Attention-Based API Locating for Malware Techniques-Reference-Cited by-同舟云学术

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Attention-Based API Locating for Malware Techniques

Published:2024 Issue: Volume:19 Page:1199-1212
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Wong Guo-Wei¹^ORCID,Huang Yi-Ting²^ORCID,Guo Ying-Ren³^ORCID,Sun Yeali⁴,Chen Meng Chang³^ORCID

Affiliation:

1. Department of Computer Science and Information Engineering, National Taiwan University, Taipei City, Taiwan

2. Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei City, Taiwan

3. Academia Sinica, Taipei City, Taiwan

4. Department of Information Management, National Taiwan University, Taipei City, Taiwan

Funder

National Science and Technology Council (NSTC), Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/10206/10319981/10309174.pdf?arnumber=10309174

Reference52 articles.

1. Adversarially robust malware detection using monotonic classification;romeo;Proc 4th ACM Int Workshop Secur Privacy Anal,2018

2. Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers

3. Polymorphic malware detection using topological feature extraction with data mining

4. Malware behavioural detection and vaccine development by using a support vector model classifier

5. Attended-over Distributed Specificity for Information Extraction in Cybersecurity

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1. Digital forensic of Maze ransomware: A case of electricity distributor enterprise in ASEAN;Expert Systems with Applications;2024-09

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