In this paper, we present DHTBL, an anti-spam blacklist built upon a novel secure distributed hash table (DHT). We show how DHTBL can be used to replace existing DNS-based blacklists (DNSBLs) of IP addresses of mail relays that forward spam. Implementing a blacklist on a DHT improves resilience to DoS attacks and secures message delivery, when compared to DNSBLs. However, due to the sensitive nature of the blacklist, storing the data in a peer-to-peer DHT would invite attackers to infiltrate the system. Typical DHTs can withstand fail-stop failures, but malicious nodes may provide incorrect routing information, refuse to return published items, or simply ignore certain queries. The neighborhoodwatch DHT is resilient to malicious nodes and maintains the O(logiV) bounds on routing table size and expected lookup time. NeighborhoodWatch depends on two assumptions in order to make these guarantees: (1) the existence of an on-line trusted authority that periodically contacts and issues signed certificates to each node, and (2) for every sequence of k + 1 consecutive nodes in the ID space, at least one is alive and non-malicious. We show how NeighborhoodWatch maintains many of its security properties even when the second assumption is violated. Honest nodes in NeighborhoodWatch can detect malicious behavior and expel the responsible nodes from the DHT.

Online social networks (OSNs) are immensely popular, with some claiming over 200 million users. Users share private content, such as personal information or photographs, using OSN applications. Users must trust the OSN service to protect personal information even as the OSN provider benefits from examining and sharing that information. We present Persona, an OSN where users dictate who may access their information. Persona hides user data with attribute-based encryption (ABE), allowing users to apply fine-grained policies over who may view their data. Persona provides an effective means of creating applications in which users, not the OSN, define policy over access to private data. We demonstrate new cryptographic mechanisms that enhance the general applicability of ABE. We show how Persona provides the functionality of existing online social networks with additional privacy benefits. We describe an implementation of Persona that replicates Facebook applications and show that Persona provides acceptable performance when browsing privacy-enhanced web pages, even on mobile devices.

Mapping the router topology is an important component of Internet measurement. Alias resolution, the process of mapping IP addresses to routers, is critical to accurate Internet mapping. Ally, a popular alias resolution tool, was developed to resolve aliases in individual ISPs, but its probabilistic accuracy and need to send O(n2) probes to infer aliases among n IP addresses make it unappealing for large-scale Internet mapping. In this paper, we present RadarGun, a tool that uses IP identifier velocity modeling to improve the accuracy and scalability of the Ally-based resolution technique. We provide analytical bounds on Ally's accuracy and validate our predicted aliases against Ally. Additionally, we show that velocity modeling requires only O(n) probes and thus scales to Internet-sized mapping efforts.