Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: When Wireless Security Meets Machine Learning: Motivation, Challenges,
  and Research Directions   Wireless systems are vulnerable to various attacks such as jamming and
eavesdropping due to the shared and broadcast nature of wireless medium. To
support both attack and defense strategies, machine learning (ML) provides
automated means to learn from and adapt to wireless communication
characteristics that are hard to capture by hand-crafted features and models.
This article discusses motivation, background, and scope of research efforts
that bridge ML and wireless security. Motivated by research directions surveyed
in the context of ML for wireless security, ML-based attack and defense
solutions and emerging adversarial ML techniques in the wireless domain are
identified along with a roadmap to foster research efforts in bridging ML and
wireless security.

37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
35
The categories of this paper are: mtrl-th
33
The categories of this paper are: plasm-ph
23
The categories of this paper are: solv-int