• Ms. Ujwala Phere
• Mr. Ramesh V.Shahabade

Currently Mobile anti-theft mechanisms are available for discovery of the particular theft occurrence. Locating lost phone, GPS, remotely wiping and locking device, locking the SIM card service provider is only anti-theft mechanisms for discovery of the actual occurrence. They cannot detect the stealing behavior. The anti-theft mechanism will determine if the phone is in the hands of thieves, which detect stealing behavior by using long short-term memory is classifier to enhance accuracy of reorganization. We detect ongoing unauthorized movement of device notify its motion pattern inherent to actual movement. We use the waveform of accelerometer provided in mobile devices to research the pattern. We apply Long short-term memory classifier is depending upon matching patterns. So LSTM requires the step cycles, which are stored in the database that is acceleration data. LSTM verify the unknown behavior, if the mobile device hand of a thief. Motion pattern to verify the identity of the person’s possession of the device immediately whenever it has moved. We provide a device detection system for performing authentication whenever the mobile device is move. We use the accelerometer data, which monitors the device’s acceleration because of human movement. Long short-term memory requires when a user is sitting on a desk, the data is recorded by its accelerometer. Hence, we should always ignore this data instead of attempting process it into motion step cycles. However, we want to detect the start of a motion pattern during a timely fashion. We discovering out the accuracy using unauthorized movement within step cycles, which is test with some volunteers.

Mobile Society, Anti-theft, Motion pattern, Gait authentication.

" Anti-theft Mobile Device Motion Pattern Identification Using LSTM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 9, page no.c626-c630, September-2023, Available :http://www.jetir.org/papers/JETIR2309270.pdf

" Anti-theft Mobile Device Motion Pattern Identification Using LSTM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 9, page no. ppc626-c630, September-2023, Available at : http://www.jetir.org/papers/JETIR2309270.pdf