A Security Analysis of Honey Vaults
Fei Duan, Ding Wang, Chunfu Jia
摘要
Honey encryption (HE) protected password vaults (called honey vaults) are promising tools that allow a user to store multiple passwords (called a password vault) and encrypt them with a master password using HE. In case password vaults are somehow leaked and the attackers launch offline password guessing, honey vaults can yield decoy password vaults for incorrect guesses, forcing an offline guessing attacker to interact with the authentication server to identify whether passwords in decrypted vaults are correct or not. Therefore, honey vaults transform the offline guessing attacker into an online guessing attacker, i.e., honey vault distinguishing attacker.In online guessing, attackers can adopt various attacks to perform multiple guesses against multiple vaults, but the existing theoretical message recovery (MR) security for HE only focuses on the advantage of one-time guess against a single vault, which cannot accurately model realistic attackers and thus can not provide practical advice for users’ vault security. To address this issue, we propose a theoretically-grounded optimal strategy for distinguishing attackers, and manage to derive a much tighter upper bound on the advantage against MR security. Particularly, we provide much tighter upper/lower bounds for advantage against HE-related cryptographic security games, i.e., the security of distribution transforming encoder (DTE), known message attack, and known side information attack. This provides a better understanding of the actual security of honey encryption.To better understand the security of honey vault systems, we instantiate our optimal strategy into three practical attacks and propose an encoding attack. Extensive experiments against two major honey vault systems demonstrate that our four attacks can improve the attack success rate by 1.15-4.35 times compared with their counterparts. For the intersection attack, we propose a feature attack against Cheng et al.’s incremental update mechanism (at USENIX SEC’21), and our attack can breach their mechanism with 87%-93% advantage.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- Practically Secure Honey Password Vaults: New Design and New Evaluation against Online GuessingHaibo Cheng, Fugeng Huang, Jiahong Yang, Wenting Li 等USENIX Security 2025
- Detecting Compromise of Passkey Storage on the CloudMazharul Islam, Sunpreet S. Arora, Rahul Chatterjee, Ke Coby WangUSENIX Security 2025
它引用的顶会 Paper15
- A Security Analysis of HoneywordsDing Wang, Haibo Cheng, Ping Wang, Jeff Yan 等NDSS 2018 · 被引用 1,102 次
- Targeted Online Password Guessing: An Underestimated ThreatDing Wang, Zijian Zhang, Ping Wang, Jeff Yan 等CCS 2016 · 被引用 385 次
- Fast, Lean, and Accurate: Modeling Password Guessability Using Neural NetworksWilliam Melicher, Blase Ur, Sean M. Segreti, Saranga Komanduri 等USENIX Security 2016 · 被引用 331 次
- Let's Go in for a Closer Look: Observing Passwords in Their Natural HabitatSarah Pearman, Jeremy Thomas, Pardis Emami Naeini, Hana Habib 等CCS 2017 · 被引用 168 次
- Who Are You? A Statistical Approach to Measuring User AuthenticityDavid Freeman, Sakshi Jain, Markus Dürmuth, Battista Biggio 等NDSS 2016 · 被引用 151 次
相关 Paper
- Incrementally Updateable Honey Password VaultsHaibo Cheng, Wenting Li, Ping Wang, Chao-Hsien Chu 等USENIX Security 2021 · 被引用 15 次
- How to Design Secure Honey Vault SchemesZhenduo Hou, Tingwei Fan, Fei Duan, Ding WangCCS 2025
- On the Security of Cracking-Resistant Password VaultsMaximilian Golla, Benedict Beuscher, Markus DürmuthCCS 2016 · 被引用 54 次
- Probability Model Transforming Encoders Against Encoding AttacksHaibo Cheng, Zhixiong Zheng, Wenting Li, Ping Wang 等USENIX Security 2019 · 被引用 12 次
- How to Attack and Generate HoneywordsDing Wang, Yunkai Zou, Qiying Dong, Yuanming Song 等S&P 2022 · 被引用 45 次
