Cutting Through the Emissions: Feature Selection from Electromagnetic Side-Channel Data for Activity Detection

  1. Sayakkara, A.
  2. Miralles-Pechuán, L.
  3. Le-Khac, N.-A.
  4. Scanlon, M.
Zeitschrift:
Forensic Science International: Digital Investigation

ISSN: 2666-2817,  2666-2825

Datum der Publikation: 2020

Ausgabe: 32

Art: Artikel

DOI: 10.1016/J.FSIDI.2020.300927 GOOGLE SCHOLAR lock_openOpen Access editor
Datenquelle: Scopus