Student Name: Kathlee een n Silveira ra Student ID: 420004 0440 - PowerPoint PPT Presentation

Student Name: Kathlee een n Silveira ra Student ID: 420004 0440 Supervisor Name: Mehmet t Orgun un

1. Introduction 2. Functional Design 3. Technical Design 4. Evaluation 5. Conclusion 2

What is Biometrics?  What is Keystroke Dynamics?  Aims, Outcomes and Significance  Methodology  Past Work  3

 Bio (life) and metric (to measure) ◦ Biometric is a method to measure certain human characteristics  unique to a person, permanent, measurable, not transferable or shared 4

User A typing the same phrase 2 users typing the same phrase 5

Aims Ou Outcomes comes  Implement and test a  Prototype of prototype of Keystroke Keystroke Dynamics Dynamics based on an application algorithm by (Teh, Teoh  Final Report and et al. 2010) Presentation Signifi ificance cance  increase security by verifying online users who attempt to login  reducing identity thefts or forgery 6

Plann nnin ing Setup up envi viro ronme ment Regi gistr tration ation Screen Application Component onent Test t (Regi gistr tratio ation) n) Verifi fica cati tion on Screen Application Component onent Test(Ve t(Verifica ificati tion) n) System m Integr gration ation Testi ting ng Analysis is & Docume ment ntation ation 7

Select ect 1 Biomet metri ric: Keyst stro roke e Dyna namic mics Select ct 2 B 2 Biome ometri trics cs based on ease of implementation • Fingerprin ngerprint ( from Conventional & physiological group) • Keyst strok roke e Dynamics amics (from Emerging & behavioural group) Research search variou ious s Biometr metric ic Technologies nologies 8

The Concept of a Feature  Vector Basic outline of the process  The algorithm  9

 Dwell ell time me (D1): ): D1= R1- P1  Flight ight time e (D2): ): D2 = P2 - P1  Flight ight time e (D3): ): D3 = P2 - R1  Flight ight ti time e (D4): ): D4 = R2 - R1 10

 2 parts of the process: ◦ Enrolment (One-time) ◦ Verification (Recurring) Enrolmen olment t Mode Verifi rificati tion on Mode 11

 Enrolment ◦ Use the Feature Vector to generate a template (mean, standard deviation, number of samples, summation) ◦ Store the template  Verification ◦ Gaussian probability density function (GPD) is used to compute the similarity score between the reference template and the test data template ◦ output score of GPD has range of [0,1] 12

Basic Architectural Pattern  Technologies Considered  Component Design  13

 Modular design allows components to be plugged in High-level Architectural Pattern A1. Input/Output Layer A2. Application Layer A3. Storage Layer 14

• Applets • Requirement: • Swings Algorithm Input t / suggested to Output t • Java command line capture time using Layer • JAAS nanoseconds • JavaScript • Out of the technologies considered, only Applic icatio ation n • Java Swings could Layer capture time in nanoseconds Storage age • Oracle Database Layer 15

Test t Environment onment Deve velopme ment nt Input t / Output ut Layer er Applica cation tion Layer er Stora rage ge Oracle Oracle Layer er Database se Database se 16

Experiment Setup  Preliminary Results  17

 Acquisition of the test-data ◦ 10 volunteers from the IT department for testing ◦ Registration: Page to capture the user’s keystroke patterns ◦ Verification: Login into the system during which the real-time keystroke pattern was matched against the stored template to allow or deny the user.  Captured user data useful in testing the system  Captured user data is also useful for analysing patterns to obtain better algorithm 18

 With given time of 1 semester, tests conducted with 6 volunteers were not sufficient to provide reliable metrics like FAR (False Acceptance Rate) and FRR (False Rejection Rate)  Before a large scale testing occurs, there are other issues like ethics and the user’s consent.  The proto totyp type e is ready ady for more e tests ts using ing mo more e users. ers. 19

Summary  Lessons Learnt & Future work  20

 The Prototype of Keystroke Dynamics is ready for further evaluation  Components are modular to allow replacements for other technology / algorithms / metrics  Swings was the chosen technology as it could capture time in nanoseconds 21

 Les essons sons Lea earnt rnt ◦ technology: what other technologies could be considered (e.g., Platform as a Service), precision of keystroke timings ◦ project management: how the project could have been structured to optimize it (e.g., advertised for voluntary users in a wider population)  Future ture wo work ◦ augmenting the implementation to be more robust ◦ inter-operable with other key Out-Of-The-Box (OOTB) Identity and Access Management (IAM) solutions and products ◦ the use of multiple biometrics 22

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