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From using secret knowledge like password up to physical traits as biometrics, current smartphone authentication systems are deemed inconvenience and difficult for users. Burdens on remembering password as well as privacy issue on stolen or forged biometrics have raised a new idea of authentication systems. New system is expected to be transparent to users without or with very minimum user involvement being as implicit authentication system. With user’s convenience in mind yet without sacrificing security aspect, behavioral biometrics can be applied in implicit authentication system for security protection to users and their smartphones. Behavioral biometrics (behaviometrics) concept has emerged intending on both being inexpensive for deployment and being safe to user as compared on physical traits-based biometrics. One of the human behaviors considered being unique is arm’s flex (AF). It is gestural pattern i.e. the way people bending their arm for picking a phone when responding to incoming calls. That arm’s flexing is considered as a subset of gesture pattern in lower limb gesture. We study and evaluate arm’s movements that take place when picking up smartphone to receive incoming phone call. Our study shows that arm’s movements captured by smartphone built-in accelerometer are potentially useful for authentication system using smartphone. Our study shows that AF is indeed unique and has discriminant power to distinguish one user from others. These findings will promisingly augment development of novel implicit and transparent authentication system in smartphone so that authentication becomes easier and unobtrusive for user.