Machine-driven crowd-disambiguation of data resources

Abstract

Embodiments use crowd disambiguation techniques to protect the privacy of potentially sensitive client resources in web transactions. Crowd disambiguation servers can aggregate information about resources, such as URLs, accessed by clients, in the form of resource fingerprints submitted by the clients. Said resource fingerprints can be used to provide crowd-sourced services in a privacy-protected manner. For example, in some embodiments a fingerprint of a URL visited by a client can be communicated to the server as both a fully ambiguated resource instance (FARI) and a partially disambiguated resource instance (PDRI). When only one client, or a limited number of clients, has communicated a certain resource fmgerprint, the underlying identity of the resource, in this case the URL, remains obfuscated from the crowd disambiguation server, which lacks sufficient information to reconstruct it. As more clients communicate fmgerprints for the same resource (as identified, for example, by the FARIs), the corresponding PDRIs, which are different from client to client, enable the crowd disambiguation server to gradually reconstruct further portions of the resource, ultimately permitting the entire resource to be reconstructed. In that case, the resource is considered non-private, and can be further used e.g., in hint generation or other crowd-sourced services.