Abstract. We address the problem in which a client stores a large amount of data with an untrusted server in such a way that, at any moment, the client can ask the server to compute a function on some portion of its outsourced data. In this scenario, the client must be able to efficiently verify the correctness of the result despite no longer knowing the inputs of the delegated computation, it must be able to keep adding elements to its remote storage, and it does not have to fix in advance (i.e., at data outsourcing time) the functions that it will delegate. Even more ambitiously, clients should be able to verify in time independent of the input-size -a very appealing property for computations over huge amounts of data.In this work we propose novel cryptographic techniques that solve the above problem for the class of computations of quadratic polynomials over a large number of variables. This class covers a wide range of significant arithmetic computations -notably, many important statistics. To confirm the efficiency of our solution, we show encouraging performance results, e.g., correctness proofs have size below 1 kB and are verifiable by clients in less than 10 milliseconds.
We study the problem of privacy-preserving proofs on authenticated data, where a party receives data from a trusted source and is requested to prove computations over the data to third parties in a correct and private way, i.e., the third party learns no information on the data but is still assured that the claimed proof is valid. Our work particularly focuses on the challenging requirement that the third party should be able to verify the validity with respect to the specific data authenticated by the source-even without having access to that source. This problem is motivated by various scenarios emerging from several application areas such as wearable computing, smart metering, or general business-to-business interactions. Furthermore, these applications also demand any meaningful solution to satisfy additional properties related to usability and scalability. In this paper, we formalize the above three-party model, discuss concrete application scenarios, and then we design, build, and evaluate ADSNARK, a nearly practical system for proving arbitrary computations over authenticated data in a privacy-preserving manner. ADSNARK improves significantly over state-of-the-art solutions for this model. For instance, compared to corresponding solutions based on Pinocchio (Oakland'13), ADSNARK achieves up to 25× improvement in proof-computation time and a 20× reduction in prover storage space.
This paper proposes a Scalable Internet Bandwidth Reservation Architecture (SIBRA) as a new approach against DDoS attacks, which, until now, continue to be a menace on today's Internet. SIBRA provides scalable inter-domain resource allocations and botnet-size independence, an important property to realize why previous defense approaches are insufficient. Botnetsize independence enables two end hosts to set up communication regardless of the size of distributed botnets in any Autonomous System in the Internet. SIBRA thus ends the arms race between DDoS attackers and defenders. Furthermore, SIBRA is based on purely stateless operations for reservation renewal, flow monitoring, and policing, resulting in highly efficient router operation, which is demonstrated with a full implementation. Finally, SIBRA supports Dynamic Interdomain Leased Lines (DILLs), offering new business opportunities for ISPs.
This paper presents a novel method for enabling fast development and easy customization of interactive data-intensive web applications. Our approach is based on a high-level hierarchical programming model that results in both a very clean semantics of the application while at the same time creating well-defined interfaces for customization of application components. A prototypical implementation of a conference management system shows the efficacy of our approach.
In this article, we address the problem of scaling authentication for naming, routing, and end-entity (EE) certification to a global environment in which authentication policies and users’ sets of trust roots vary widely. The current mechanisms for authenticating names (DNSSEC), routes (BGPSEC), and EE certificates (TLS) do not support a coexistence of authentication policies, affect the entire Internet when compromised, cannot update trust root information efficiently, and do not provide users with the ability to make flexible trust decisions. We propose the Scalable Authentication Infrastructure for Next-generation Trust (SAINT), which partitions the Internet into groups with common, local trust roots and isolates the effects of a compromised trust root. SAINT requires groups with direct routing connections to cross-sign each other for authentication purposes, allowing diverse authentication policies while keeping all entities’ authentication information globally discoverable. SAINT makes trust root management a central part of the network architecture, enabling trust root updates within seconds and allowing users to make flexible trust decisions. SAINT operates without a significant performance penalty and can be deployed alongside existing infrastructures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.