Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing

Article

Ehatisham-ul-Haq, M., Azam, Muhammad Awais, Naeem, U., Rѐhman, Shafiq Ur and Khalid, Asra 2017. Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing. Procedia Computer Science. 113, pp. 202-209. https://doi.org/10.1016/j.procs.2017.08.349
AuthorsEhatisham-ul-Haq, M., Azam, Muhammad Awais, Naeem, U., Rѐhman, Shafiq Ur and Khalid, Asra
Abstract

Smartphones are ubiquitous devices that enable users to perform many of their routine tasks anytime and anywhere. With the advancement in information technology, smartphones are now equipped with sensing and networking capabilities that provide context-awareness for a wide range of applications. Due to ease of use and access, many users are using smartphones to store their private data, such as personal identifiers and bank account details. This type of sensitive data can be vulnerable if the device gets lost or stolen. The existing methods for securing mobile devices, including passwords, PINs and pattern locks are susceptible to many bouts such as smudge attacks. This paper proposes a novel framework to protect sensitive data on smartphones by identifying smartphone users based on their behavioral traits using smartphone embedded sensors. A series of experiments have been conducted for validating the proposed framework, which demonstrate its effectiveness.

JournalProcedia Computer Science
Journal citation113, pp. 202-209
ISSN1877-0509
Year2017
PublisherElsevier
Publisher's version
License
CC BY-NC-ND
Digital Object Identifier (DOI)https://doi.org/10.1016/j.procs.2017.08.349
Web address (URL)https://doi.org/10.1016/j.procs.2017.08.349
Publication dates
Print19 Sep 2017
Publication process dates
Deposited05 Oct 2017
Copyright information© 2017 The Authors.
Permalink -

https://repository.uel.ac.uk/item/84q61

Log in to edit

Download files

Publisher's version
Procedia Computer Science 2017.pdf
License: CC BY-NC-ND

  • 183
    total views
  • 298
    total downloads
  • 2
    views this month
  • 1
    downloads this month

Export as

Related outputs

Tracking Functional Decline using Ambient Intelligence for Alzheimer's Patients
Lee, Sin Wee, Naeem, U., Anthony, Richard, Tawil, A., Azam, Muhammad Awais and Preston, David 2014. Tracking Functional Decline using Ambient Intelligence for Alzheimer's Patients. in: Dogru, Ali H. and Suh, Sang (ed.) Proceedings of the 19th International Conference on Transformative Science and Engineering, Business and Social Innovation Society for Design and Process Science. pp. 107-116
Inference of Activities with Unexpected Actions Using Pattern Mining
Nasreen, Shamila, Azam, Muhammad Awais, Naeem, U. and Ghazanfar, Mustansar Ali 2015. Inference of Activities with Unexpected Actions Using Pattern Mining. in: UbiComp/ISWC'15 Adjunct: Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 1479-1488
Inference of Hygiene Behaviours While Recognising Activities of Daily Living
Naeem, U., Tawil, Abdel-Rahman, Semelis, Ivans, Judah, Gaby and Aunger, Robert 2015. Inference of Hygiene Behaviours While Recognising Activities of Daily Living. in: Mansoor, Wathiq, Maamar, Zakaria and Rabhi, Fethi (ed.) ICCASA '14: Proceedings of the 3rd International Conference on Context-Aware Systems and Applications ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering). pp. 154-161
Neural Predictors of Gait Stability When Walking Freely in the Real-World.
Pizzamiglio, S., Abdalla, H., Naeem, U. and Turner, D. 2018. Neural Predictors of Gait Stability When Walking Freely in the Real-World. Journal of NeuroEngineering and Rehabilitation. 15 (11). https://doi.org/10.1186/s12984-018-0357-z
Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network
Sharif, M., Naeem, U., Islam, S. and Karami, A. 2018. Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network. Arai, Kohei, Kapoor, Supriya and Bhatia, Rahul (ed.) Intelligent Systems Conference (IntelliSys) 2018. London, UK 06 - 07 Sep 2018 Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_34
The Application of a Semantic-Based Process Mining Framework on a Learning Process Domain
Okoye, Kingsley, Islam, S., Naeem, U., Sharif, M., Azam, Muhammad Awais and Karami, A. 2018. The Application of a Semantic-Based Process Mining Framework on a Learning Process Domain. Arai, Kohei, Kapoor, Supriya and Bhatia, Rahul (ed.) Intelligent Systems Conference (IntelliSys) 2018. London, UK 06 - 07 Sep 2018 Springer, Cham. https://doi.org/10.1007/978-3-030-01054-6_96
Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing
Ehatisham-ul-Haq, Muhammad, Azam, Muhammad Awais, Loo, Jonathan, Shuang, Kai, Islam, S., Naeem, U. and Amin, Yasar 2017. Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing. Sensors. 17 (9), p. 2043. https://doi.org/10.3390/s17092043
Taskification – Gamification of Tasks
Naeem, U., Islam, S., Sharif, M., Sudakov, Sergey and Azam, Awais 2017. Taskification – Gamification of Tasks. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 631-634
SignalSense - Towards Quality Service
Islam, S., Sharif, M., Naeem, U. and Geehan, James 2017. SignalSense - Towards Quality Service. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 627-630
CrimeSafe - Helping you stay safe
Islam, S., Naeem, U., Sharif, M. and Dovnarovic, Arnold 2017. CrimeSafe - Helping you stay safe. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 642-645
Neural correlates of single- and dual-task walking in the real world
Pizzamiglio, Sara, Naeem, U., Abdalla, H. and Turner, D. 2017. Neural correlates of single- and dual-task walking in the real world. Frontiers in Human Neuroscience. 11, p. Art 460. https://doi.org/10.3389/fnhum.2017.00460
Recognizing activities of daily living from patterns and extraction of web knowledge
Ihianle, I., Naeem, U., Tawil, A. and Azam, Muhammad Awais 2016. Recognizing activities of daily living from patterns and extraction of web knowledge. in: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp '16 New York, NY, USA Association for Computing Machinery (ACM). pp. 1255-1262
Using semantic-based approach to manage perspectives of process mining: Application on improving learning process domain data
Kingsley, Okoye, Tawil, Abdel-Rahman H., Naeem, U., Islam, S. and Lamine, Elyes 2017. Using semantic-based approach to manage perspectives of process mining: Application on improving learning process domain data. in: 2016 IEEE International Conference on Big Data (Big Data) IEEE. pp. 3529-3538
Inference Engine Based on a Hierarchical Structure for Detecting Everyday Activities within the Home
Naeem, U., Tawil, A., Semelis, Ivans, Azam, Muhammad Awais and Ghazanfar, Mustansar Ali 2017. Inference Engine Based on a Hierarchical Structure for Detecting Everyday Activities within the Home. in: Bi, Yaxin, Kapoor, Supriya and Bhatia, Rahul (ed.) Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 Springer, Cham. pp. 969-986
Integration operators for generating RDF/OWL-based user defined mediator views in a grid environment
Tawil, Abdel-Rahman H., Taweel, Adel, Naeem, U., Montebello, Matthew, Bashroush, R. and Al-Nemrat, A. 2014. Integration operators for generating RDF/OWL-based user defined mediator views in a grid environment. Journal of Intelligent Information Systems. 43 (1), pp. 1-32. https://doi.org/10.1007/s10844-013-0300-5
A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis
Okoye, Kingsley, Tawil, A., Naeem, U. and Lamine, Elyes 2015. A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis. in: Pillay, Nelishia, Engelbrecht, Andries P., Abraham, Ajith, Plessis, Mathys C. du, Snášel, Václav and Muda, Azah Kamilah (ed.) Advances in Nature and Biologically Inspired Computing Cham, Switzerland Springer International Publishing.
A dynamic segmentation based activity discovery through topic modelling
Kennedy, Ihianle Isibor, Naeem, U. and Tawil, A. 2016. A dynamic segmentation based activity discovery through topic modelling. in: IET International Conference on Technologies for Active and Assisted Living (TechAAL) IEEE.
Semantic-Based Model Analysis Towards Enhancing Information Values of Process Mining: Case Study of Learning Process Domain
Okoye, Kingsley, Tawila, Abdel-Rahman H., Naeem, U., Islam, S. and Lamine, Elyes 2017. Semantic-Based Model Analysis Towards Enhancing Information Values of Process Mining: Case Study of Learning Process Domain. in: Abraham, Ajith, Cherukuri, Aswani Kumar, Madureira, Ana Maria and Muda, Azah Kamilah (ed.) Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) Springer, Cham.
High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation
Pizzamiglio, Sara, De Lillo, Martina, Naeem, U., Abdalla, Hassan and Turner, D. 2017. High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation. Frontiers in Physiology. 7 (668), pp. 1-14. https://doi.org/10.3389/fphys.2016.00668
A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing
Pizzamiglio, S., Naeem, U., ur Réhman, Shafiq, Sharif, M., Abdalla, H. and Turner, D. 2017. A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing. Procedia Computer Science. 113, pp. 89-96. https://doi.org/10.1016/j.procs.2017.08.297
Recognition of Activities of Daily Living from Topic Model
Ihianle, I., Naeem, U. and Tawil, A. 2016. Recognition of Activities of Daily Living from Topic Model. Procedia Computer Science. 98, pp. 24-31. https://doi.org/10.1016/j.procs.2016.09.007
Recognition Framework for Inferring Activities of Daily Living Based on Pattern Mining
Nasreen, Shamila, Azam, Muhammad Awais, Naeem, U., Ghazanfar, Mustansar Ali and Khalid, Asra 2016. Recognition Framework for Inferring Activities of Daily Living Based on Pattern Mining. Arabian Journal for Science and Engineering. 41 (8), pp. 3113-3126. https://doi.org/10.1007/s13369-016-2091-9
Activities of daily life recognition using process representation modelling to support intention analysis
Naeem, U., Bashroush, R., Anthony, Richard, Azam, Muhammad Awais, Tawil, Abdel Rahman, Lee, S. and Mou-Ling, Dennis 2015. Activities of daily life recognition using process representation modelling to support intention analysis. International Journal of Pervasive Computing and Communications. 11 (3), pp. 347-371. https://doi.org/10.1108/IJPCC-01-2015-0002
Novel centroid selection approaches for KMeans-clustering based recommender systems
Zahra, Sobia, Ghazanfar, Mustansar Ali, Khalid, Asra, Azam, Muhammad Awais, Naeem, U. and Prugel-Bennett, Adam 2015. Novel centroid selection approaches for KMeans-clustering based recommender systems. Information Sciences. 320, pp. 156-189.
Semantic Process Mining Towards Discovery and Enhancement of Learning Model Analysis
Okoye, Kingsley, Tawil, Abdel Rahman H., Naeem, U. and Lamine, Elyes 2015. Semantic Process Mining Towards Discovery and Enhancement of Learning Model Analysis. in: 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems IEEE. pp. 363-370
A Semantic Rule-based Approach Supported by Process Mining for Personalised Adaptive Learning
Okoye, Kingsley, Tawil, A., Naeem, U., Bashroush, Rabih and Lamine, Elyes 2014. A Semantic Rule-based Approach Supported by Process Mining for Personalised Adaptive Learning. Procedia Computer Science. 37, pp. 203-210.
Frequent Pattern Mining Algorithms for Finding Associated Frequent Patterns for Data Streams: A Survey
Nasreen, Shamila, Azam, Muhammad Awais, Shehzad, Khurram, Naeem, U. and Ghazanfar, Mustansar Ali 2014. Frequent Pattern Mining Algorithms for Finding Associated Frequent Patterns for Data Streams: A Survey. Procedia Computer Science. 37, pp. 109-116.
Statistical Sampling Approach to Investigate Child Pornography Cases
Sarantinos, N., Al-Nemrat, A. and Naeem, U. 2013. Statistical Sampling Approach to Investigate Child Pornography Cases. 2013 Fourth Cybercrime and Trustworthy Computing Workshop (CTC). Sydney NSW, Australia 21 - 22 Nov 2013 IEEE. https://doi.org/10.1109/CTC.2013.14
A Framework to Recognise Daily Life Activities with Wireless Proximity and Object Usage Data
Azam, M.A., Loo, J., Naeem, U., Khan, S.K.A., Lasebae, A. and Gemikonakli, O. 2012. A Framework to Recognise Daily Life Activities with Wireless Proximity and Object Usage Data. in: Proceedings of 23rd IEEE International Symposium on Personal, Indoor and Mobile Radio Communication 2012 IEEE. pp. 590-595
Behavioural Patterns Analysis of Low Entropy People Using Proximity Data
Azam, M.A., Loo, J., Khan, S.K.A., Naeem, U., Adeel, M. and Ejaz, Waleed 2012. Behavioural Patterns Analysis of Low Entropy People Using Proximity Data. Innovative Information Science & Technology Research Group.
A Comparison of Two Hidden Markov Approaches to Task Identification in the Home Environment
Naeem, U. and Bigham, John 2007. A Comparison of Two Hidden Markov Approaches to Task Identification in the Home Environment. Proceedings of the 2nd International Conference on Pervasive Computing and Applications, Birmingham, UK, 2007, pp. 383-388
Recognising Activities of Daily Life Using Hierarchical Plans
Naeem, U., Bigham, John and Wang, Jinfu 2007. Recognising Activities of Daily Life Using Hierarchical Plans. Proceedings of the 2nd European Conference on Smart Sensing and Context, LNCS 4793, Lake District, UK, 2007, pp. 175-189
A Hierarchal Approach to Activity Recognition in the Home Environment based on Object Usage
Naeem, U. and Bigham, John 2008. A Hierarchal Approach to Activity Recognition in the Home Environment based on Object Usage. Proceedings of the 2008 Networking and Electronic Commerce Research Conference (NAEC 2008), Lake Garda, Italy, 2008, pp. 48-54
Recognising Activities of Daily Life through the Usage of Everyday Objects around the Home
Naeem, U. and Bigham, John 2009. Recognising Activities of Daily Life through the Usage of Everyday Objects around the Home. Proceedings of the 3rd International Conference on Pervasive Computing Technologies for Healthcare. Technologies to Counter Cognitive Decline Workshop London
Activity Recognition using a Hierarchical Framework
Naeem, U. and Bigham, John 2008. Activity Recognition using a Hierarchical Framework. Proceedings of the 2nd International Conference on Pervasive Computing Technologies for Healthcare, Ambient Technologies for Diagnosing and Monitoring Chronic Patients Workshop, Tampere, Finland, 2008, IEEE pp. 24-27