• Dr.K.N.S Lakshmi
• Amith Prasad

The Android Malware Detection using Genetic Algorithm (Feature Selection) and Artificial Neural Network (ANN) Model project aims to develop an advanced system for detecting malware in Android applications. The project combines the power of genetic algorithms and artificial neural networks to achieve accurate and efficient malware detection. By employing a Genetic Algorithm, relevant features are selected from a large feature set, reducing dimensionality and improving classification performance. The selected features are then used to train an ANN model capable of accurately classifying Android applications as malware or benign. The project encompasses steps such as dataset preprocessing, implementing the Genetic Algorithm, training the ANN model, and evaluating its performance. The results obtained from the system can demonstrate its effectiveness in detecting Android malware and contribute to enhancing the security and privacy

Malware Prediction, Machine Learning, Genetic Algorithm, Artificial Neural Network (ANN), Android Dataset.

"ANDROID MALWARE DETECTION USING ANN AND GENETIC ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 6, page no.j551-j560, June-2023, Available :http://www.jetir.org/papers/JETIR2306964.pdf

"ANDROID MALWARE DETECTION USING ANN AND GENETIC ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 6, page no. ppj551-j560, June-2023, Available at : http://www.jetir.org/papers/JETIR2306964.pdf