Mobile phone technology dominantly controls our daily life whether for solemn business matter or for our social life through which we access the whole universe just in a tap away. Thus, the power of connectivity using the Internet through GSM (Global System for Mobile)/LTE (Latest Technology Extended) enhanced its usage in a way not having one can be considered as handicapped. Losing our device, leaving the device unattended and exposure of our password/pattern can make us not only lose our reputation in our social network presence but also might be a risk allowing others to have control over our activities by the features we use through applications in our phones.The problem here is that this screen-lock authentication feature is breakable and the device can be unlocked easily.Our application will manage to work on behavioral authentication by studying and analyzing the characteristics of the owner of the apparatus with a combination of signature and character usage scheme. This paper adopted the concept of machine learning from natural language processing so that an intelligent application can secure the devices content from unauthorized access.

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M. Eng. Yonatan Mekonnen Abera holds a software engineering Master's Thesis on Androids operating system security. He is involved in many big projects focusing on technological advancement and automation. Acquired twice an Innovative and Initiative Award followed by an honorary recognition for his outstanding competency.