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Mobile Malware Detection using Anomaly Based Machine Learning Classifier Techniques
Diyala Journal for Pure Science
Smartphones have become essential in our daily lives. Many works can be done by using it like, browse the internet, and download many applications for each device through the available store. As a result, the number of malware applications downloaded also increases. These malware carries out various activities behind the scenes, such as breach of confidentiality, breach of privacy, loss of confidentiality, system breakdown, theft of sensitive information, etc. Many types of research and studiesdoi:10.24237/djps.17.02.544b fatcat:p7odtztomzgb7pierkabnf5q7i