVM). Such attacks inject specially crafted training data that increases the SVM's test error. Central…

cs.LG2010★ 3 cited

Query Strategies for Evading Convex-Inducing Classifiers

Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang +4

Classifiers are often used to detect miscreant activities. We study how an adversary can systematically query a classifier to elicit information that allows the adversary to evade…

cs.LG2010★ 13 cited

Near-Optimal Evasion of Convex-Inducing Classifiers

Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang +6

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 det…