Malware Detection in Android

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Malware detection in Android involves identifying and preventing malicious software or apps from running on Android devices. This can be done using a variety of methods, including signature-based detection, behavior-based detection, and machine learning-based detection. Signature-based detection involves comparing the digital signature of an app to a database of known malware signatures. Behavior-based detection involves monitoring an app's behavior for suspicious activity, such as accessing sensitive data or sending unauthorized messages. Machine learning-based detection involves training algorithms to identify patterns in in-app behavior that is associated with malware. These methods can be used in combination to provide comprehensive protection against malware in Android devices. Additionally, users can take steps to protect themselves from malware, such as only installing apps from trusted sources, keeping their devices up-to-date, and using anti-malware software.

Autorentext
As a computer engineer, my vita is filled with an MS degree and a variety of technical achievements. I have spent countless hours honing my skills in programming and software development. Throughout my career, I have remained committed to continued learning and development, staying up-to-date with the latest technologies and industry trends.

Weitere Informationen

  • Allgemeine Informationen
    • Sprache Englisch
    • Anzahl Seiten 92
    • Herausgeber LAP LAMBERT Academic Publishing
    • Gewicht 155g
    • Untertitel An Android permissions-focused Malware Detection & Type Labeling Approach using Machine Learning Techniques
    • Autor Usama Bin Amir
    • Titel Malware Detection in Android
    • Veröffentlichung 03.03.2023
    • ISBN 6206148270
    • Format Kartonierter Einband
    • EAN 9786206148272
    • Jahr 2023
    • Größe H220mm x B150mm x T6mm
    • GTIN 09786206148272

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