Sena Sahin (Georgia Institute of Technology), Burak Sahin (Georgia Institute of Technology), Frank Li (Georgia Institute of Technology)

Many online platforms monitor the account login activities of their users to detect unauthorized login attempts. Upon detecting anomalous activity, these platforms send suspicious login notifications to their users. These notifications serve to inform users about the login activity in sufficient detail for them to ascertain its legitimacy and take remedial actions if necessary. Despite the prevalence of these notifications, limited research has explored how users engage with them and how they can be effectively designed.

In this paper, we examine user engagement with email-based suspicious login notifications, focusing on real-world practices. We collect and analyze notifications currently in use to establish
an empirical foundation for common design elements. We focus our study on designs used by online platforms rather than exploring all possible design options. Thus, these design options
are likely supported by real-world online platforms based on the login data they can realistically provide. Then, we investigate how these design elements influence users to read the notification, validate its authenticity, diagnose the login attempt, and determine appropriate remedial steps. By conducting online semi-structured interviews with 20 US-based participants, we investigate their
past experiences and present them with design elements employed by top online platforms to identify what design elements work best. Our findings highlight the practical design options that
enhance users’ understanding and engagement, providing recommendations for deploying effective notifications and identifying future directions for the security community.

View More Papers

All your (data)base are belong to us: Characterizing Database...

Kevin van Liebergen (IMDEA Software Institute), Gibran Gomez (IMDEA Software Institute), Srdjan Matic (IMDEA Software Institute), Juan Caballero (IMDEA Software Institute)

Read More

The Discriminative Power of Cross-layer RTTs in Fingerprinting Proxy...

Diwen Xue (University of Michigan), Robert Stanley (University of Michigan), Piyush Kumar (University of Michigan), Roya Ensafi (University of Michigan)

Read More

Iris: Dynamic Privacy Preserving Search in Authenticated Chord Peer-to-Peer...

Angeliki Aktypi (University of Oxford), Kasper Rasmussen (University of Oxford)

Read More

AegisSat: A Satellite Cybersecurity Testbed

Roee Idan, Roy Peled, Aviel Ben Siman Tov, Eli Markus, Boris Zadov, Ofir Chodeda, Yohai Fadida (Ben Gurion University of the Negev), Oliver Holschke, Jan Plachy (T-Labs (Research & Innovation)), Yuval Elovici, Asaf Shabtai (Ben Gurion University of the Negev)

Read More