TY - GEN
T1 - Incrementally updateable honey password vaults
AU - Cheng, Haibo
AU - Li, Wenting
AU - Wang, Ping
AU - Chu, Chao Hsien
AU - Liang, Kaitai
N1 - Funding Information:
The authors are grateful to the anonymous reviewers and the shepherd, David Freeman, for their invaluable comments that highly improve the completeness of the paper. We also give our special thanks to Qianchen Gu, Zhixiong Zheng, Jiahong Yang, Xiaoxi He and Jiahong Xie for their insightful suggestions and invaluable help. This research is supported by National Key R&D Program of China (2020YFB1805400), National Natural Science Foundation of China (62072010), and European Union's Horizon 2020 research and innovation programme under grant agreement No. 952697 (ASSURED).
Publisher Copyright:
© 2021 by The USENIX Association. All rights reserved.
PY - 2021
Y1 - 2021
N2 - Password vault applications allow a user to store multiple passwords in a vault and choose a master password to encrypt the vault. In practice, attackers may steal the storage file of the vault and further compromise all stored passwords by offline guessing the master password. Honey vaults have been proposed to address the threat. By producing plausible-looking decoy vaults for wrong master passwords, honey vaults force attackers to shift offline guessing to online verifications. However, the existing honey vault schemes all suffer from intersection attacks in the multi-leakage case where an old version of the storage file (e.g., a backup) is stolen along with the current version. The attacker can offline identify the decoys and completely break the schemes. We design a generic construction based on a multi-similar-password model and further propose an incremental update mechanism. With our mechanism, the attacker cannot get any extra advantages from the old storage, and therefore degenerates to an attacker only with knowledge of the current version. To further evaluate the security in the traditional single-leakage case where only the current version is stolen, we investigate the theoretically optimal strategy for online verifications, and propose practical attacks. Targeting the existing schemes, our attacks crack 33%-55% of real vaults via only one-time online guess and achieve 85%-94% accuracy in distinguishing real vaults from decoys. In contrast, our design reduces the values of the two metrics to 2% and 58% (close to the ideal values 0% and 50%), respectively. This indicates that the attackers needs to carry out 2.8x-7.5x online verifications to break our scheme.
AB - Password vault applications allow a user to store multiple passwords in a vault and choose a master password to encrypt the vault. In practice, attackers may steal the storage file of the vault and further compromise all stored passwords by offline guessing the master password. Honey vaults have been proposed to address the threat. By producing plausible-looking decoy vaults for wrong master passwords, honey vaults force attackers to shift offline guessing to online verifications. However, the existing honey vault schemes all suffer from intersection attacks in the multi-leakage case where an old version of the storage file (e.g., a backup) is stolen along with the current version. The attacker can offline identify the decoys and completely break the schemes. We design a generic construction based on a multi-similar-password model and further propose an incremental update mechanism. With our mechanism, the attacker cannot get any extra advantages from the old storage, and therefore degenerates to an attacker only with knowledge of the current version. To further evaluate the security in the traditional single-leakage case where only the current version is stolen, we investigate the theoretically optimal strategy for online verifications, and propose practical attacks. Targeting the existing schemes, our attacks crack 33%-55% of real vaults via only one-time online guess and achieve 85%-94% accuracy in distinguishing real vaults from decoys. In contrast, our design reduces the values of the two metrics to 2% and 58% (close to the ideal values 0% and 50%), respectively. This indicates that the attackers needs to carry out 2.8x-7.5x online verifications to break our scheme.
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M3 - Conference contribution
AN - SCOPUS:85114466477
T3 - Proceedings of the 30th USENIX Security Symposium
SP - 857
EP - 874
BT - Proceedings of the 30th USENIX Security Symposium
PB - USENIX Association
T2 - 30th USENIX Security Symposium, USENIX Security 2021
Y2 - 11 August 2021 through 13 August 2021
ER -