Bad choices of passwords were and are a pervasive problem. Users choosing weak passwords do not only compromise themselves, but the whole ecosystem. E.g, common and default passwords in IoT devices were exploited by hackers to create botnets and mount severe attacks on large Internet services, such as the Mirai botnet DDoS attack. We present a method to help protect the Internet from such large scale attacks. Our method enables a server to identify popular passwords (heavy hitters), and publish a list of over-popular passwords that must be avoided. This filter ensures that no single password can be used to compromise a large percentage of the users. The list is dynamic and can be changed as new users are added or when current users change their passwords. We apply maliciously secure two-party computation and differential privacy to protect the users' password privacy. Our solution does not require extra hardware or cost, and is transparent to the user. Our private heavy hitters construction is secure even against a malicious coalition of devices which tries to manipulate the protocol to hide the popularity of some password that the attacker is exploiting. It also ensures differential privacy under continual observation of the blacklist as it changes over time. As a reality check we conducted three tests: computed the guarantees that the system provides wrt a few publicly available databases, ran full simulations on those databases, and implemented and analyzed a proof-of-concept on an IoT device. Our construction can also be used in other settings to privately learn heavy hitters in the presence of an active malicious adversary. E.g., learning the most popular sites accessed by the Tor network.
|Title of host publication||CCS 2019 - Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security|
|Publisher||Association for Computing Machinery|
|Number of pages||18|
|State||Published - 6 Nov 2019|
|Event||26th ACM SIGSAC Conference on Computer and Communications Security, CCS 2019 - London, United Kingdom|
Duration: 11 Nov 2019 → 15 Nov 2019
|Name||Proceedings of the ACM Conference on Computer and Communications Security|
|Conference||26th ACM SIGSAC Conference on Computer and Communications Security, CCS 2019|
|Period||11/11/19 → 15/11/19|
Bibliographical notePublisher Copyright:
© 2019 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
- Differential privacy
- Heavy hitters
- Malicious model
- Secure computation