Date of Award
12-2009
Degree Type
Thesis
Degree Name
M.S.
Degree Program
Computer Science
Department
Computer Science
Major Professor
Bilar, Daniel
Second Advisor
Richard III, Golden
Third Advisor
Winters-Hilt, Stephen
Abstract
This thesis explores what patterns, if any, exist to differentiate non-malware from malware, given only a sequence of raw bytes composing either a received file or a fixed-length initial segment of a received file. If any such patterns are found, their effectiveness as filtering criteria is investigated.
Recommended Citation
Redfern, Cory, "Malware Recognition by Properties of Executables" (2009). University of New Orleans Theses and Dissertations. 1013.
https://scholarworks.uno.edu/td/1013
COinS
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.