A UNIQUE MACHINE LEARNING METHOD FOR ANDRIOD  MALWARE DETECTION USING FEATURE CO-EXSISTENCE

Mrs. M. MOUNIKA, CHELLUBOINA SHIRISHA, MUNAGAPATI SHEEVANI,   TUPPATHI ANUSHA

A UNIQUE MACHINE LEARNING METHOD FOR ANDRIOD MALWARE DETECTION USING FEATURE CO-EXSISTENCE

Authors

Mrs. M. MOUNIKA, CHELLUBOINA SHIRISHA, MUNAGAPATI SHEEVANI, TUPPATHI ANUSHA

Keywords:

Abstract

The paper proposes a new machinelearning model for detecting Android malware based on the coexistence of static features. The modelassumes that Android malware requests an abnormal

References

Elenkov, N. (2014). Android Security Internals. No Starch Press.

Ng, A. (2018). Machine Learning Yearning. deeplearning.ai.

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Published

2024-02-15

How to Cite

Mrs. M. MOUNIKA, CHELLUBOINA SHIRISHA, MUNAGAPATI SHEEVANI, TUPPATHI ANUSHA. (2024). A UNIQUE MACHINE LEARNING METHOD FOR ANDRIOD MALWARE DETECTION USING FEATURE CO-EXSISTENCE . Journal of Computational Analysis and Applications (JoCAAA), 32(2), 288–298. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2703