The Resource Evolving decision trees for the categorization of software, by Jasenko Hosic

Evolving decision trees for the categorization of software, by Jasenko Hosic

Label
Evolving decision trees for the categorization of software
Title
Evolving decision trees for the categorization of software
Statement of responsibility
by Jasenko Hosic
Creator
Author
Subject
Language
eng
Summary
"Current manual techniques of static reverse engineering are inefficient at providing semantic program understanding. An automated method to categorize applications was developed in order to quickly determine pertinent characteristics. Prior work in this area has had some success, but a major strength of the approach detailed in this thesis is that it produces heuristics that can be reused for quick analysis of new data. The method relies on a genetic programming algorithm to evolve decision trees which can be used to categorize software. The terminals, or leaf nodes, within the trees each contain values based on selected features from one of several attributes: system calls, byte N-grams, opcode N-grams, registers, opcode collocation, cyclomatic complexity, and bonding. The evolved decision trees are reusable and achieve average accuracies above 90% when categorizing programs based on compiler origin, authorship, and versions. Developing new decision trees simply requires more labeled datasets and potentially different feature selection algorithms for other attributes, depending on the data being classified. The genetic programming algorithm used to evolve the decision trees was compared against C4.5, a classic decision tree technique. In all experiments, the genetic programming approach outperformed C4.5. This thesis is an extension and expansion of the work published in the Computer Forensics in Software Engineering workshop at COMPSAC 2014 - the Annual 38th IEEE International Conference on Computer Software and Applications. This thesis is also being prepared as a journal article to be submitted for publication."--Abstract, page iii
Member of
Cataloging source
UMR
http://library.link/vocab/creatorDate
1989-
http://library.link/vocab/creatorName
Hosic, Jasenko
Degree
M.S.
Dissertation year
2014
Funding information
Funding by U.S. Department of Energy's National Nuclear Security Administration
Granting institution
Missouri University of Science and Technology
Illustrations
illustrations
Index
no index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
  • theses
http://library.link/vocab/subjectName
  • Decision trees
  • Computational intelligence
  • Genetic programming (Computer science)
Label
Evolving decision trees for the categorization of software, by Jasenko Hosic
Instantiates
Publication
Note
Vita
Bibliography note
Includes bibliographic references (pages 52-55)
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Control code
894579837
Extent
1 online resource (ix, 56 pages)
Form of item
online
Governing access note
These materials are protected under copyright by the original author
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations (some colored).
Specific material designation
remote
System control number
(OCoLC)894579837
Label
Evolving decision trees for the categorization of software, by Jasenko Hosic
Publication
Note
Vita
Bibliography note
Includes bibliographic references (pages 52-55)
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Control code
894579837
Extent
1 online resource (ix, 56 pages)
Form of item
online
Governing access note
These materials are protected under copyright by the original author
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations (some colored).
Specific material designation
remote
System control number
(OCoLC)894579837

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