Chi-en Amy Tai (University of Waterloo), Urs Hengartner (University of Waterloo), Alexander Wong (University of Waterloo)

Passwords are a ubiquitous form of authentication that is still present for many online services and platforms. Researchers have measured password creation policies for a multitude of websites and studied password creation behaviour for users who speak various languages. Evidence shows that limiting all users to alphanumeric characters and select special characters resulted in weaker passwords for certain demographics. However, password creation policies still concentrate on only alphanumeric characters and focus on increasing the length of passwords rather than the diversity of potential characters in the password. With the recent recommendation towards passphrases, further concerns arise pertaining to the potential consequences of not being inclusive in password creation. Previous work studying multilingual passphrase policies that combined English and African languages showed that multilingual passphrases are more user-friendly and also more difficult to guess than a passphrase based on a single language. However, their work only studied passphrases based on standard alphanumeric characters. In this paper, we measure the password strength of using a multilingual passphrase that contains characters outside of the standard alphanumeric characters and assess the availability of such multilingual passwords for websites with free account creation in the Tranco top 50 list and the Semrush top 20 websites in China list. We find that password strength meters like zxcvbn and MultiPSM surprisingly struggle with correctly assessing the strength of non-English-only passphrases with MultiPSM encountering an encoding issue with non-alphanumeric characters. In addition, we find that half of all tested valid websites accept multilingual passphrases but three websites struggled in general due to imposing a maximum password character limitation.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 40 [1] => 118 ) ) ) [post__not_in] => Array ( [0] => 20924 ) )

Unleashing the Power of Generative Model in Recovering Variable...

Xiangzhe Xu (Purdue University), Zhuo Zhang (Purdue University), Zian Su (Purdue University), Ziyang Huang (Purdue University), Shiwei Feng (Purdue University), Yapeng Ye (Purdue University), Nan Jiang (Purdue University), Danning Xie (Purdue University), Siyuan Cheng (Purdue University), Lin Tan (Purdue University), Xiangyu Zhang (Purdue University)

Read More

Vision: Retiring Scenarios — Enabling Ecologically Valid Measurement in...

Oliver D. Reithmaier (Leibniz University Hannover), Thorsten Thiel (Atmina Solutions), Anne Vonderheide (Leibniz University Hannover), Markus Dürmuth (Leibniz University Hannover)

Read More

insecure:// Vulnerability Analysis of URI Scheme Handling in Android...

Abdulla Aldoseri (University of Birmingham) and David Oswald (University of Birmingham)

Read More

Target-Centric Firmware Rehosting with Penguin

Andrew Fasano, Zachary Estrada, Luke Craig, Ben Levy, Jordan McLeod, Jacques Becker, Elysia Witham, Cole DiLorenzo, Caden Kline, Ali Bobi (MIT Lincoln Laboratory), Dinko Dermendzhiev (Georgia Institute of Technology), Tim Leek (MIT Lincoln Laboratory), William Robertson (Northeastern University)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)