Pump up the Volume: Practical Database Reconstruction from Volume Leakage on Range Queries
Paul Grubbs, Marie-Sarah Lacharité, Brice Minaud, Kenneth G. Paterson
Abstract
We present attacks that use only the volume of responses to range queries to reconstruct databases. Our focus is on practical attacks that work for large-scale databases with many values and records, without requiring assumptions on the data or query distributions. Our work improves on the previous state-of-the-art due to Kellaris et al. (CCS 2016) in all of these dimensions. Our main attack targets reconstruction of database counts and involves a novel graph-theoretic approach. It generally succeeds when R, the number of records, exceeds N 2 /2, where N is the number of possible values in the database. For a uniform query distribution, we show that it requires volume leakage from only O(N 2 log N ) queries (cf. O(N 4 log N ) in prior work). We present two ancillary attacks. The first identifies the value of a new item added to a database using the volume leakage from fresh queries, in the setting where the adversary knows or has previously recovered the database counts. The second shows how to efficiently recover the ranges involved in queries in an online fashion, given an auxiliary distribution describing the database. Our attacks are all backed with mathematical analyses and extensive simulations using real data.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext eec05c12-b384-4c1a-816a-c5c646ef2ef1Cited by top-tier papers48
- Encrypted Databases: New Volume Attacks against Range QueriesZichen Gui, Oliver Johnson, Bogdan WarinschiCCS 2019 · 97 citations
- Waldo: A Private Time-Series Database from Function Secret SharingEmma Dauterman, Mayank Rathee, Raluca Ada Popa, Ion StoicaS&P 2022 · 91 citations
- Response-Hiding Encrypted Ranges: Revisiting Security via Parametrized Leakage-Abuse AttacksEvgenios M. Kornaropoulos, Charalampos Papamanthou, Roberto TamassiaS&P 2021 · 56 citations
- SECRECY: Secure collaborative analytics in untrusted cloudsJohn Liagouris, Vasiliki Kalavri, Muhammad Faisal, Mayank VariaNSDI 2023 · 53 citations
- A Highly Accurate Query-Recovery Attack against Searchable Encryption using Non-Indexed DocumentsMarc Damie, Florian Hahn, Andreas PeterUSENIX Security 2021 · 46 citations
Builds on4
- Generic Attacks on Secure Outsourced DatabasesGeorgios Kellaris, George Kollios, Kobbi Nissim, Adam O'NeillCCS 2016 · 327 citations
- Beauty and the Burst: Remote Identification of Encrypted Video StreamsRoei Schuster, Vitaly Shmatikov, Eran TromerUSENIX Security 2017 · 205 citations
- Leakage-Abuse Attacks against Order-Revealing EncryptionPaul Grubbs, Kevin Sekniqi, Vincent Bindschaedler, Muhammad Naveed et al.S&P 2017 · 204 citations
- Improved Reconstruction Attacks on Encrypted Data Using Range Query LeakageMarie-Sarah Lacharité, Brice Minaud, Kenneth G. PatersonS&P 2018 · 183 citations
Related papers
- Learning to Reconstruct: Statistical Learning Theory and Encrypted Database AttacksPaul Grubbs, Marie-Sarah Lacharité, Brice Minaud, Kenneth G. PatersonS&P 2019 · 146 citations
- Reconstructing with Less: Leakage Abuse Attacks in Two DimensionsEvangelia Anna Markatou, Francesca Falzon, Roberto Tamassia, William SchorCCS 2021 · 22 citations
- The State of the Uniform: Attacks on Encrypted Databases Beyond the Uniform Query DistributionEvgenios M. Kornaropoulos, Charalampos Papamanthou, Roberto TamassiaS&P 2020 · 104 citations
- Reconstructing with Even Less: Amplifying Leakage and Drawing GraphsEvangelia Anna Markatou, Roberto TamassiaCCS 2024 · 2 citations
- Full Database Reconstruction in Two DimensionsFrancesca Falzon, Evangelia Anna Markatou, Akshima, David Cash et al.CCS 2020 · 27 citations
