arXiv:2611.01031v1 Announce Type: new Abstract: Reliable first-seen dates are important for constructing temporal malware evaluation splits, but this information often comes from external services that are not equally accessible to all researchers. We investigate whether machine learning can instead estimate an executable's first-seen date or determine when its PE/COFF compilation timestamp is unreliable.

Read the full article at arXiv cs.CR →