Reference number : GC-2017-Q3-00619, amendment number : , agreement type : G, recipient legal name : Samet, Saeed (University of Windsor), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Traditional access control systems that rely on static or fixed-point authentication are considered insecure and_x000D_
not suitable for mission-critical systems, especially when the users share their credentials, even when the_x000D_
security policies in place forbid those behaviours. Without continually checking that "you are who you claim_x000D_
you are", a potential security breach is almost certain to happen at some point. To solve this challenges with_x000D_
HCI touch screen data our approach will focus on investigating the available HCI touch screen datasets and_x000D_
validate their fitness for identity recognition and verification. After studying the touchscreen interaction data,_x000D_
we will focus on engineering relevant features to describe the unique behaviours of the user while interacting_x000D_
with touchscreen. We will investigate different feature selection and extraction techniques to identify the best_x000D_
features for identity verification. The next stage will focus on evaluating pattern classification algorithms that_x000D_
require positive training only (e.g. artificial immune system) to identify the most promising algorithm for_x000D_
novelty detection. Finally, we will propose an architecture for a non-intrusive continuous authentication. The_x000D_
expected outcome of the project includes the following:_x000D_
1. Evaluate the effectiveness of using touchscreen data for continuous authentication._x000D_
2. Engineering features for pattern classifications from touchscreen interaction data_x000D_
3. Design a new non-intrusive continuous authentication model based on touch screen data., program purpose french : Traditional access control systems that rely on static or fixed-point authentication are considered insecure and_x000D_
not suitable for mission-critical systems, especially when the users share their credentials, even when the_x000D_
security policies in place forbid those behaviours. Without continually checking that "you are who you claim_x000D_
you are", a potential security breach is almost certain to happen at some point. To solve this challenges with_x000D_
HCI touch screen data our approach will focus on investigating the available HCI touch screen datasets and_x000D_
validate their fitness for identity recognition and verification. After studying the touchscreen interaction data,_x000D_
we will focus on engineering relevant features to describe the unique behaviours of the user while interacting_x000D_
with touchscreen. We will investigate different feature selection and extraction techniques to identify the best_x000D_
features for identity verification. The next stage will focus on evaluating pattern classification algorithms that_x000D_
require positive training only (e.g. artificial immune system) to identify the most promising algorithm for_x000D_
novelty detection. Finally, we will propose an architecture for a non-intrusive continuous authentication. The_x000D_
expected outcome of the project includes the following:_x000D_
1. Evaluate the effectiveness of using touchscreen data for continuous authentication._x000D_
2. Engineering features for pattern classifications from touchscreen interaction data_x000D_
3. Design a new non-intrusive continuous authentication model based on touch screen data., agreement title english : Continuous Proof of Presence based on Touchscreen Devices Interactions and Signals, agreement title french : Continuous Proof of Presence based on Touchscreen Devices Interactions and Signals, agreement number : EGP, agreement value : 24500.0, agreement start date : 2017-12-13, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada