The Tor Darknet is a pseudo-anonymous place to host content online frequently used by criminals to sell narcotics and to distribute illicit material. Many studies have attempted to estimate the size of the darknet, but this paper will show that previous estimates on size are inaccurate due to hidden service lifecycle. The first examination of its kind will be presented on the differences between short-lived and long-lived hidden services. Finally, in light of a new Tor protocol for the darknet which will prevent the running of relays to learning darknet sites, an analysis is presented of the use of crawling and whether this is an effective mechanism to discover sites for law enforcement.

Motivated by the effectiveness of correlation attacks against Tor, the censorship arms race, and observations of malicious relays in Tor, we propose that Tor users capture their trust in network elements using probability distributions over the sets of elements observed by network adversaries. We present a modular system that allows users to efficiently and conveniently create such distributions and use them to improve their security. To illustrate this system, we present two novel types of adversaries. First, we study a powerful, pervasive adversary that can compromise an unknown number of Autonomous System organizations, Internet Exchange Point organizations, and Tor relay families. Second, we initiate the study of how an adversary might use Mutual Legal Assistance Treaties (MLATs) to enact surveillance. As part of this, we identify submarine cables as a potential subject of trust and incorporate data about these into our MLAT analysis by using them as a proxy for adversary power. Finally, we present preliminary experimental results that show the potential for our trust framework to be used by Tor clients and services to improve security.

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