Anzeige
Erschienen in:
2018 | OriginalPaper | Buchkapitel
Permission-Set Based Detection and Analysis of Android Malware
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Smartphone industry has become one of the fastest growing technological areas in the past few years. The monotonic growth of Android share market and the diversity among various app sources besides official Google Play Store has attracted attention of malware attacker. To tackle with the problem of increasing number of malicious Android app available at various sources, this paper proposes a novel approach which is based on feature similarity of Android apps. This approach has been implemented by performing static analysis to extract the features from an APK file. Extracted features are useful and meaningful to make efficient training system. This paper proposes a permission-based model which makes use of self-organizing map algorithm. The implemented approach has been analyzed using 1200 heterogeneous Android apps. The proposed approach shows improved results for TPR, FPR, and accuracy.