Singapore Academic Cybersecurity R&D
Harnessing R&D to Secure our Nation
Malware Source Attribution through Multi-Dimensional Code-Feature Analysis
- Lead PIs : Vitaly Kamluk, Kaspersky Lab ( firstname.lastname@example.org ) and Liang Zhenkai, Associate Professor, NUS ( liangzk@ )
- Host Institution : Kaspersky Lab
- Parner Institution : School of Computing, NUS
In this proposal, Kaspersky Lab and NUS are collaborating to create automated solutions for malware source attribution. We aim to combine program analysis and machine learning to develop automated solutions that can scale malware attribution to handle a large amount of malware.