Secure Strokes – A Security Mechanism for Authentication in Mobile Devices using User ’ s Behavioral Pattern of Keystrokes Dynamics with Visual Cues

The aim is to develop a security system for mobile devices that eliminates the vulnerability of PIN (4-digit) security and which reduces the high end configuration and memory space requirements of biometrics security. The issues that we will be handling in the project work is the vulnerability of PIN security in mobile devices and providing an extra layer of security through Key Strokes Dynamics based authentication system. Also the problem of authentication error rates while using natural user keystroke pattern will be worked upon. And a better mechanism which uses an artificial keystroke rhythm with cues will be worked upon. MethodKeystroke Dynamics based Authentication Security system for Mobile Devices using Artificial typing rhythm and cues. PrincipleMaking use of the behavioral pattern of the user rather than any physical pattern or biometrics. 1. LITERATURE SURVEY / RELATED WORKS Paper Title with Authors, and year Keystroke dynamics-based authentication for mobile devices. (Seong-seob Hwang, Sungzoon Cho, Sunghoon Park)2008 Keystroke Dynamics as a Biometric for Authentication (Fabian Monrose, Aviel D. Rubin)1999 Specific problems/issues discussed Keystroke dynamics based authentication for mobile devices. Security threats to a computer and using biometrics to increase the level of security Problem statement Data security through keystrokes dynamics based authentication Result on the Authentication based on Keystrokes dynamics and comparison of the experiment results with the prior works Assumptions User acquaintance with typing in Users are familiar with computers and mobile keypad passwords Constraints Limited user group for the experiment Limitation of user group for data collection Process or operation or functional description Keystrokes Dynamics based Authentication Claimed advantages Less configuration and memory space required Claimed disadvantages Difficult to implement for a larger and diverse set of users with varying typing pattern The problem with keystroke recognition is that unlike other non-static biometrics there are no known features or feature transformations which are dedicated solely to carrying discriminating information. Tools used 3G synchronized IMT-2000 cellular system MATLAB, C++, GNU plot Volume 1 No. 1 APRIL 2011 ARPN Journal of Systems and Software ©2010-11 AJSS Journal. All rights reserved http://www.scientific-journals.org (CDMA2000 1xEV-DO) Tables and fields Choice of Passwords and use of typing hands, Equal Error rates, factors affecting error rates Domain tested Domain of 25 users with average age 25.3 yrs Data was collected from 63 users Metrics used with formula Euclidean Distance measure, Non weighted and weighted probability Performance graphs Cumulative distribution of enroll, login and imposter distances Future work proposed Applying the same theory to a more diverse user group Recognition based on freetext typing pattern during the identification process 7 2. ANALYSIS & DESIGN The system design is split into two major parts.  Enrollment Process for the user  Natural Rhythm Keystrokes  Artificial Rhythm Keystrokes  Login and Authentication 2.1 Enrollment Process The enrollment process is started by collecting the basic profile data from the user i.e. Name, username, security PIN (4 digits). Then follows the process of enrolling his keystroke pattern using the two methods. 2.1. 1 Natural Rhythm Keystrokes without cues The user is asked to type his PIN in his natural typing rhythm (4 times) and his typing pattern is recorded. S(x, y) is taken as some discrete coordinates where x=the key pressed and y= the key press timings of the user. A time out of 10 sec is used. The 4 discrete points S1, S2, S3, S4 are taken and a arbitrary quadrilateral is formed whose area is calculated and the average area of the 4 are taken Aavg and the deviation in his typing pattern is found out Deviation = Max(A1, A2, A3 A4 )Min(A1, A2, A3 A4 ) 2.1. 2 Artificial Rhythm Keystrokes with visual cues Here the same is done as Natural Rhythm Keystroke with a major difference that visual color cues (red, orange, yellow) are used so that the user can remember his typing pattern and a more consistency is obtained. Here the x value is according to the color (pattern) that the user is following. 2.2 Login and Authentication Process The Average Quadrilateral Area Aavg for the natural rhythm and artificial rhythm with their Deviation is determined and stored in the local RMS database and a threshold T is determined. The user when tries to login first has to pass through the password validation and in next stage the user is asked to type the password either in his natural rhythm or artificial rhythm with visual cues. The Aavg is determined again using the same Varignon Parallelogram method. It is checked if it lies within the threshold value T and the user is authenticated if he satisfies the threshold limit. 2.2.1 Mathematical Models and Formula used Here the Varignon Parallelogram Method for calculating the area of arbitrary quadrilateral using Midpoint Theorem Fig 1: Arbitrary Quadrilateral Area Calculation (Varignon Method) From elementary geometry, we know that in triangle V0V1V2 the midpoint line M0M1 is parallel to the base V0V2. In triangle V0V1V2V3, the line M3M2 is Volume 1 No. 1 APRIL 2011 ARPN Journal of Systems and Software ©2010-11 AJSS Journal. All rights reserved http://www.scientific-journals.org parallel to that same base V0V2. Thus, M0M1 and M3M2 are parallel to each other. Similarly, M0M3 and M1M2 are parallel, which shows that M0M1M2M3 is a parallelogram. The area relation is also easy to demonstrate, and we can compute the quadrilateral's area as: But if we are using the key stroke pattern authentication method using artificial visual cues (3colors) and a 10 sec timeout then the number of combination becomes 10000 * 3 * 10C4 = 10000 * 81 * 210 = 10000 * 17010 combinations. Area=2*Area (M0 M1 M2 M3) =2*| (M3 – M0) (M1 M0) | 8 =2*| ((V1+V2)/2-(V0+V1)/2)*((V3+V0)/2-(V0+V1)/2) | =1/2 | (V2-V0) * (V3-V1) | 2.2.2 Mathematical Comparison and Analysis of Probability So we can see that this method reduces the vulnerability of PIN (4 digits) by increasing the number of combinations by 17000 times, thus reducing the probability of an imposter accessing the data illegally. So this method can be considered as a better security technique. If we are using the normal PIN authentication and assume that it is of 4 digits P1P2 P3 P 4. Then the total combinations that can be formed are 10000 (0-9 digits).