Collected research

“You Might Also Like:” Privacy Risks of Collaborative Filtering

Joseph A. Calandrino, Ann Kilzer, Arvind Narayanan, Edward W. Felten and Vitaly Shmatikov · ieee-security.org

Public recommender output - item-similarity lists and item-to-item covariances - shifts measurably when a single user acts. The authors monitor those shifts over time and combine them with a little known auxiliary history for a target, inferring that user's non-public purchases and ratings. Evaluated passively against Hunch, LibraryThing, Last.fm and Amazon.

Record

Researcher

Joseph A. Calandrino, Ann Kilzer, Arvind Narayanan, Edward W. Felten and Vitaly Shmatikov

Published by

ieee-security.org

Format

Whitepaper

Topic

Other

In the archive

• Collected in the 2011 research round

Tags

• info-leak
• side-channel
• measurement-study
• case-study

This page is the archive's own catalogue record. The research is the work of Joseph A. Calandrino, Ann Kilzer, Arvind Narayanan, Edward W. Felten and Vitaly Shmatikov, first published at the original source. Preserved copies are kept so the citation survives its host; this one was last captured on 11 August 2026.