Security Benefits of Little Data From the Socio-Technical Perspective

Security Benefits of Little Data From the Socio-Technical Perspective

Peter Imrie (University of Portsmouth, Portsmouth, UK) and Peter M. Bednar (University of Portsmouth, Portsmouth, UK)
Copyright: © 2018 |Pages: 9
DOI: 10.4018/IJSS.2018010104
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As organisations are further developing ways to extract value from big data, the amount of personal data being stored in centralised systems is rising. These large data sets are becoming prime targets for hackers as well as raising concerns about end user privacy with how the data is handled. Virtual Personal Assistants (VPA) that use the Little Data approach of keeping data within the control of the end user have the potential to mitigate these risks due to its decentralised nature. Within this article the authors discuss the potential security benefits from the Socio-Technical Perspective of utilising a VPA as a supporting technology for controlling an individual's personal data.
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Data Handling

This section will begin by explaining what a VPA is and expanding on its functionality, which may allow e users to retain the benefits of data analytics without giving control over to external stakeholders. It will then explore the value that organizations can extract from the data collected from individuals from the perspective of Big Data. Following this there will be a discussion on a VPA’s approach to data control and Little Data, where the focus is on protecting the data of the user rather than collecting it for external stakeholders.

VPAs are supporting systems that utilise natural language processing, simulated emotions and learning capabilities to engage the user in conversation. The interaction between VPA and user will allow the VPA to gather more data and create metadata by relating what it is receiving as an input to data it has already stored. While interacting with an individual a VPA would be able to develop a personal relationship with the user by producing metadata and tailor its outputs to provide responses that are contextually relevant to the user. This relationship between user and system allows for each to learn from the other and explore a subject through interaction, both continually evolving to better interact with the other. Similar technologies to this already exist in the forms of Apple’s Siri, Microsoft’s Cortana and Amazon’s Alexa, but these systems are primarily acting to benefit the company that owns them. This results in the data and data analytics being owned by the organization rather than the user, and the support provided by the tool being generalised to a demographic of user, rather than focusing on the context of that particular individual.

Large technology-based organizations such as Google are utilising data analytics to improve their interaction with users. By gathering large amounts of data on individuals a Big Data approach can be utilised by service providers to better tailor their interactions with different categories of user. Data analytics can identify trends between users with similar interests and can infer additional information about individuals’ behaviour, tastes and preferences.

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