Handling Adaptive Compromise for Practical Encryption Schemes

We provide a new definitional framework capturing the multi-user security of encryption schemes and pseudorandom functions in the face of adversaries that can adaptively compromise users\u27 keys. We provide a sequence of results establishing the security of practical symmetric encryption schemes under adaptive compromise in the random oracle or ideal cipher model. The bulk of analysis complexity for adaptive compromise security is relegated to the analysis of lower-level primitives such as pseudorandom functions. We apply our framework to give proofs of security for the BurnBox system for privacy in the face of border searches and the in-use searchable symmetric encryption scheme due to Cash et al. In both cases, prior analyses had bugs that our framework helps avoid

Orca: Blocklisting in Sender-Anonymous Messaging

Sender-anonymous end-to-end encrypted messaging allows sending messages to a recipient without revealing the sender’s identity to the messaging platform. Signal recently introduced a sender anonymity feature that includes an abuse mitigation mechanism meant to allow the platform to block malicious senders on behalf of a recipient. We explore the tension between sender anonymity and abuse mitigation. We start by showing limitations of Signal’s deployed mechanism, observing that it results in relatively weak anonymity properties and showing a new griefing attack that allows a malicious sender to drain a victim’s battery. We therefore design a new protocol, called Orca, that allows recipients to register a privacy-preserving blocklist with the platform. Without learning the sender’s identity, the platform can check that the sender is not on the blocklist and that the sender can be identified by the recipient. We construct Orca using a new type of group signature scheme, for which we give formal security notions. Our prototype implementation showcases Orca’s practicality

Bicorn: An optimistically efficient distributed randomness beacon

We introduce Bicorn, an optimistically efficient distributed randomness protocol with strong robustness under a dishonest majority. Bicorn is a commit-reveal-recover protocol. Each participant commits to a random value, which are combined to produce a random output. If any participants fail to open their commitment, recovery is possible via a single time-lock puzzle which can be solved by any party. In the optimistic case, Bicorn is a simple and efficient two-round protocol with no time-lock puzzle. In either case, Bicorn supports open, flexible participation, requires only a public bulletin board and no group-specific setup or PKI, and is guaranteed to produce random output assuming any single participant is honest. All communication and computation costs are (at most) linear in the number of participants with low concrete overhead

BurnBox: Self-Revocable Encryption in a World of Compelled Access

Dissidents, journalists, and others require technical means to protect their privacy in the face of compelled access to their digital devices (smartphones, laptops, tablets, etc.). For example, authorities increasingly force disclosure of all secrets, including passwords, to search devices upon national border crossings. We therefore present the design, implementation, and evaluation of a new system to help victims of compelled searches. Our system, called BurnBox, provides self-revocable encryption: the user can temporarily disable their access to specific files stored remotely, without revealing which files were revoked during compelled searches, even if the adversary also compromises the cloud storage service. They can later restore access. We formalize the threat model and provide a construction that uses an erasable index, secure erasure of keys, and standard cryptographic tools in order to provide security supported by our formal analysis. We report on a prototype implementation, which showcases the practicality of BurnBox

Stadium: A Distributed Metadata-Private Messaging System

Private communication over the Internet remains a challenging problem. Even if messages are encrypted, it is hard to deliver them without revealing metadata about which pairs of users are communicating. Scalable anonymity systems, such as Tor, are susceptible to traffic analysis attacks that leak metadata. In contrast, the largest-scale systems with metadata privacy require passing all messages through a small number of providers, requiring a high operational cost for each provider and limiting their deployability in practice. This paper presents Stadium, a point-to-point messaging system that provides metadata and data privacy while scaling its work efficiently across hundreds of low-cost providers operated by different organizations. Much like Vuvuzela, the current largest-scale metadata-private system, Stadium achieves its provable guarantees through differential privacy and the addition of noisy cover traffic. The key challenge in Stadium is limiting the information revealed from the many observable traffic links of a highly distributed system, without requiring an overwhelming amount of noise. To solve this challenge, Stadium introduces techniques for distributed noise generation and differentially private routing as well as a verifiable parallel mixnet design where the servers collaboratively check that others follow the protocol. We show that Stadium can scale to support 4X more users than Vuvuzela using servers that cost an order of magnitude less to operate than Vuvuzela nodes

Proofs for Inner Pairing Products and Applications

We present a generalized inner product argument and demonstrate its applications to pairing-based languages. We apply our generalized argument to proving that an inner pairing product is correctly evaluated with respect to committed vectors of $n$ source group elements. With a structured reference string (SRS), we achieve a logarithmic-time verifier whose work is dominated by $6 \log n$ target group exponentiations. Proofs are of size $6 \log n$ target group elements, computed using $6n$ pairings and $4n$ exponentiations in each source group. We apply our inner product arguments to build the first polynomial commitment scheme with succinct (logarithmic) verification, $O(\sqrt{d})$ prover complexity for degree $d$ polynomials (not including the cost to evaluate the polynomial), and a CRS of size $O(\sqrt{d})$. Concretely, this means that for $d=2^{28}$, producing an evaluation proof in our protocol is $76\times$ faster than doing so in the KZG commitment scheme, and the CRS in our protocol is $1,000\times$ smaller: $13$MB vs $13$GB for KZG. This gap only grows as the degree increases. Our polynomial commitment scheme is applicable to both univariate and bivariate polynomials. As a second application, we introduce an argument for aggregating $n$ $\mathsf{Groth16}$ zkSNARKs into an $O(\log n)$ sized proof. Our protocol is significantly more efficient than aggregating these SNARKs via recursive composition (BCGMMW20): we can aggregate about $130,000$ proofs in $25$min, while in the same time recursive composition aggregates just $90$ proofs. Finally, we show how to apply our aggregation protocol to construct a low-memory SNARK for machine computations. For a computation that requires time $T$ and space $S$, our SNARK produces proofs in space $\tilde{\mathcal{O}}(S+T)$, which is significantly more space efficient than a monolithic SNARK, which requires space $\tilde{\mathcal{O}}(S \cdot T)$

Talek: Private Group Messaging with Hidden Access Patterns

Talek is a private group messaging system that sends messages through potentially untrustworthy servers, while hiding both data content and the communication patterns among its users. Talek explores a new point in the design space of private messaging; it guarantees access sequence indistinguishability, which is among the strongest guarantees in the space, while assuming an anytrust threat model, which is only slightly weaker than the strongest threat model currently found in related work. Our results suggest that this is a pragmatic point in the design space, since it supports strong privacy and good performance: we demonstrate a 3-server Talek cluster that achieves throughput of 9,433 messages/second for 32,000 active users with 1.7-second end-to-end latency. To achieve its security goals without coordination between clients, Talek relies on information-theoretic private information retrieval. To achieve good performance and minimize server-side storage, Talek intro- duces new techniques and optimizations that may be of independent interest, e.g., a novel use of blocked cuckoo hashing and support for private notifications. The latter provide a private, efficient mechanism for users to learn, without polling, which logs have new messages

A distributed metadata-private messaging system

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 61-63).Private communication over the Internet continues to be a difficult problem. Even if messages are encrypted, it is hard to deliver them without revealing metadata about which pairs of users are communicating. Scalable systems such as Tor are susceptible to traffic analysis. In contrast, the largest-scale systems with metadata privacy require passing all messages through a single server, which places a hard cap on their scalability. This paper presents Stadium, the first system to protect both messages and metadata while being able to scale its work efficiently across multiple servers. Stadium uses the same differential privacy definition for metadata privacy as Vuvuzela, the currently highest-scale system. However, providing privacy in Stadium is significantly more challenging because distributing users' traffic across servers creates more opportunities for adversaries to observe it. To solve this challenge, Stadium uses a novel verifiable mixnet design. We use a verifiable shuffle scheme that we extend to allow for efficient group verification, and present a verifiable distribution primitive to check message transfers across servers. We show that Stadium can scale to use hundreds of servers, support an order of magnitude more users than Vuvuzela, and cut the costs of operating each server.by Nirvan Tyagi.M. Eng