Authentication, an identity verification and confirmation method, is a defense mechanism that reduces the risk of adversarial attacks, specifically to identity theft and impersonation in computer systems. Existing authentication methods exhibit vulnerabilities, such as password dictionary attack, credential stuffing, and identity spoofing. In this study, we examine the possibility of using a class of biometric data, namely step counts, to investigate their potential in person identification and verification. For this purpose, we collected step-count data from research volunteers over a period of 33 days or over 560 hours. Subsequently, we used these data to establish an appropriate threshold and tested their accuracy using a confusion matrix. Our evaluations showed that a suitable threshold range for step-count authentication is x ̅-1S.D.≤Range ≤ x ̅+1S.D., where S.D. represents standard deviation and x ̅ is the mean value of step counts of an individual. Moreover, we constructed a receiver operating characteristic curve and calculated the area under the curve, which showed that step counts have the potential to be used in behavioral biometric authentication methods. Thus, using the threshold range method, step counts can potentially become another behavioral biometric factor for authentication systems.