CyLab announces third round of Secure Blockchain Initiative funded projects

Carnegie Mellon University's Secure Blockchain Initiative (SBI) has announced its third round of funded proposals, providing $130K to six groundbreaking research projects that are exploring the security and privacy of distributed ledger technology.

Through research, the CMU SBI aims to revolutionize blockchain technology within enterprise ecosystems by tackling various challenges, including enhancing consensus mechanisms and scalability, exploring cryptocurrencies and markets, advancing cryptography, implementing formal verification, and addressing regulation, policy, and governance concerns.

Led by co-directors Nicolas Christin, Elaine Shi, and Ariel Zetlin-Jones, the multi-year CyLab initiative intends to develop a suite of novel foundations and technologies focused on three key thrusts:

• Cryptoeconomics: Cryptography, Consensus, and Verification
• Applications and Implementations
• Cryptocurrencies, Tokenized Assets, and Policy

Funded Projects

Large Party Scalable Multiparty Computation from Learning Parity with Noise (LPN)

• Aayush Jain - assistant professor, Computer Science Department

Objectives

My objective is to design semi-honest and maliciously secure multi-party computation (MPC) with low communication and compute in the large party setting through novel use of learning parity with noise and related assumption..

Analysis and Optimization of Robustness in XRP Ledger Consensus Protocol

• Osman Yağan - research professor, Electrical and Computer Engineering

Objectives

My goal is to obtain the current topology of the XRP Ledger (XRPL) using its native crawler. I will conduct a detailed analysis of the robustness of the XRPL with respect to both network robustness metric and the quorum robustness metric. I will also develop strategies for improving the robustness of the XRPL based on i) rewiring of the existing edges; ii) establishing additional edges in the entire network using the random K-out graph construction; and iii) establishing additional edges only over a subset of nodes.

Incentivizing Constructive Participation in Decentralized Governance

• Giulia Fanti - Angel Jordan associate professor - Electrical and Computer Engineering

• Elaine Shi - professor, Computer Science Department, Electrical and Computer Engineering

Objectives

Today, decentralized autonomous organizations (DAOs) have different ways of rewarding professional delegates. We aim to design a new algorithm for rewarding delegates in a way that is game-theoretically incentive-compatible. We hope to evaluate it on a real dataset of DAO conversations.

Tiered Payments Networks

• Ariel Zetlin-Jones - associate professor of economics, Tepper School of Business

• Shengxing Zhang - visiting professor of economics, Tepper School of Business

Objectives

Our goal is to build a theory to understand the effect of tiered payments network on economic development. We will use Lightning network as a laboratory to understand key features of tiered payment networks. We also seek to understand how trading needs and the duration of relationships affect the amount of capital pledged in bilateral relationships in the second tier of the network.

Efficient Anonymous Verifiable Credentials

• Sarah Scheffler - assistant professor, Engineering and Public Policy, Software and Societal Systems Department

Objectives

This is an applied cryptography effort to develop private, anonymous, and verifiable credentials that are backward-compatible with existing non-private credentials (e.g. U.S. driver’s licenses). My goal is to provide comments and revisions to the W3C specification for Verifiable Credentials, as well as build open-source code compatible with identities, credentials, or revocations presented on the XRP Ledger (XRPL) (e.g. via the DID API).

Superoptimizing probabilistic-proof-systems compilers

• Fraser Brown - assistant professor, Software and Societal Systems Department

• Riad Wahby - assistant professor, Electrical and Computer Engineering

Objectives

Our goal for this research is to leverage and improve Jolt’s lookup-based execution in CoBBl, a new compiler and proof system that we’ve built and submitted for USENIX 2025. Jolt is an Andreesen Research-funded CPU emulation system. While CoBBl roughly matches Jolt’s performance, it does so using a much less efficient approach to proving CPU-like operations.

Our first milestone is to extend CoBBl to automatically use Jolt’s lookup-based representations for CPU-like operations when doing so reduces the cost of proof generation. Our next milestone is to automatically infer instructions that correspond directly to the program being compiled.