On the Application of Active Learning to Handle Data Evolution in Android Malware Detection

Keyphrases

• Active Learning 100%
• Mobile Malware Detection 100%
• Malware 100%
• Android Malware Detection 100%
• Data Evolution 100%
• Adaptation 50%
• Rapidly Evolving 50%
• Holistically 50%
• Sampling Strategy 50%
• High Cost 50%
• Detection Performance 50%
• Detection Model 50%
• Machine Learning Techniques 50%
• Machine Learning Applications 50%
• Labeled Data 50%
• Dynamic Features 50%
• Operational Environment 50%
• Uncertainty Sampling 50%
• Mobile Malware 50%
• Feature Variation 50%
• Hybrid Features 50%
• Cyber Threat Landscape 50%
• Data Labeling 50%
• Problem Domain 50%
• Static Features 50%
• Active Learning Approach 50%
• Major Challenges 50%

Computer Science

• Active Learning 100%
• Malware Detection 100%
• Mobile Malware 100%
• Android Malware 100%
• Learning Approach 33%
• Baseline Approach 33%
• Detection Performance 33%
• Machine Learning 33%
• Learning System 33%
• Operational Environment 33%
• Threat Landscape 33%
• Malware 33%
• Detecting Malware 33%
• Problem Domain 33%