Touch paper presentation-tarek
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![Page 1: Touch paper presentation-tarek](https://reader035.fdocuments.in/reader035/viewer/2022062308/55c06ee3bb61ebf15c8b4660/html5/thumbnails/1.jpg)
IMPLICIT AUTHENTICATION SYSTEM FOR SMARTPHONES USERS BASED
ON TOUCH DATA
Presented by
Tarek Gaber Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt
IT4Invocation, VSB-TUO, Czech Republic
Co-authored by Reham Amin, Tarek Gaber, and Ghada ElTaweel
Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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OUTLINES
Introduction
The problem
Research Aim
Proposed Solution
Results and discussion
Conclusion and Future work
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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INTRODUCTION
Smartphones are currently used for:
• Sensitive and private information E.g.:
• Bank credential• Confidential emails• Other privacy issues
Gartner Says 30% of Organizations Will Use Biometric Authentication for Mobile Devices by 2016
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
Does traditional biometric authentication suitable for the smartphones?
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THE PROBLEM Smartphones are usually protected using unlock pattern which is subject to:
• Shoulder-surfing attack• Password remembering problem.
• Owner forgets his/her phone• any bystander can pick up the
smartphone, and sends SMS of business secrets to a competitor, and places it back
Resulted in identity theft and privacy violation
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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SOLUTION
Provides authentication system based on touch behavior of users
• The style of a user’s typing on phone.
• Such touch data are available in most smartphones
• Authenticates user without using any external hardware.
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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CHARACTERISTICS OF TOUCH DATA
It is biometrics, • so unique to an individual and difficult to imitate.
•
Non-visual cues for tapping behavior • So, it countermeasures the shoulder-surfing or smudge attacks
Last but not the least, such mechanism require no extra hardware and done implicitly.
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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PROPOSED MODELTheoretical framework
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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DATA COLLECTION: MOBILE APP
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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DATA COLLECTION: PARTICIPANTS
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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FEATURE EXTRACTION
Four features were considered • Size• Pressure• Time• XY Position
The above features are recorded while touching any key
• During the raw touch events(Up, Down and Move).
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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SAMPLE OF COLLECTED DATA
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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OWNER IDENTIFICATION
This was done through the classification phase
• SVM and KNN were used to differentiate between the Mobile's owner and the impostor.
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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RESULTS AND DISCUSSION
KNN classier using the Euclidean Distance was better than SVM.
Features of touch data were able to distinguish stroke behavior among users (discriminating users).
• Users with few times touching the soft keyboard (i.e. only 7 taps) can still be a rich source of data to distinguish among owner and impostor.
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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CONCLUSION AND FUTURE WORK
Implicit authentication could be a good solution to the problem of password or unhook pattern of smartphones
System for authenticating smartphone's users based on touch behavior was proposed
A dataset was collected from participates from different background and ages.
Users were classified using SVM with its 4 kernel functions and KNN classifiers.
It was found that KNN is better than the SVM with its 4 kernel functions .
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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FUTURE WORK
For the future work, we plan to • Collect more data by increasing the number of participates
• Try other classifiers, e.g. Random Linear Oracle.
ECC 2015: June 29 - July 1, Ostrava, Czech Republic
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Thanks For any question, contact:
ECC 2015: June 29 - July 1, Ostrava, Czech Republic