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Tobias Länge

dblp:362/7460 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0009-3261-7017ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Web and mobile security · 77% Authentication and access control · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Web and mobile security
phishing
1.012026
Development, Evaluation, and Implementation of SEQR - a Usable Secure QR Code Scanner · CHI 2026
Authentication and access control
mobile authentication
0.312026
Development, Evaluation, and Implementation of SEQR - a Usable Secure QR Code Scanner · CHI 2026

Methods — techniques the papers use, named apart from their topics

systematic review · 1.0between-subjects study · 1.0
YearPublicationVenuePosition
2026 Development, Evaluation, and Implementation of SEQR - a Usable Secure QR Code Scanner
abstract
QR codes are widely used, but can become the vector of phishing attacks (QRishing). To support users, we systematically developed a usable secure QR code scanner, SEQR (Security Enhanced QR code scanner). We based the SEQR’s design on two systematic reviews: (i) of academic literature (2015–2025), identifying 96 papers on QRishing, and (ii) of the MITRE ATT&CK® Mobile repository, finding 36 QRishing techniques. From these two sources, we categorized 60 potential attacks, and divided them between those that SEQR addresses only at the technology level, and those where SEQR involves the users in the decision. We evaluated SEQR effectiveness in thwarting attacks in a between-subjects online study (n = 556), where SEQR achieved 93.35% correct answers, compared to 75.24% for the Apple iOS QR code scanner and 65.11% for the Samsung Android QR code scanner. We implemented SEQR as an open source Android application, available on GitHub.
Mattia Mossano, Maxime Veit, Tobias Länge, Benjamin Berens, Filipo Sharevski, Melanie Volkamer
CHI3
2026 Implementing and Evaluating the Usability of Reliable Voter Complaints in E2E Verifiable Remote Electronic Voting
Tobias Hilt, Christian Mack, Philipp Matheis, Benjamin Berens, Tobias Länge, Rolf Haenni, Reto E. Koenig, Philipp Locher, Melanie Volkamer
EuroS&P5