Oksana Kulyk (ITU Copenhagen), Willard Rafnsson (IT University of Copenhagen), Ida Marie Borberg, Rene Hougard Pedersen

Cookies are widely acknowledged as a potential privacy issue, due to their prevalence and use for tracking users across the web. To address this issue, multiple regulations have been enacted which mandate informing users about data collection via. so-called cookie notices. Unfortunately, these notices have been shown to be ineffective; they are largely ignored, and are generally not understood by end-users. One main source of this ineffectiveness is the presence of dark patterns in notice designs, i.e. user interface design elements that nudge users into performing an action they may not otherwise do, e.g. consent to data collection.

In this paper, we investigate the mental models and behavior of users when confronted with dark patterns in cookie notices. We do this by performing a mixed-method study (on Danes in their late-20s) which integrates quantitative and qualitative insights. Our quantitative findings confirm that the design of a cookie notice does influence the decisions of users on whether or not to consent to data collection, as well as whether they recall seeing the notice at all. Our qualitative findings reveal that users do in fact recognize the presence of dark patterns in cookie notice designs, and that they are very uncomfortable with standard practices in data collection. However, they seldom take action to protect their privacy, being overall resigned due to decision fatigue. We conclude that website maintainers need to reconsider how they request consent lest they alienate their users, and that end-users need better solutions that alleviate their burden wrt. protecting their privacy whilst visiting websites that collect data.

View More Papers

Demo #1: Security of Multi-Sensor Fusion based Perception in...

Yulong Cao (University of Michigan), Ningfei Wang (UC, Irvine), Chaowei Xiao (Arizona State University), Dawei Yang (University of Michigan), Jin Fang (Baidu Research), Ruigang Yang (University of Michigan), Qi Alfred Chen (UC, Irvine), Mingyan Liu (University of Michigan) and Bo Li (University of Illinois at Urbana-Champaign)

Read More

Demo #2: Policy-based Discovery and Patching of Logic Bugs...

Hyungsub Kim (Purdue University), Muslum Ozgur Ozmen (Purdue University), Antonio Bianchi (Purdue University), Z. Berkay Celik (Purdue University) and Dongyan Xu (Purdue University)

Read More

Towards a TEE-based V2V Protocol for Connected and Autonomous...

Mohit Kumar Jangid (Ohio State University) and Zhiqiang Lin (Ohio State University)

Read More

NSFuzz: Towards Efficient and State-Aware Network Service Fuzzing

Shisong Qin (Tsinghua University), Fan Hu (State Key Laboratory of Mathematical Engineering and Advanced Computing), Bodong Zhao (Tsinghua University), Tingting Yin (Tsinghua University), Chao Zhang (Tsinghua University)

Read More