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ETD

Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-09062022-133039


Tipo di tesi
Tesi di laurea magistrale
URN
etd-09062022-133039
Titolo
Graph-based android malware categorization based on Convolutional Neural Networks
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
ARTIFICIAL INTELLIGENCE AND DATA ENGINEERING
Parole chiave
  • android
  • cnn
  • cybersecurity
  • graph
  • machine learning
  • malware
  • rever engineering
Data inizio appello
23/09/2022
Consultabilità
Completa
Riassunto (Inglese)
Riassunto (Italiano)
My study will focus on the Classification of APKs in these different categories:
1. Benign APK : Harmless or well intentioned application, the opposite of malicious APKs.
2. File Infector APK : A file infector is a type of malware that has the capability to propagate by attaching its code to other programs or files.
3. Riskware APK : Riskware is any potentially unwanted application that is not classified as malware, but may utilize system resources in an undesirable or annoying manner, and/or may pose a security risk.
4. Trojan APK : A trojan is a type of malware that performs activites without the user’s knowledge.
5. Adware APK : Adware typically display advertising content to the user.
File