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Free, publicly-accessible full text available May 22, 2026
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This paper addresses volume leakage (i.e., leakage of the number of records in the answer set) when processing keyword queries in encrypted key-value (KV) datasets. Volume leakage, coupled with prior knowledge about data distribution and/or previously executed queries, can reveal both ciphertexts and current user queries. We develop a solution to prevent volume leakage, entitled Veil, that partitions the dataset by randomly mapping keys to a set of equi-sized buckets. Veil provides a tunable mechanism for data owners to explore a trade-off between storage and communication overheads. To make buckets indistinguishable to the adversary, Veil uses a novel padding strategy that allow buckets to overlap, reducing the need to add fake records. Both theoretical and experimental results show Veil to significantly outperform existing state-of-the-art.more » « less
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We describe ENRICHDB, a new DBMS technology designed for emerging domains (e.g., sensor-driven smart spaces and social media analytics) that require incoming data to be enriched using expensive functions prior to its usage. To support online processing, today, such enrichment is performed outside of DBMSs, as a static data processing workflow prior to its ingestion into a DBMS. Such a strategy could result in a significant delay from the time when data arrives and when it is enriched and ingested into the DBMS, especially when the enrichment complexity is high. Also, enriching at ingestion could result in wastage of resources if applications do not use/require all data to be enriched. ENRICHDB's design represents a significant departure from the above, where we explore seamless integration of data enrichment all through the data processing pipeline - at ingestion, triggered based on events in the background, and progressively during query processing. The cornerstone of ENRICHDB is a powerful enrichment data and query model that encapsulates enrichment as an operator inside a DBMS enabling it to co-optimize enrichment with query processing. This paper describes this data model and provides a summary of the system implementation.more » « less
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