Main Reference PaperMADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention, IEEE Transactions on Dependable and Secure Computing, 2016 [Java/Android].
  • Malware Detection system for Android devices called MADAM (Multi-Level Anomaly Detector for Android Malware) is proposed in which detection of malicious behavior is found in four levels of kernel, application, user and package by grouping five android features.

+ Description
  • Malware Detection system for Android devices called MADAM (Multi-Level Anomaly Detector for Android Malware) is proposed in which detection of malicious behavior is found in four levels of kernel, application, user and package by grouping five android features.

  • To detect and block malicious apps using classifiers and a behavioral signature-based detector.

  • To provide high efficacy with low overhead.

+ Aim & Objectives
  • To detect and block malicious apps using classifiers and a behavioral signature-based detector.

  • To provide high efficacy with low overhead.

  • Adaptive threshold identification method is contributed to behavioral patterns.

+ Contribution
  • Adaptive threshold identification method is contributed to behavioral patterns.

  • Java JDK 1.8, Android-sdk_r22.6.2-linux, SQLite 3.8.6.

  • Eclipse – Indigo SR2, ADT Plug-in for Eclipse, & J2SE.

+ Software Tools & Technologies
  • Java JDK 1.8, Android-sdk_r22.6.2-linux, SQLite 3.8.6.

  • Eclipse – Indigo SR2, ADT Plug-in for Eclipse, & J2SE.

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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