Key Stroke Analysis in Python

Abstract:

This paper illustrated one unique measure of keystroke patterns of user typing to prevent insider threats with combination of existing keystroke credentials. While insider threats may never be eliminated, it is worth noting that risk-mitigating counter measures exist. Every organization's security architecture must take insider threat into account. As reiterated trough out the security industry, defense in depth is the essential. Defense in depth requires security professional to take a layered approach to protecting information. In essence, we should never rely on just one security method or technology. Only user ID and passwords are not enough strong now a day to protect workstations from unauthorized access. Being remarkable advantages and to support multilevel authentication biometrics may be strong add-on. Recent research on behavioral biometrics i.e., keystroke dynamics proves its efficiency for stronger authentication. With numerous advantages key-stroke pattern credential are employing in many organization to establish layered security mechanism. Work of last decade on keystroke dynamics also reveals some drawbacks. So research is going on to find more traits of user typing for more efficient authentication. Through this paper we proposed and experimentally proved one measure of keystroke pattern which is distinctive for each user and can make keystroke pattern credential stronger.