Visible to the public Biblio

Filters: Author is Chowdhury, Soumyadeb  [Clear All Filters]
2017-10-25
Chowdhury, Soumyadeb, Ferdous, Md Sadek, Jose, Joemon M.  2016.  Exploring Lifelog Sharing and Privacy. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct. :553–558.

The emphasis on exhaustive passive capturing of images using wearable cameras like Autographer, which is often known as lifelogging has brought into foreground the challenge of preserving privacy, in addition to presenting the vast amount of images in a meaningful way. In this paper, we present a user-study to understand the importance of an array of factors that are likely to influence the lifeloggers to share their lifelog images in their online circle. The findings are a step forward in the emerging area intersecting HCI, and privacy, to help in exploring design directions for privacy mediating techniques in lifelogging applications.

Ferdous, Md Sadek, Chowdhury, Soumyadeb, Jose, Joemon M.  2016.  Privacy Threat Model in Lifelogging. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct. :576–581.

The lifelogging activity enables a user, the lifelogger, to passively capture multimodal records from a first-person perspective and ultimately create a visual diary encompassing every possible aspect of her life with unprecedented details. In recent years it has gained popularity among different groups of users. However, the possibility of ubiquitous presence of lifelogging devices especially in private spheres has raised serious concerns with respect to personal privacy. Different practitioners and active researchers in the field of lifelogging have analysed the issue of privacy in lifelogging and proposed different mitigation strategies. However, none of the existing works has considered a well-defined privacy threat model in the domain of lifelogging. Without a proper threat model, any analysis and discussion of privacy threats in lifelogging remains incomplete. In this paper we aim to fill in this gap by introducing a first-ever privacy threat model identifying several threats with respect to lifelogging. We believe that the introduced threat model will be an essential tool and will act as the basis for any further research within this domain.