Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Comparison of Static, Dynamic, and Hybrid Analysis for Malware
  Detection   In this research, we compare malware detection techniques based on static,
dynamic, and hybrid analysis. Specifically, we train Hidden Markov Models (HMMs
) on both static and dynamic feature sets and compare the resulting detection
rates over a substantial number of malware families. We also consider hybrid
cases, where dynamic analysis is used in the training phase, with static
techniques used in the detection phase, and vice versa. In our experiments, a
fully dynamic approach generally yields the best detection rates. We discuss
the implications of this research for malware detection based on hybrid
techniques.

20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
11
The categories of this paper are: hep-lat
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an