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Explained from scratch: private information retrieval using homomorphic encryption

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This is a from-scratch explanation of private information retrieval built using homomorphic encryption. I try to assume only a general math / computer science background. To simplify things, my explanations may not always match academic definitions. You can check out this Wikipedia demo, Bitcoin balance checker, paper, or code for more. Follow us @SpiralPrivacy. Say we want to fetch an article from Wikipedia, but somehow not reveal to the server which one we fetched. A naive solution is to download and store the entirety of Wikipedia; then, all your queries can be local and the server never learns anything. Unfortunately, this takes a lot of bandwidth and storage (~10 GB), so it isn’t very practical. Another strawman solution might be to put the articles in buckets, and just send some ‘dummy’ articles along with the true response. This still leaks significant information - over time, or with any additional prior about your behavior, it’s easy to narrow down the set of articles you were

This is a from-scratch explanation of private information retrieval built using homomorphic encryption. I try to assume only a general math / computer science background. To simplify things, my explanations may not always match academic definitions. You can check out this paper or code for more. Table of Contents ## Private information retrieval (PIR) --> Say we want to fetch an article from Wikipedia, but somehow not reveal to the server which one we fetched. A naive solution is to download and store the entirety of Wikipedia; then, all your queries can be local and the server never learns an

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