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SEMANTIC MODELLING OF ANDROID MALWARE FOR EFFECTIVE MALWARE COMPREHENSION, DETECTION AND CLASSIFICATION Constructed DSA of attacks DSA & OBA depicts the essential invocation of APIs in a malicious behavior Android Malware - 30.6% of apps are potential harmful apps - Including privacy leakage, privilege escalation, and ransomware. Motivation - Semantic modeling, identify malware essences - Combined detection, scalability & precision - Attack identification, understand attacks For known Android malware - Learn DSA & OBA - Extract feature for training For Android Apps to test - Extract feature and do classification - Generate DFA to do family classification - Identify OBA to determine attacks INTRODUCTION CONSTRUCTION OF DSA EVALUATION SYSTEM OVERVIEW Guozhu Meng, Yinxing Xue and Yang Liu. School of Computer Science and Engineering, NTU

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Page 1: SEMANTIC MODELLING OF ANDROID MALWARE …Android Malware - 30.6% of apps are potential harmful apps - Including privacy leakage, privilege escalation, and ransomware. Motivation -

SEMANTIC MODELLING OF ANDROID MALWARE FOR EFFECTIVE MALWARE COMPREHENSION,

DETECTION AND CLASSIFICATION

Constructed DSA of attacks

DSA & OBA depicts the essential invocation

of APIs in a malicious behavior

Android Malware

- 30.6% of apps are potential harmful apps

- Including privacy leakage, privilege escalation,

and ransomware.

Motivation

- Semantic modeling, identify malware essences

- Combined detection, scalability & precision

- Attack identification, understand attacks

For known Android malware

- Learn DSA & OBA

- Extract feature for training

For Android Apps to test

- Extract feature and do classification

- Generate DFA to do family classification

- Identify OBA to determine attacks

INTRODUCTION CONSTRUCTION OF DSA

EVALUATIONSYSTEM OVERVIEW

Guozhu Meng, Yinxing Xue and Yang Liu. School of Computer Science and Engineering, NTU

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