A Scalable and Efficient Privacy Preserving Global Itemset Support Approximation Using Bloom Filters

DOI10.1007/978-3-662-43936-4_26zbMath1391.94725OpenAlexW315172248MaRDI QIDQ5252105

Ravi Mukkamala, Vikas G. Ashok

Publication date: 29 May 2015

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://hal.inria.fr/hal-01284874/file/978-3-662-43936-4_26_Chapter.pdf

zbMATH Keywords

privacy preserving data miningsecure multiparty computationprivacy preserving set union protocol

Mathematics Subject Classification ID

Cryptography (94A60) Data encryption (aspects in computer science) (68P25)

Related Items (2)

Privately Computing Set-Union and Set-Intersection Cardinality via Bloom Filters ⋮ Efficient private set intersection cardinality protocol in the reverse unbalanced setting

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