International Association for Cryptologic Research

International Association
for Cryptologic Research


Gabriel Kaptchuk


Abuse Resistant Law Enforcement Access Systems
Matthew Green Gabriel Kaptchuk Gijs Van Laer
The increased deployment of end-to-end encryption has ignited a debate between technology firms and law enforcement agencies over the need for lawful access to encrypted communications. Unfortunately, existing solutions to this problem suffer from serious technical risks, such as the possibility of operator abuse and theft of escrow key material. In this work we investigate the problem of constructing law enforcement access systems that mitigate the possibility of unauthorized surveillance. We first define a set of desirable properties for an abuse-resistant law enforcement access system (ARLEAS), and motivate each of these properties. We then formalize these definitions in the Universal Composability framework, and present two main constructions that realize this definition. The first construction enables {\em prospective} access, allowing surveillance only if encryption occurs after a warrant has been issued and activated. The second, more powerful construction, allows {\em retrospective} access to communications that occurred prior to a warrant's issuance. To illustrate the technical challenge of constructing the latter type of protocol, we conclude by investigating the minimal assumptions required to realize these systems.
Order-C Secure Multiparty Computation for Highly Repetitive Circuits
Running secure multiparty computation (MPC) protocols with hundreds or thousands of players would allow leveraging large volunteer networks (such as blockchains and Tor) and help justify honest majority assumptions. However, most existing protocols have at least a linear (multiplicative) dependence on the number of players, making scaling difficult. Known protocols with asymptotic efficiency independent of the number of parties (excluding additive factors) require expensive circuit transformations that induce large overheads. We observe that the circuits used in many important applications of MPC such as training algorithms used to create machine learning models have a highly repetitive structure. We formalize this class of circuits and propose an MPC protocol that achieves O(|C|) total complexity for this class. We implement our protocol and show that it is practical and outperforms O(n|C|) protocols for modest numbers of players.
Fluid MPC: Secure Multiparty Computation with Dynamic Participants 📺
Existing approaches to secure multiparty computation (MPC) require all participants to commit to the entire duration of the protocol. As interest in MPC continues to grow, it is inevitable that there will be a desire to use it to evaluate increasingly complex functionalities, resulting in computations spanning several hours or days. Such scenarios call for a *dynamic* participation model for MPC where participants have the flexibility to go offline as needed and (re)join when they have available computational resources. Such a model would also democratize access to privacy-preserving computation by facilitating an ``MPC-as-a-service'' paradigm --- the deployment of MPC in volunteer-operated networks (such as blockchains, where dynamism is inherent) that perform computation on behalf of clients. In this work, we initiate the study of *fluid MPC*, where parties can dynamically join and leave the computation. The minimum commitment required from each participant is referred to as *fluidity*, measured in the number of rounds of communication that it must stay online. Our contributions are threefold: - We provide a formal treatment of fluid MPC, exploring various possible modeling choices. - We construct information-theoretic fluid MPC protocols in the honest-majority setting. Our protocols achieve *maximal fluidity*, meaning that a party can exit the computation after receiving and sending messages in one round. - We implement our protocol and test it in multiple network settings.