Data structures have a prominent modern computational role, due to their wide applicability, such as in database querying, web searching, and social network analysis. This project focuses on the interplay of data structures with security protocols, examining two different paradigms: the security for data structures paradigm (SD) and the data structures for security paradigm (DS). The objectives of this project are, in the SD paradigm, to provide security and privacy both for data elements in data sets and also for the inter-relationships and distributions between such data elements, such as links between nodes in a social network, and, in the DS paradigm, to develop new data structures to improve the efficiency of algorithms for security and/or privacy applications.
The project explores methods for achieving these objectives include algorithm design, theoretical analysis, rigorous proofs of security and correctness, and experimental validation of claims of practicality. This research focuses on the security and cybersecurity uses of three advanced data structures: tree structures, invertible Bloom filters and cascading tables. The project advances knowledge on (a) authenticated data structures and verifiable query execution within the SD paradigm, and (b) secure deduplication, searchable encryption, and privacy-preserving memory allocators within the DS paradigm.
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