Mr Neamah Al-Naffakh
Brief biographical email@example.com
Wearable Computing and Transparent Authentication
Over 7.7 billion people currently utilise mobile devices for personal communication (i.e. call, text), with increasing access to sensitive information from financial, health-related and corporate services. Therefore, securing this information from unauthorized access in an effective and useable fashion is essential. However, current user authentication approaches are intrusive which impacts their usability and subsequently security (as user’s seek to circumvent them). Transparent and continuous authentication was proposed over 15 years ago to removes the inconvenience of authenticating the user through capturing the samples non-intrusively. A significant amount of research has been completed in the domain, with studies focussing upon the development of transparent-enabled biometric modalities and the design of “intelligent” multi-biometric systems to support the underlying technique. However, they still have weakness in term of performance due to the focus upon behavioural biometrics and instability in external factors (such as environment). Whilst previous research in transparent authentication system (TAS) has been focussed upon its application with computer and mobile devices, little attention has been given to the use of wearable devices – which tend to be sensor-rich highly personal technologies. This research proposes to investigate the role wearable computing devices (such as Smart Watches) in strengthening transparent authentication.Mr Neamah Al-Naffakh
The MPhil stage will focus upon exploring and evaluating the current state of the art in biometric based authentication focusing upon their use within mobile devices and their applicability in the context of wearable computing. In addition, this stage will involve investigating the multiple sensor data available in smart-watches (such as accelerometer and gyroscope) and evaluate their usefulness within a Transparent Authentication System (TAS).
Director of studies: Prof. Nathan L Clarke
Other supervisors: Dr Paul S Haskell-Dowland, Dr Fudong Li
A Comprehensive Evaluation of Feature Selection for Gait Recognition Using Smartwatches
1 Journal papers
Unobtrusive Gait Recognition Using Smartwatches
Activity Recognition using wearable computing
2 Conference papers
3 publication(s) - all categories.