Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automated detection and classification of cryptographic algorithms in
  binary programs through machine learning   Threats from the internet, particularly malicious software (i.e., malware)
often use cryptographic algorithms to disguise their actions and even to take
control of a victim's system (as in the case of ransomware). Malware and other
threats proliferate too quickly for the time-consuming traditional methods of
binary analysis to be effective. By automating detection and classification of
cryptographic algorithms, we can speed program analysis and more efficiently
combat malware.
  This thesis will present several methods of leveraging machine learning to
automatically discover and classify cryptographic algorithms in compiled binary
programs.
  While further work is necessary to fully evaluate these methods on real-world
binary programs, the results in this paper suggest that machine learning can be
used successfully to detect and identify cryptographic primitives in compiled
code. Currently, these techniques successfully detect and classify
cryptographic algorithms in small single-purpose programs, and further work is
proposed to apply them to real-world examples.

30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con