Improving the Effectiveness and Efficiency of Dynamic Malware Analysis Using Machine Learning

Text Registration

Improving the Effectiveness and Efficiency of Dynamic Malware Analysis Using Machine Learning

Status

Published

on 12 Mar 2019

Year of Creation

2018

Leonardo Andres De La Rosa Angarita

Registration Number

TX0008693872

on 12 Mar 2019

The U.S. Copyright record (Registration Number: TX0008693872) dated 12 Mar 2019, pertains to an electronic file (eService) titled "Improving the Effectiveness and Efficiency of Dynamic Malware Analysis Using Machine Learning" created in 2018. The copyright holder is Leonardo Andres De La Rosa Angarita, known for their creative contributions in text registration. For any inquiries concerning this copyrighted material, kindly reach out to Leonardo Andres De La Rosa Angarita.

Leonardo Andres De La Rosa Angarita

Application Details

Registration Number

TX0008693872

Registration Date

3/12/2019

Year of Creation

2018

Agency Marc Code

DLC-CO

Record Status

New

First Publication Nation

United States

Personal Authors

Leonardo De La Rosa

Notes

Rights Note: Mark Dill, ProQuest-CSA, LLC, 789 E. Eisenhower Parkway, Ann Arbor, MI, 48108-3218, United States, (800) 521-0600, disspub@proquest.com

Statements

Application Title Statement: Improving the Effectiveness and Efficiency of Dynamic Malware Analysis Using Machine Learning

Author Statement: Leonardo De La Rosa Citizenship: not known Authorship: text

Notes

Rights Note: Mark Dill, ProQuest-CSA, LLC, 789 E. Eisenhower Parkway, Ann Arbor, MI, 48108-3218, United States, (800) 521-0600, disspub@proquest.com

Statements

Application Title Statement: Improving the Effectiveness and Efficiency of Dynamic Malware Analysis Using Machine Learning

Author Statement: Leonardo De La Rosa Citizenship: not known Authorship: text

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