
NSF Org: |
CNS Division Of Computer and Network Systems |
Recipient: |
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Initial Amendment Date: | August 4, 2017 |
Latest Amendment Date: | August 4, 2017 |
Award Number: | 1717067 |
Award Instrument: | Standard Grant |
Program Manager: |
James Joshi
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
Start Date: | September 1, 2017 |
End Date: | August 31, 2022 (Estimated) |
Total Intended Award Amount: | $250,000.00 |
Total Awarded Amount to Date: | $250,000.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
4400 UNIVERSITY DR FAIRFAX VA US 22030-4422 (703)993-2295 |
Sponsor Congressional District: |
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Primary Place of Performance: |
4400 University Drive Fairfax VA US 22030-4422 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | Secure &Trustworthy Cyberspace |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070 |
ABSTRACT
Blockchains provide a new perspective on secure, decentralized information sharing and are projected to be the technology of the future. Blockchains were first introduced as the underlying mechanism of cryptocurrencies and are used to secure financial transactions without the need for a central trusted party. Today, blockchains are also recognized for their potential advantages in various contexts ranging from identity management to health data records. However, despite being such a promising tool, the data posted on a blockchain is public and immortally captured and thus the privacy of the users can be massively violated if privacy concerns are not taken into consideration. The goals of this project are to develop a formal model for privacy in blockchains and privacy-preserving tools.
This project develops a framework that captures privacy requirements for transactions, data blocks and the mining process under a threat model that reflects the adversarial capabilities over the Internet (i.e., composable security). Building on this framework, the researchers investigate new privacy-preserving mechanisms for existing blockchain payment systems and the design of new blockchain-based payment systems with built-in privacy properties that do not require a trusted setup. Next, the researchers investigate new privacy requirements like hiding the identity of the miner which is relevant in scenarios where mining a block might signify the endorsement of the information included in the block. Finally, the researchers develop techniques to guarantee accountability even in a privacy-preserving setting where privacy should be preserved only so long as a pre-specified bad behavior is not detected.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project focused on the problem of analyzing, formalizing, and enhancing privacy in blockchain systems and applications.
Intellectual merits.
Our main contributions can be grouped as follows:
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Analyzing privacy: We proved a lower bound on the highest anonymity guarantees that can be achieved in any proof-of-stake blockchain. We showed that de-anonymization attacks can be mounted through network delays, regardless of whether parties are using anonymous broadcast or point-to-point channels, and regardless of the cryptographic protocols being employed. As a consequence we proved that full anonymity is impossible to achieve in network that allow adversarial delays (S&P ‘21). Along the same lines, but in a different contest, we showed other privacy attacks that are based on the ability of the adversary to run smart contracts, and allow an adversary to break the zero-knowledge property of certain blockchain-based zero-knowledge proofs (PKC ‘21,’20).
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Formalizing privacy: we explored novel approaches for defining anonymity for blockchain-based payment systems, based on differential privacy (PoPETS ‘22). We provided the first definition of privacy for side-chains (CBT workshop at ESORICS ’21), and provided a framework to categorize and analyze techniques for accountability and auditability of anonymous blockchains (ACNS ’21).
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Enhancing privacy: We introduced and constructed new building blocks to enhance privacy in blockchain applications. The most recent primitive, called Private Signaling, was awarded the distinguished paper award at USENIX ‘22 and it aims at providing full anonymity with zero-overhead to blockchain users. We also built a plethora of primitives that serve as building blocks for adding privacy under various trade-offs in terms of efficiency, trust assumptions and computational assumptions. In terms of efficiency, we constructed communication-efficient cryptographic accumulators in the Bilinear Pairing setting, that allows for faster batching and aggregation of zero-knowledge proofs (CCS ‘22). Additionally, we build an efficient system for proving total assets in cryptocurrencies in a privacy preserving way (PoPETS ‘22). In terms of reducing trust-assumptions, we constructed publicly verifiable zero-knowledge proofs that do not require any trusted setup, but only the existence of a blockchain with some unpredictability property. We also designed a decentralized protocol that allows a crowd of people to audit the validity of a trusted setup process even in the setting that all servers and all the clients of the MPC protocol are subverted by an adversary (ASIACRYPT ‘20). In terms of reducing computational assumptions, we built the first post-quantum secure threshold ring signature (PKC ‘21), and one-time traceable ring signatures that use primitives in a black-box manner (ESORICS21). Notably, the latter is the only example of an anonymous building block that uses a random oracle only.
Broader Impacts
Our results have direct impacts on both the blockchain research and development communities. We provide analysis on the inherent limitations of anonymity (e.g., through our lower bound) and what a variety of tools that can be used to enhance anonymity in a provably secure way (e.g., through our building blocks). Importantly, all our results are proved in formal frameworks.
The PIs have actively engaged with local blockchain interest groups, startup and established companies working on blockchain and privacy projects as well as with scientists from different disciplines such as policy and economics researchers.
The results of this proposal have been published in major conferences and are all publicly available to public archives. We have further disseminated our results, through recorded seminars, tutorials, invited talks and conference presentations.
Last Modified: 02/16/2023
Modified by: Foteini Baldimtsi
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