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The evaluation conducted under real Android deployment conditions demonstrates the robustness and effectiveness of the proposed hybrid fusion model. Compared to the standalone CNN and LSTM models, the hybrid approach achieves the highest accuracy at 95.4% while simultaneously maintaining the lowest false positive rate of 3.8%. These results indicate a substantial improvement in detection reliability, which is critical in forensic applications where minimizing false alarms is essential. The performance gains observed in real-world environments further confirm the suitability of the proposed architecture for practical Android forensic deployment. |
IEEE/ICACT20260079 Slide.17
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