Inconsistent quality and aesthetics in agricultural crops can result in increased consumer and producer food waste, reduced industry resiliency and decreased farmers������������������ and growers������������������ profit, poor consumer satisfaction, and inefficiencies across the supply chain. Although there are opportunities to characterize and quantify sources of phenotypic variability across the agricultural supply chain - from cultural practices of growers and producers to storage and handling by distributors - the data available to allow for assessment of horticultural quality drivers are disparate and disconnected. The absence of data integration platforms that link heterogeneous datasets across the supply chain precludes the development of strategies and solutions to constrain variability in produce quality. This project������������������s central hypothesis is that multi-dimensional produce data can be securely integrated and used to optimize management practices in the field while simultaneously adding value across the entire food supply chain. We propose to develop multi-modal sensing platform along with a trust-based, data management, integration, and analytics framework for systematic organization and dynamic abstraction of heterogeneous data across the supply chain of agricultural crops. The projects short term goals are to (1) engage growers to refine research and extension priorities; (2) develop a first-of-its-kind modular imaging system that responds to grower needs by analyzing existing and novel multi-dimensional data; (3) establish the cyberinfrastructure, including analytics and blockchain, to make meaningful inference of the acquired data as related to management practices while ensuring data security; (4) deploy the sensing system at NCSU������������������s Horticultural Crops Research Station in Clinton, NC and on a large-scale system at a major commercial farm and distribution facility, and (5) extend findings to producers and regulators through NC Cooperative Extension. The proposed sensing and cyberinfrastructure platforms will be crop-agnostic and our findings will be transferable to other horticultural crops produced in NC and beyond.

This project seeks to develop a platform-SmartChainDB for supporting Smart Marketplaces in trustless environments. Such marketplaces should enable efficient assessment of bids in response to service requests without a-priori trust establishment between parties. In domains like Digital Manufacturing, job bid assessments are very time consuming efforts that take order of months. The platform will be developed by extending a BlockChain database for managing trust, with transaction types necessary to support a protocol for service requests and response bids. Another key extension will be semantic-enablement of the BlockChain database. A proof-of-concept prototype in Smart Manufacturing will be developed using SmartChainDB.

We aim to devise a general framework for anonymity and traceability in blockchain applications which fulfills efficiency and trustless requirements of current blockchain ecosystems.

A blockchain is a public, distributed, append-only database whose consistency is maintained by the combined work of users across the world rather than a single party, thus avoiding single points of failure and trust. The public nature of the blockchain, however, raises important privacy concerns. Existing work partially addressed privacy concerns for the restricted case of blockchains used for financial transactions. As blockchains are set to be used in a variety of contexts, proposed work will initiate a broad treatment of privacy definition and provide constructions achieving new privacy goals that can be implemented across different blockchains.

Digital signatures are fundamental cryptographic building blocks that guarantee the authenticity and integrity of digital communications. Currently adopted signature schemes (such as ECDSA) leverage number-theoretic properties, and their security relies on the intractability of solving number-theoretic problems such as integer factorization and the discrete logarithm problem. Shor's algorithm however shows that such problems are practically solvable on quantum computers. The threat of quantum attacks triggered NIST's competition for the development and standardization of signature schemes that are secure in presence of quantum adversaries. There exist several candidates for such competition, and CISCO research team is participating with the LMS scheme. The advantage of the LMS scheme over the other candidates is in its simplicity. The goal of the proposed research is to develop a formal treatment of the post-quantum security of the LMS scheme.