MobiSys 2016

The 14th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2016) spanned a range of themes and domains, from smart environments to security and privacy. The highlights presented here cover the keynotes, paper sessions, and first Asian Students Symposium on Emerging Technologies

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

Poster: Understanding Mobile User Interactions with the IoT

The increasing reach of the Internet of Things (IoT) is leading to a world rich in sensors [3] that can be used to support physical analytics -- analogous to web analytics but targeted at user interactions with physical devices in the real-world (e.g. [2]). In contrast to web analytics, physical analytics systems typically only provide data relating to sensors and objects without consideration of individual users. This is mainly a consequence of an inability to track individual mobile user interactions across multiple physical objects (or across sessions of interaction with a single object) using, for example, an analogue of a web cookie. Indeed, such a "physical analytics cookie" could raise significant privacy concerns. However, in many cases a more "human-centric" approach to analytics would enable us to provide new and interesting insights into interactions between mobile users and the physical world [1]. In our work we endeavour to leverage synthetic user traces of human mobility, and data from real IoT systems, to provide such insights

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

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

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

Repurposing web analytics to support the IoT

Internet of Things analytics engines are complex to use and often optimized for a single domain or limited to proprietary data. A prototype system shows that existing Web analytics technologies can successfully be repurposed for IoT applications including sensor monitoring and user engagement tracking

Value-In-Context with Service Innovation in the Digital Age: A Service-Dominant Logic Perspective

The increasingly complex service context with the convergence of physical products, digitalization, and service offerings presents a major challenge for IS research on service innovation. This article addresses the resulting need for research on an adequate understanding of the perceived value of innovative digital services. It continues previous work that makes the first move in this regard—conceptualizing this value as the sum of direct value-in-context (S-D logic), and indirect and option value-in-context (both newly introduced). This article closes two research gaps. First, the option and indirect value-in-context components are clarified by developing propositions that link both to S-D logic’s main concepts of service innovation. Second, the value-in-context anatomy is empirically validated with two conjoint analyses. It can be shown that both newly introduced components of value-in-context indeed are decisive factors for customers’ perceptions of value with innovative digital services—implicating their conceptual separation