• 368 Citations
  • 11 h-Index
20032019
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Fingerprint Fingerprint is based on mining the text of the experts' scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 1 Similar Profiles
Dynamic analysis Engineering & Materials Science
Application programming interfaces (API) Engineering & Materials Science
Internet Engineering & Materials Science
Malware Mathematics
Intrusion detection Engineering & Materials Science
Authentication Engineering & Materials Science
Web services Engineering & Materials Science
Servers Engineering & Materials Science

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Research Output 2003 2019

  • 368 Citations
  • 11 h-Index
  • 48 Conference contribution
  • 33 Article
  • 7 Conference article
  • 3 Paper
2 Citations (Scopus)

A multimodal deep learning method for android malware detection using various features

Kim, T., Kang, B., Rho, M., Sezer, S. & Im, E. G., 2019 Mar 1, In : IEEE Transactions on Information Forensics and Security. 14, 3, p. 773-788 16 p., 8443370.

Research output: Contribution to journalArticleResearchpeer-review

Smartphones
Deep learning
Malware
Feature extraction
Experiments

Binary executable file similarity calculation using function matching

Kim, T. G., Lee, Y. R., Kang, B. J. & Im, E. G., 2019 Feb 6, In : Journal of Supercomputing. 75, 2, p. 607-622 16 p.

Research output: Contribution to journalArticleResearchpeer-review

Binary
Software
Attribute
Malware
N-gram

Detection Method for Distributed Web-Crawlers: A Long-Tail Threshold Model

Ro, I., Han, J. S. & Im, E. G., 2018 Jan 1, In : Security and Communication Networks. 2018, 9065424.

Research output: Contribution to journalArticleResearchpeer-review

Websites
NASA

Malware classification using byte sequence information

Jung, B., Kim, T. & Im, E. G., 2018 Oct 9, Proceedings of the 2018 Research in Adaptive and Convergent Systems, RACS 2018. Association for Computing Machinery, Inc, p. 143-148 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Malware
Neural networks
Application programming interfaces (API)
Recurrent neural networks
Dynamic analysis

Packer identification method based on byte sequences

Jung, B. H., Bae, S. I., Choi, C. & Im, E. G., 2018 Jan 1, (Accepted/In press) In : Concurrency Computation. e5082.

Research output: Contribution to journalArticleResearchpeer-review

Packers
Malware
Packing
Signature