Are Machine Learning Models for Malware Detection Ready for Prime Time?-Reference-Cited by-同舟云学术

Are Machine Learning Models for Malware Detection Ready for Prime Time?

Published:2023-03 Issue:2 Volume:21 Page:53-56
ISSN:1540-7993
Container-title:IEEE Security & Privacy
language:
Short-container-title:IEEE Secur. Privacy

Author:

Cavallaro Lorenzo¹^ORCID,Kinder Johannes²^ORCID,Pendlebury Feargus¹^ORCID,Pierazzi Fabio³^ORCID

Affiliation:

1. University College London, London, U.K.

2. Bundeswehr University Munich, Neubiberg, Germany

3. Department of Informatics, King’s College London, London, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Law,Electrical and Electronic Engineering,Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/8013/10102603/10102612.pdf?arnumber=10102612

Reference15 articles.

1. AndroZoo: Collecting Millions of Android Apps for the Research Community;allix;2016 IEEE/ACM 13th Conference on Mining Software Repositories (MSR),2016

2. A unifying view on dataset shift in classification

3. Intriguing Properties of Adversarial ML Attacks in the Problem Space

4. SOREL-20M: A large scale benchmark dataset for malicious PE detection;harang,2020

5. Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift

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