Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Security Evaluation of Support Vector Machines in Adversarial
  Environments   Support Vector Machines (SVMs) are among the most popular classification
techniques adopted in security applications like malware detection, intrusion
detection, and spam filtering. However, if SVMs are to be incorporated in
real-world security systems, they must be able to cope with attack patterns
that can either mislead the learning algorithm (poisoning), evade detection
(evasion), or gain information about their internal parameters (privacy
breaches). The main contributions of this chapter are twofold. First, we
introduce a formal general framework for the empirical evaluation of the
security of machine-learning systems. Second, according to our framework, we
demonstrate the feasibility of evasion, poisoning and privacy attacks against
SVMs in real-world security problems. For each attack technique, we evaluate
its impact and discuss whether (and how) it can be countered through an
adversary-aware design of SVMs. Our experiments are easily reproducible thanks
to open-source code that we have made available, together with all the employed
datasets, on a public repository.

16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
11
The categories of this paper are: hep-lat
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph