Ke Coby Wang (UNC Chapel Hill), Michael K. Reiter (UNC Chapel Hill)

We present a framework by which websites can coordinate to make it difficult for users to set similar passwords at these websites, in an effort to break the culture of password reuse on the web today.
Though the design of such a framework is fraught with risks to users’ security and privacy, we show that these risks can be effectively mitigated through careful scoping of the goals for such a framework and through principled design. At the core of our framework is a private set-membership-test protocol that enables one website to determine, upon a user setting a password for use at it, whether that user has already set a similar password at another participating website, but with neither side disclosing to the other the password(s) it employs in the protocol. Our framework then layers over this protocol a collection of techniques to mitigate the leakage necessitated by such a test. We verify via probabilistic model checking that these techniques are effective in maintaining account security, and since these mechanisms are consistent with common user experience today, our framework should be unobtrusive to users who do not reuse similar passwords across websites (e.g., due to having adopted a password manager). Through a working implementation of our framework and optimization of its parameters based on insights of how passwords tend to be reused, we show that our design can meet the scalability challenges facing such a service.

View More Papers

Vault: Fast Bootstrapping for the Algorand Cryptocurrency

Derek Leung (MIT CSAIL), Adam Suhl (MIT CSAIL), Yossi Gilad (MIT CSAIL), Nickolai Zeldovich (MIT CSAIL)

Read More

IoTGuard: Dynamic Enforcement of Security and Safety Policy in...

Z. Berkay Celik (Penn State University), Gang Tan (Penn State University), Patrick McDaniel (Penn State University)

Read More

A Treasury System for Cryptocurrencies: Enabling Better Collaborative Intelligence

Bingsheng Zhang (Lancaster University), Roman Oliynykov (IOHK Ltd.), Hamed Balogun (Lancaster University)

Read More

Analyzing Semantic Correctness with Symbolic Execution: A Case Study...

Sze Yiu Chau (Purdue University), Moosa Yahyazadeh (The University of Iowa), Omar Chowdhury (The University of Iowa), Aniket Kate (Purdue University), Ninghui Li (Purdue University)

Read More