Mobile phones & behavioral modalities: Surveying users' practices

Mobile phones are one of the most popular means of access to the internet. Users, via the telephone, connect to different services such as: Google, social networks, work accounts, banks accounts, etc. Those services, are many times, left open in their device. This enables risks, such as, loss or/and the violation of their personal data. In addition, in case of device theft after login, full access to sensitive data and applications may be fully granted. The purpose of this research is to analyze the most salient patterns characterizing user practices regarding certain behavioral modalities including: the way of using the various applications, power consumption, touch gestures and guest users' habits. To this end, we used an original questionnaire, created for the needs of the specific survey, to examine whether we can find some trends among the users. This can give us a qualitative information, for the different behaviors / "characters" of users, in order to be used in further research regarding User's Continuous Authentication.

[1]  Iosif Androulidakis,et al.  Surveying users' practices regarding mobile phones' security features , 2009 .

[2]  Steven Furnell,et al.  Beyond the PIN: Enhancing user authentication for mobile devices , 2008 .

[3]  Markus Jakobsson,et al.  Implicit Authentication through Learning User Behavior , 2010, ISC.

[4]  Gokhan Memik,et al.  Into the wild: Studying real user activity patterns to guide power optimizations for mobile architectures , 2009, 2009 42nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[5]  Steven Furnell,et al.  Authentication of users on mobile telephones - A survey of attitudes and practices , 2005, Comput. Secur..

[6]  Dawn Xiaodong Song,et al.  Touchalytics: On the Applicability of Touchscreen Input as a Behavioral Biometric for Continuous Authentication , 2012, IEEE Transactions on Information Forensics and Security.

[7]  Eunjin Kim,et al.  A Novel Biometric Identification Based on a User’s Input Pattern Analysis for Intelligent Mobile Devices , 2012 .

[8]  Xiang-Yang Li,et al.  Continuous user identification via touch and movement behavioral biometrics , 2014, 2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC).

[9]  Steven Furnell,et al.  Multi-modal Behavioural Biometric Authentication for Mobile Devices , 2012, SEC.

[10]  D. Dillman.  Mail and internet surveys: The tailored design method, 2nd ed. , 2007 .

[11]  Elena Zaitseva,et al.  Smart phone users: Are they green users? , 2014, The 10th International Conference on Digital Technologies 2014.

[12]  G. Padmavathi,et al.  Mobile Device Security: A Survey on Mobile Device Threats, Vulnerabilities and their Defensive Mechanism , 2012 .

[13]  Sheikh Iqbal Ahamed,et al.  ePet: when cellular phone learns to recognize its owner , 2009, SafeConfig '09.