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. 2022 Aug 6;22(15):5883. doi: 10.3390/s22155883
Algorithm 4: Malware Classification
Input: Trained and texture features
Output: Malware classification
Step 1: Insert T and I
Step 2: T=CNNT to apply the CNN technique of trained features
Step 3: I=CNNI to apply CNN the technique of texture features
Step 4: Calculate deep PF as a prominent features as a prominent features
Step 5: Apply voting-based ensemble learning on deep PF
Step 6: App classification as malware or benign
Step 7: Finish