On the Security of Smartphone Unlock PINs

Author:

Markert Philipp1ORCID,Bailey Daniel V.1,Golla Maximilian2,Dürmuth Markus1,Aviv Adam J.3

Affiliation:

1. Ruhr University Bochum, Bochum, Germany

2. Max Planck Institute for Security and Privacy, Bochum, Germany

3. The George Washington University, Washington, District of Columbia, USA

Abstract

In this article, we provide the first comprehensive study of user-chosen four- and six-digit PINs ( n =1705) collected on smartphones with participants being explicitly primed for device unlocking. We find that against a throttled attacker (with 10, 30, or 100 guesses, matching the smartphone unlock setting), using six-digit PINs instead of four-digit PINs provides little to no increase in security and surprisingly may even decrease security. We also study the effects of blocklists, where a set of “easy to guess” PINs is disallowed during selection. Two such blocklists are in use today by iOS, for four digits (274 PINs) as well as six digits (2,910 PINs). We extracted both blocklists and compared them with six other blocklists, three for each PIN length. In each case, we had a small (four-digit: 27 PINs; six-digit: 29 PINs), a large (four-digit: 2,740 PINs; six-digit: 291,000 PINs), and a placebo blocklist that always excluded the first-choice PIN. For four-digit PINs, we find that the relatively small blocklist in use today by iOS offers little to no benefit against a throttled guessing attack. Security gains are only observed when the blocklist is much larger. In the six-digit case, we were able to reach a similar security level with a smaller blocklist. As the user frustration increases with the blocklists size, developers should employ a blocklist that is as small as possible while ensuring the desired security. Based on our analysis, we recommend that for four-digit PINs a blocklist should contain the 1,000 most popular PINs to provide the best balance between usability and security and for six-digit PINs the 2,000 most popular PINs should be blocked.

Funder

Research Training Group Human Centered Systems Security

Deutsche Forschungsgemeinschaft

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Safety, Risk, Reliability and Quality,General Computer Science

Reference61 articles.

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. “Someone Definitely Used 0000”: Strategies, Performance, and User Perception of Novice Smartphone-Unlock PIN-Guessers;Proceedings of the 2023 European Symposium on Usable Security;2023-10-16

2. Cybersecurity Practices of Rural Underserved Communities in Africa: A Case Study from Northern Namibia;2023 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD);2023-08-03

3. Machine Learning for PIN Side-Channel Attacks Based on Smartphone Motion Sensors;IEEE Access;2023

4. Co-CEP: A co-designed community engagement protocol as a catalyst for cybersecurity research in Africa: The case of northern Namibia;Journal of Information and Optimization Sciences;2023

5. User Perceptions of Five-Word Passwords;Proceedings of the 38th Annual Computer Security Applications Conference;2022-12-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3