Memorability of cued-recall graphical passwords with saliency masks

Cued-recall graphical passwords have a lot of potential for secure user authentication, particularly if combined with saliency masks to prevent users from selecting weak passwords. Saliency masks were shown to significantly improve password security by excluding those areas of the image that are most likely to lead to hotspots. In this paper we investigate the impact of such saliency masks on the memorability of cued-recall graphical passwords. We first conduct two pre-studies (N=52) to obtain a set of images with three different image complexities as well as real passwords. A month-long user study (N=26) revealed that there is a strong learning effect for graphical passwords, in particular if defined on images with a saliency mask. While for complex images, the learning curve is steeper than for less complex ones, they best supported memorability in the long term, most likely because they provided users more alternatives to select memorable password points. These results complement prior work on the security of such passwords and underline the potential of saliency masks as both a secure and usable improvement to cued-recall gaze-based graphical passwords

Design Considerations for Multi-Stakeholder Display Analytics

Measuring viewer interactions through detailed analytics will be crucial to improving the overall performance of future open display networks. However, in contrast to traditional sign and web analytics systems, such display networks are likely to feature multiple stakeholders each with the ability to collect a subset of the required analytics information. Combining analytics data from multiple stakeholders could lead to new insights, but stakeholders may have limited willingness to share information due to privacy concerns or commercial sensitivities. In this paper, we provide a comprehensive overview of analytics data that might be captured by different stakeholders in a display network, make the case for the synthesis of analytics data in such display networks, present design considerations for future architectures designed to enable the sharing of display analytics information, and offer an example of how such systems might be implemented

Next generation physical analytics for digital signage

Traditional digital signage analytics are based on a display-centric view of the world, reporting data on the content shown augmented with frequency of views and possibly classification of the audience demographics. What these systems are unable to provide, are insights into viewers' overall experience of content. This is problematic if we want to understand where, for example, to place content in a network of physically distributed digital signs to optimise content exposure. In this paper we propose a new approach that combines mobility simulations with comprehensive signage analytics data to provide viewer-centric physical analytics. Our approach enables us to ask questions of the analytics from the viewer's perspective for the first time, including estimating the exposure of different user groups to specific content across the entire signage network. We describe a proof of concept implementation that demonstrates the feasibility of our approach, and provide an overview of potential applications and analytics reports

Audience monitor:an open source tool for tracking audience mobility in front of pervasive displays

Understanding an audience's behavior is an important aspect of evaluating display installations. In particular, it is important to understand how people move around in the vicinity of displays, including viewer transitions from noticing a display, through approach, to final use of the display. Despite the importance of measuring viewer mobility patterns, there are still relatively few low-cost tools that can be used with research display deployments to capture detailed spatial and temporal behavior of an audience. In this paper, we present an approach to audience monitoring that uses an off-the-shelf depth sensor and open source computer vision algorithms to monitor the space in front of a digital display, tracking presence and movements of both passers-by and display users. We believe that our approach can help display researchers evaluate their public display deployments and improve the level of quantitative data underpinning our field

Raising Awareness of IoT Sensor Deployments

The IoT is increasingly being used to support smart spaces and physical analytics and yet much of this smartness is made deliberately invisible to the user - echoing Weiser's vision of calm computing and technology that fades into the background. However, this means that users may not be aware or may not understand how the IoT is being deployed in their area. In other domains we know that a lack of awareness and a lack of understanding can lead to poor user experience and frustration, mistrust, suspicion, inability to capitalise on benefits and security vulnerabilities. In this paper, we present preliminary work that explores the issue of user awareness of IoT-based data collection

Demo: Tacita - A Privacy Preserving Public Display Personalisation Service

In this demonstration, we present a full implementation of Tacita, a display personalisation system designed to address viewer privacy concerns whilst still capable of providing relevant content to viewers and therefore increasing the value of displays

IoT Enabled Highways Maintenance:Towards an Understanding of Emerging Cyber Security Threats

IoT technologies are increasingly being deployed to support the operation and maintenance of complex highways infrastructure assets. However, the use of interconnected cyber-physical systems in such critical infrastructure raises important privacy, safety and security issues. While security issues in IoT transport systems and autonomous vehicles are well studied, there is minimal research relating to cyber security in the field of highways maintenance. In this paper, we introduce the problem domain, evidence the lack of existing research and provide example threats to IoT highways maintenance systems based on a real-world case study