The Future of Enterprise Security with Regards to Mobile Technology and Applications

Book chapter

Tagoe, F. T. and Sharif, M. 2017. The Future of Enterprise Security with Regards to Mobile Technology and Applications. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.
AuthorsTagoe, F. T. and Sharif, M.
EditorsJahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad
Abstract

The utilisation of work assigned mobile technology by enterprise staff to chat and upload contents to the social media applications for personal use has become a key issue for a significant number of enterprises. This work aims to understand the trends amongst the users of work assigned phones when unknowingly downloading and using applications which could breach the security of the enterprise. In this paper; we assess current trends amongst employees and organisations’ use and trust of hybrid and web based social media applications used on a daily basis to communicate. This information is then evaluated alongside human related cyber security risks presented by such applications to provide instructions and advice on the management of social media application use within organisations in the Healthcare, Education and Energy sectors. The findings may be employed to develop a more robust cyber security strategy which focuses at reducing the user related risks.

KeywordsSocial media; Security; Mobile technology
Book titleGlobal Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings
Year2017
PublisherSpringer International Publishing
Publication dates
Print04 Jan 2017
Publication process dates
Deposited30 May 2017
Accepted2016
Series Communications in Computer and Information Science ISSN: 1865-0929
Event11th International Conference, ICGS3 2017
ISBN978-3-319-51063-7
978-3-319-51064-4
ISSN1865-0929
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-319-51064-4_25
Web address (URL)https://link.springer.com/chapter/10.1007/978-3-319-51064-4_25
Additional information

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-51064-4_25

JournalCommunications in Computer and Information Science
Journal citation630, pp. 321-330
Accepted author manuscript
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Ali, A., Glackin, C., Cannings, N., Wall, J., Sharif, S. and Moniri, M. 2019. A Framework for Augmented Reality Based Shared Experiences. Immersive Learning Research Network - iLRN. London, UK 23 - 27 Jun 2019 Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-657-4-24
A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images
Van Druten, J., Sharif, S., Chan, S. S., Chong, C. and Abdalla, H. 2019. A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images. IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19) . London Metropolitan University, London, UK 22 - 23 Aug 2019 IEEE. https://doi.org/10.1109/iCCECE46942.2019.8941615
Context-Aware Driver Distraction Severity Classification using LSTM Network
Fasanmade, A., Aliyu, S., He, Y., Al-Bayatti, A. H., Sharif, S. and Alfakeeh, A. S. 2019. Context-Aware Driver Distraction Severity Classification using LSTM Network. IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19) . London Metropolitan University, London, UK 22 - 23 Aug 2019 IEEE. pp. 147-152 https://doi.org/10.1109/iCCECE46942.2019.8941966
Predicting the Standard and Deviant Patterns In EEG Signals Based On Deep Learning Model
Sharif, S., Al-Bayatti, A. H. and Alfakeeh, A. S. 2019. Predicting the Standard and Deviant Patterns In EEG Signals Based On Deep Learning Model. IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19) . London Metropolitan University, London, UK 22 - 23 Aug 2019 IEEE. https://doi.org/10.1109/iCCECE46942.2019.8941730
Effect of PET Image Reconstruction Techniques on Unexpected Aorta Uptake
Hirji, H., Sullivan, K., Lasker, I., Sharif, S., Nunes, A., Shepherd, C., Wong, W. and Sanghera, B. 2019. Effect of PET Image Reconstruction Techniques on Unexpected Aorta Uptake. Molecular Imaging and Radionuclide Therapy. 28 (1), pp. 1-7. https://doi.org/10.4274/mirt.galenos.2018.88528
Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data
Ebenuwa, S., Sharif, M., Alazab, Mamoun and Al-Nemrat, A. 2019. Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data. IEEE Access. 7, pp. 24649-24666. https://doi.org/10.1109/ACCESS.2019.2899578
Medical data analysis based on Nao robot: An automated approach towards robotic real-time interaction with human body
Sharif, M. and Alsibai, Mohammed Hayyan 2018. Medical data analysis based on Nao robot: An automated approach towards robotic real-time interaction with human body. in: 2017 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) IEEE. pp. 91-96
A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis
van Druten, Jacqueline, Sharif, M., Khashu, Minesh and Abdalla, H. 2019. A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis. in: Miraz, Mahdi H., Exce, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 101-106
A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser
Alsallal, Muna, Sharif, M., Al-Ghzawi, Baydaa and al Mutoki, Sabah Mohammed Mlkat 2019. A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser. in: Miraz, Mahdi H., Excell, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 118-122
An Innovative EPW Design Using Add-on Features to Meet Malaysian Requirements
Alsibai, Mohammed Hayyan, Sharif, M., Yaakub, Salma and Hamran, Nurul Nadia Nor 2018. An Innovative EPW Design Using Add-on Features to Meet Malaysian Requirements. in: Proceedings of the 7th IEEE International Conference on Control Systems, Computing and Engineering (ICCSCE 2017) IEEE. pp. 180-185
An Effective TeleHealth Assistive System to Support Senior Citizen at Home or Care-Homes
Sharif, M., Alsallal, Muna and Herghelegiu, Lucian 2018. An Effective TeleHealth Assistive System to Support Senior Citizen at Home or Care-Homes. IEEE International Conference on Computing, Electronics & Communications Engineering 2018 (iCCECE '18). Southend, UK 16 - 17 Aug 2018 IEEE. pp. 113-117 https://doi.org/10.1109/iCCECOME.2018.8658877
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
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
Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles
Seuwou, Patrice, Banissi, Ebad, Ubakanma, George, Sharif, M. and Healey, Ann 2017. Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.
An efficient system for preprocessing confocal corneal images for subsequent analysis
Sharif, M., Qahwaji, Rami, Hayajneh, Sofyan, Ipson, Stanley, Alzubaidi, Rania and Brahma, Arun 2014. An efficient system for preprocessing confocal corneal images for subsequent analysis. in: 2014 14th UK Workshop on Computational Intelligence (UKCI) IEEE.
Artificial Neural Network-Based System for PET Volume Segmentation
Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2010. Artificial Neural Network-Based System for PET Volume Segmentation. International Journal of Biomedical Imaging. 2010 (105610). https://doi.org/10.1155/2010/105610
Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification
Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2012. Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification. Advances in Fuzzy Systems. 2012 (327861). https://doi.org/10.1155/2012/327861
Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study
Sharif, M., Abbod, Maysam, Sonoda, Luke I. and Sanghera, Bal 2013. Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study. British Journal of Applied Science & Technology. 4 (4), pp. 634-649. https://doi.org/10.9734/bjast/2014/5084
Preparation of 2D sequences of corneal images for 3D model building
Elbita, Abdulhakim, Qahwaji, Rami, Ipson, Stanley, Sharif, M. and Ghanchi, Faruque 2015. Preparation of 2D sequences of corneal images for 3D model building. Computer Methods and Programs in Biomedicine. 114 (2), pp. 194-205. https://doi.org/10.1016/j.cmpb.2014.01.009
Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images
Sharif, M., Qahwaji, R., Ipson, S. and Brahma, A. 2015. Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images. Applied Soft Computing. 36 (Nov.), pp. 269-282. https://doi.org/10.1016/j.asoc.2015.07.019
An efficient intelligent analysis system for confocal corneal endothelium images
Sharif, M., Qahwaji, R., Shahamatnia, E., Alzubaidi, R., Ipson, S. and Brahma, A. 2015. An efficient intelligent analysis system for confocal corneal endothelium images. Computer Methods and Programs in Biomedicine. 122 (3), pp. 421-436. https://doi.org/10.1016/j.cmpb.2015.09.003
In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study
Alzubaidi, Rania, Sharif, M., Qahwaji, Rami, Ipson, Stanley and Brahma, Arun 2015. In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study. British Journal of Ophthalmology. 100 (1), pp. 41-55. https://doi.org/10.1136/bjophthalmol-2015-306934
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