Graph Theoretical Methods for Blockchain Data Analysis

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Graph Theoretical Methods for Blockchain Data Analysis Workshop, May 25, 2022 George Mason UniversityThe Workshop on Graph Theoretical Methods for Blockchain Data Analysis will be focused on the recent developments on the foundational statistical and mathematical tools associated with the data structures that arise from the use of distributed secure ledger technologies. Building on the efforts of the first conference, the second workshop will bring together researchers from a broad range of mathematical and statistical disciplines, from graph theory to computational topology to mathematical statistics, to discuss the open problems in analysis, modeling and inference for this class of data in an open forum. While the goal of the second workshop is focused on the mathematical sciences community, we will also include select researchers in e-crime detection, cryptocurrency risk analysis, integration of private and public blockchains, and other distributed ledger-based applications to calibrate the mathematical scientists on the needs of this community. The Workshop on Graph Theoretical Methods for Blockchain Data Analysis will address issues related to the new blockchain technology. Blockchain has already revolutionized many fields, from e-payments to digital ownership management, enabling organizations to leverage a secure distributed public ledger. The first popular application of blockchain was the Bitcoin cryptocurrency, and since then blockchain technology has witnessed rapid evolution and unprecedented interest, from investors to regulating agencies to the general public. For instance, most recent versions of public blockchains such as Ethereum are now used to support fundraising activities for many start-ups by enabling the sales of digital assets worth billions of dollars, to trace the life cycles of crops and other agricultural products, from seed to consumers, determining the responsibilities of each party within the supply chain, and to validate compliance protocols and transparency of clinical trials. As more blockchain applications and variations of the original algorithms are developed and deployed, novel interdisciplinary tools for blockchain data analytics are of critical importance for enhancing our understanding of the emerging phenomena and a wide range of its societal impacts, from energy sharing during natural disasters to novel methods for secure access of electronic health information. This workshop will bring together researchers in the mathematical sciences to address the needs of this rapidly evolving community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.