Critical visualization: a case for rethinking how we visualize risk and security

Abstract

In an era of high-profile hacks, information leaks and cybercrime, cybersecurity is the focus of much corporate and state-funded research. Data visualization is regarded as an important tool in the detection and prediction of risk and vulnerability in cybersecurity, but discussion tends to remain at the level of the usability of visualization tools and how to reduce the cognitive load on the consumers of the visualizations. This focus is rooted in a desire to simplify the complexity of cybersecurity. This article argues that while usability and simplification are important goals for the designers of visualizations, there is a much wider discussion that needs to take place about the underlying narratives upon which these visualizations are based. The authors take the position that the narratives on which cybersecurity visualizations are based ignore important aspects of cybersecurity and that their visual form causes the producers and users of these visualizations to focus too narrowly on adversarial security issues, ignoring important aspects of social and community-based security. By situating the discussion of security visualization in a larger socio-historical context, the limitations and implications of current ways of seeing risk become more apparent. Cybersecurity might also learn from other disciplines, specifically critiques of artificial intelligence and the discourse and methods of post-war urban planning. In this way, the article follows a humanities tradition of situating the focus of analysis in a broader tradition of scholarship and critiquing current practices from this wider context. The purpose of such critique is to stimulate reflection on underlying principles and the implications of different approaches to operationalizing those principles. Finally, case studies of participatory modelling and crowdsourcing projects are discussed that aim to foster resilience through social and spatial practices. These case studies illustrate the potential for a wider range of visualizations.