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Attack of mechanical replicas liveness detection with eye movements

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Final Year IEEE Projects for BE, B.Tech, ME, M.Tech,M.Sc, MCA & Diploma Students latest Java, .Net, Matlab, NS2, Android, Embedded,Mechanical, Robtics, VLSI, Power Electronics, IEEE projects are given absolutely complete working product and document providing with real time Software & Embedded training......

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Attack of mechanical replicas liveness detection with eye movements

  1. 1. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com ATTACK OF MECHANICAL REPLICAS: LIVENESS DETECTION WITH EYE MOVEMENTS By A PROJECT REPORT Submitted to the Department of electronics &communication Engineering in the FACULTY OF ENGINEERING & TECHNOLOGY In partial fulfillment of the requirements for the award of the degree Of MASTER OF TECHNOLOGY IN ELECTRONICS &COMMUNICATION ENGINEERING APRIL 2016
  2. 2. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com CERTIFICATE Certified that this project report titled “Attack of Mechanical Replicas: Liveness Detection With Eye Movements” is the bonafide work of Mr. _____________Who carried out the research under my supervision Certified further, that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate. Signature of the Guide Signature of the H.O.D Name Name
  3. 3. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com DECLARATION I hereby declare that the project work entitled “Attack of Mechanical Replicas: Liveness Detection With Eye Movements” Submitted to BHARATHIDASAN UNIVERSITY in partial fulfillment of the requirement for the award of the Degree of MASTER OF APPLIED ELECTRONICS is a record of original work done by me the guidance of Prof.A.Vinayagam M.Sc., M.Phil., M.E., to the best of my knowledge, the work reported here is not a part of any other thesis or work on the basis of which a degree or award was conferred on an earlier occasion to me or any other candidate. (Student Name) (Reg.No) Place: Date:
  4. 4. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com ACKNOWLEDGEMENT I am extremely glad to present my project “Attack of Mechanical Replicas: Liveness Detection With Eye Movements” which is a part of my curriculum of third semester Master of Science in Computer science. I take this opportunity to express my sincere gratitude to those who helped me in bringing out this project work. I would like to express my Director,Dr. K. ANANDAN, M.A.(Eco.), M.Ed., M.Phil.,(Edn.), PGDCA., CGT., M.A.(Psy.)of who had given me an opportunity to undertake this project. I am highly indebted to Co-OrdinatorProf. Muniappan Department of Physics and thank from my deep heart for her valuable comments I received through my project. I wish to express my deep sense of gratitude to my guide Prof. A.Vinayagam M.Sc., M.Phil., M.E., for her immense help and encouragement for successful completion of this project. I also express my sincere thanks to the all the staff members of Computer science for their kind advice. And last, but not the least, I express my deep gratitude to my parents and friends for their encouragement and support throughout the project.
  5. 5. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com ABSTRACT: This paper investigates liveness detection techniques in the area of eye movement biometrics. We investigate a specific scenario, in which an impostor constructs an artificial replica of the human eye. Two attack scenarios are considered: 1) the impostor does not have access to the biometric templates representing authentic users, and instead utilizes average anatomical values from the relevant literature and 2) the impostor gains access to the complete biometric database, and is able to employ exact anatomical values for each individual. In this paper, liveness detection is performed at the feature and match score levels for several existing forms of eye movement biometric, based on different aspects of the human visual system. The ability of each technique to differentiate between live and artificial recordings is measured by its corresponding false spoof acceptance rate, false live rejection rate, and classification rate. The results suggest that eye movement biometrics are highly resistant to circumvention by artificial recordings when liveness detection is performed at the feature level. Unfortunately, not all techniques provide feature vectors that are suitable for liveness detection at the feature level. At the match score level, the accuracy of liveness detection depends highly on the biometric techniques employed.
  6. 6. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com INTRODUCTION: Liveness detection is an important problem in the biometric domain, due to the fact that it is relatively simple to create convincing replicas of many existing biometrics. For example, commercial iris identification systems can be spoofed by high-resolution images of the eye printed on paper, with a hole to present the intruder’s pupil, bypassing liveness detection mechanisms There are further examples of fingerprint scanners being spoofed by common household items like gelatin and face detection systems spoofed by printed images of the face. While liveness detection has been researched extensively in a number of fields, there is almost no research on the topic of liveness detection as it relates to the field of eye movement biometrics. The idea of liveness detection via eye movements is appealing because eye movements can be captured in tandem with iris information using a single image sensor. In fact, the hardware in many existing iris recognition devices is capable of supporting modern videooculography techniques to produce an eye movement signal. This provides an opportunity to increase the accuracy, and counterfeit-resistance of existing iris recognition devices. A.Related Work in Liveness Detection In the field of iris recognition, several liveness detection methods have been proposed and evaluated, involving: frequency spectrum analysis of the iris image; analysis of light reflected from the spherical corneal surface (front wall of the eye); detection of corneal moistness; pupil dilation; and the quality-related features of the captured image. In the field of fingerprint recognition, Coli and colleagues provide a survey of existing liveness detection techniques and their performance Shuckers et al. achieved 90-100% correct classification rate using the statistics of ridges and moisture to measure the liveness of fingerprints, Ghiani et al. applied liveness detection by local binary patterns, pores, power spectrum analysis, wavelet energy signatures, valleys wavelets, and curvelets to achieve equal error rates of 7-13% ,Recent competitions indicate that fingerprintbased biometrics are still susceptible to spoofing,In the field of face recognition, liveness detection methods can be roughly categorized as analysis of motion, texture, and detection of life signs. Competition results of various algorithms in this area indicate a high accuracy of detection for 2D spoofing attacks,particularly in regard to the PRINT-ATTACK dataset
  7. 7. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com B. Related Work in Eye Movement Biometrics In the current work, we explore the liveness detection properties of four existing eye movement biometric techniques, based on various aspects of the human visual system. These techniques include: oculomotor plant characteristics (OPC), complex oculomotor behavior (COB), complex eye movement patterns (CEM-P), and complex eye movement behavior (CEM-B) biometrics. In 2011, Holland and Komogortsev, described complex eye movement pattern (CEM- P) biometrics. CEM-P compares average and aggregate measures of the eye movement scanpath with a distance function to estimate the similarity of two recordings. Biometric features include: fixation count, average fixation duration, average saccadic amplitude, average saccadic velocity, average saccadic peak velocity, velocity waveform indicator (Q), scanpath length, scanpath area, regions of interest, inflection count, amplitude-duration coefficient, and main sequence coefficient. In 2012, Komogortsev et al. Described oculomotor plant characteristic (OPC) biometrics. OPC utilizes mathematical models of the oculomotor plant to estimate the non-visible anatomical properties of the eye from the measurable properties of eye movements. Feature vectors are compared between recordings using the Hotelling’s T−square test to obtain a measure of similarity. Biometric features vary according to the parameters of the oculomotor plant model employed. In 2013, Holland and Komogortsev, described complex eye movement behavior (CEM-B) biometrics. CEM-B compares the distribution of basic eye movement features throughout a recording using statistical techniques, such as the Kolmogorov-Smirnov test, to obtain a measure of similarity between recordings. Biometric features include: fixation start time, fixation duration, fixation centroid, saccade start time, saccade duration, saccadic amplitude, saccadic velocity, and saccadic peak velocity. In 2013, Komogortsev and Holland, described complex oculomotor behavior (COB) biometrics. COB examines the relative amount of corrective eye movements that occur in response to artifacts or otherwise aberrant behavior of the human visual system. Feature vectors are compared with a distance function to obtain a measure of similarity between recordings. Biometric features include: uncorrected, corrected, and multi-corrected saccadic dysmetria, express saccades, dynamic saccades, and compound saccades.
  8. 8. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com C. Motivation & Hypothesis The foundation for eye movement biometrics was formed in 1971, when Noton and Stark found that the eye movements exhibited by a subject during the initial viewing of a pattern were repeated in 65% of subsequent viewings. The potential biometric applications of eye movements were largely ignored, however, until 2004, when Kasprowski and Ober, applied voice recognition techniques to the eye movement signal. Over the past decade, the field of eye movement biometrics has expanded at a rapid pace, but there are still many aspects that lack definition. The potential liveness detection properties of human eye movements have yet to be investigated by rigorous experimentation. This paper builds on our previous research on the liveness detection properties of eye movement biometrics to include: 1) Additional models of the oculomotor plant; 2) An extended database of 173 living and artificial recordings; 3) Recordings conducted on equipment with properties resembling those of commercial iris recognition devices; 4) New statistical methods that allow for more accurate liveness detection; and 5) Additional forms of eye movement biometric.
  9. 9. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com CONCLUSION: This paper has investigated liveness detection techniques in the area of eye movement biometrics. We have investigated a specific scenario, in which an impostor constructs an artificial replica of the human eye. Two attack scenarios were considered, in which the imposter does and does not have direct access to the biometric database. Liveness detection was performed at the feature- and match score-levels for several existing eye movement biometric techniques. The results suggest that eye movement biometrics are highly resistant to circumvention by artificial recordings when liveness detection is performed at the feature-level. At the match score-level, the accuracy of liveness detection depends highly on the biometric techniques employed. These tests were repeated on high- and low-resolution recording devices, and while obvious degradation occurred at the match score-level, feature-level liveness detection achieved near perfect accuracy even at very low sampling rates. This suggests that eye movement biometrics could be employed on existing iris recognition devices to improve liveness detection capabilities.
  10. 10. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com REFERENCES: [1] A. Anjos and S. Marcel, “Counter-measures to photo attacks in face recognition: A public database and a baseline,” in Proc. Int. Joint Conf. Biometrics (IJCB), Washington, DC, USA, Oct. 2011, pp. 1–7. [2] X. Tan, Y. Li, J. Liu, and L. Jiang, “Face liveness detection from a single image with sparse low rank bilinear discriminative model,” in Computer Vision, K. Daniilidis, P. Maragos, and N. Paragios, Eds. Berlin, Germany: Springer-Verlag, 2010, pp. 504–517. [3] J. S. Agustin, H. Skovsgaard, J. P. Hansen, and D. W. Hansen, “Low-cost gaze interaction: Ready to deliver the promises,” in Proc. Conf. Human Factors Comput. (CHI), Boston, MA, USA, 2009, pp. 4453–4458. [4] O. V. Komogortsev, A. Karpov, C. D. Holland, and H. P. Proença, “Multimodal ocular biometrics approach: A feasibility study,” in Proc. IEEE 5th Int. Conf. Biometrics, Theory, Appl. Syst. (BTAS), Washington, DC, USA, Sep. 2012, pp. 1–8. [5] J. Galbally, J. Ortiz-Lopez, J. Fierrez, and J. Ortega-Garcia, “Iris liveness detection based on quality related features,” in Proc. 5th Int. Conf. Biometrics (ICB), New Delhi, India, Mar./Apr. 2012, pp. 271–276. [6] N. B. Puhan, N. Sudha, and A. Suhas Hegde, “A new iris liveness detection method against contact lens spoofing,” in Proc. IEEE 15th Int. Symp. Consum. Electron. (ISCE), Singapore, Jun. 2011, pp. 71–74. [7] H. Zhang, Z. Sun, and T. Tan, “Contact lens detection based on weighted LBP,” in Proc. Int. Conf. Pattern Recognit. (ICPR), Istanbul, Turkey, Aug. 2010, pp. 4279–4282.

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