Insight into user experience and behavior is critical to the success of large software systems and web services. Gaining such insights, while preserving user privacy, is a significant challenge. Recent advancements in multi-party computation have made it practical to securely compute aggregates over secret shared data. Two such protocols have emerged as candidates for standardization at IETF: Prio (NSDI 2017) for general-purpose statistics; and Poplar (IEEE S&P 2021) for heavy hitters, where the goal is to compute the most popular inputs held by users without learning the inputs themselves. While each of these protocols is well-suited to certain applications, there remain a number of use cases identified by IETF for which neither Prio nor Poplar is practical. We introduce Mastic, a protocol for the following functionality: each of a large number of clients holds an input (e.g., a URL) and its corresponding weight (e.g., page load time); for a given candidate input (or prefix), a small number of non-colluding servers wish to securely aggregate the weights of clients that hold that input (or some input with that prefix), without learning the weights or which client holds which input. This functionality makes two new classes of applications possible. The first is a natural generalization of heavy hitters we call weighted heavy-hitters. The second is an enhancement of Prio-style metrics we call attribute-based metrics in which aggregates are grouped by hierarchical user attributes (e.g., their geographic location or software version). We demonstrate Mastic's practicality for these applications with a real-world example of each. We also compare our protocol with Prio and Poplar on a wide area network. Overall, we report over one order of magnitude performance improvement over Poplar for plain heavy-hitters and 1.5-2x improvement over Prio for attribute-based metrics.

The modern Internet is built on systems that incentivize collection of information about users. In order to minimize privacy loss, it is desirable to prevent these systems from collecting more information than is required for the application. The promise of multi-party computation is that data can be aggregated without revealing individual measurements to the data collector. This work offers a provable security treatment for "Verifiable Distributed Aggregation Functions (VDAFs)", a class of multi-party computation protocols being considered for standardization by the IETF. We propose a formal framework for the analysis of VDAFs and apply it to two constructions. The first is Prio3, one of the candidates for standardization. This VDAF is based on the Prio system of Corrigan-Gibbs and Boneh (NSDI 2017). We prove that Prio3 achieves our security goals with only minor changes to the draft. The second construction, called Doplar, is introduced by this paper. Doplar is a round-reduced variant of the Poplar system of Boneh et al. (IEEE S&P 2021), itself a candidate for standardization. The cost of this improvement is a modest increase in overall bandwidth and computation.

SMS-based two-factor authentication (2FA) is the most widely deployed 2FA mechanism, despite the fact that SMS messages are known to be vulnerable to rerouting attacks, and despite the availability of alternatives that may be more secure. This is for two reasons. First, it is very effective in practice, as evidenced by reports from Google and Microsoft. Second, users prefer SMS over alternatives, because text messaging is already part of their daily communication. Accepting this practical reality, we developed a new SMS-based protocol that makes rerouting attacks useless to adversaries who aim to take over user accounts. Our protocol delivers one-time passwords (OTP) via text message in a manner that adds minimal overhead (to both the user and the server) over existing SMS-based methods, and is implemented with only small changes to the stock text-message applications that already ship on mobile phones. The security of our protocol rests upon a provably secure authenticated key exchange protocol that, crucially, does not place significant new burdens upon the user. Indeed, we carry out a user study that demonstrates no statistically significant difference between traditional SMS and our protocol, in terms of usability.

A protocol for two-party secure function evaluation (2P-SFE) aims to allow the parties to learn the output of function f of their private inputs, while leaking nothing more. In a sense, such a protocol realizes a trusted oracle that computes f and returns the result to both parties. There have been tremendous strides in efficiency over the past ten years, yet 2P-SFE protocols remain impractical for most real-time, online computations, particularly on modestly provisioned devices. Intel's Software Guard Extensions (SGX) provides hardware-protected execution environments, called enclaves, that may be viewed as trusted computation oracles. While SGX provides native CPU speed for secure computation, previous side-channel and micro-architecture attacks have demonstrated how security guarantees of enclaves can be compromised. In this paper, we explore a balanced approach to 2P-SFE on SGX-enabled processors by constructing a protocol for evaluating f relative to a partitioning of f. This approach alleviates the burden of trust on the enclave by allowing the protocol designer to choose which components should be evaluated within the enclave, and which via standard cryptographic techniques. We describe SGX-enabled SFE protocols (modeling the enclave as an oracle), and formalize the strongest-possible notion of 2P-SFE for our setting. We prove our protocol meets this notion when properly realized. We implement the protocol and apply it to two practical problems: privacy-preserving queries to a database, and a version of Dijkstra's algorithm for privacy-preserving navigation. Our evaluation shows that our SGX-enabled SFE scheme enjoys a 38x increase in performance over garbled-circuit-based SFE. Finally, we justify modeling of the enclave as an oracle by implementing protections against known side-channels.

Probabilistic data structures use space-efficient representations of data in order to (approximately) respond to queries about the data. Traditionally, these structures are accompanied by probabilistic bounds on query-response errors. These bounds implicitly assume benign attack models, in which the data and the queries are inputs are chosen non-adaptively, and independent of the randomness used to construct the representation. Yet probabilistic data structures are increasingly used in settings where these assumptions may be violated. This work provides a provable security treatment of probabilistic data structures in adversarial environments. We give a syntax that captures a wide variety of in-use structures, and our security notions support development of error bounds in the presence of powerful attacks. Concretely, we primarily focus on examining the widely used Bloom filter, but also consider counting (Bloom) filters and count-min sketch data structures. For the traditional version of these, our security findings are largely negative; however, we show that simple embellishments (e.g., using salts, or secret keys) yields structures that provide provable security, and with little overhead.

We advance the study of secure stream-based channels (Fischlin et al., CRYPTO '15) by considering the multiplexing of many data streams over a single channel, an essential feature of real world protocols such as TLS. Our treatment adopts the definitional perspective of Rogaway and Stegers (CSF '09), which offers an elegant way to reason about what standardizing documents actually provide: a partial specification of a protocol that admits a collection of compliant, fully realized implementations. We formalize partially specified channels as the component algorithms of two parties communicating over a channel. Each algorithm has an oracle that provides specification details ; the algorithms abstract the things that must be explicitly specified, while the oracle abstracts the things that need not be. Our security notions, which capture a variety of privacy and integrity goals, allow the adversary to respond to these oracle queries; security relative to these notions implies that the channel withstands attacks in the presence of worst-case (i.e., adversarial) realizations of the specification details. We apply this framework to a formal treatment of the TLS 13 record and, in doing so, show that its security hinges crucially upon details left unspecified by the standard.