Divide-and-Learn: A Random Indexing Approach to Attribute Inference Attacks in Online Social Networks
| Autor: | Sanaz Eidizadehakhcheloo, Bizhan Alipour Pijani, Abdessamad Imine, Michaël Rusinowitch |
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| Přispěvatelé: | Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Proof techniques for security protocols (PESTO), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Formal Methods (LORIA - FM), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA), TC 11, WG 11.3, Ken Barker |
| Rok vydání: | 2021 |
| Předmět: |
Information retrieval
Computer science Emoji Comparability Inference 02 engineering and technology 16. Peace & justice [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI] [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR] Random indexing Social Networks Privacy Attribute Inference Attack 020204 information systems 0202 electrical engineering electronic engineering information engineering Targeted advertising 020201 artificial intelligence & image processing Random Indexing Classifier (UML) Value (mathematics) Word (computer architecture) |
| Zdroj: | Data and Applications Security and Privacy XXXV ISBN: 9783030812416 DBSec Data and Applications Security and Privacy XXXV-35th Annual IFIP WG 11.3 Conference, DBSec 2021 Data and Applications Security and Privacy XXXV-35th Annual IFIP WG 11.3 Conference, DBSec 2021, Jul 2021, Calgary, Canada Lecture Notes in Computer Science 35th IFIP Annual Conference on Data and Applications Security and Privacy (DBSec) 35th IFIP Annual Conference on Data and Applications Security and Privacy (DBSec), Jul 2021, Calgary, AB, Canada. pp.338-356, ⟨10.1007/978-3-030-81242-3_20⟩ |
| DOI: | 10.1007/978-3-030-81242-3_20 |
| Popis: | Part 6: Potpourri II; International audience; We present a Divide-and-Learn machine learning methodology to investigate a new class of attribute inference attacks against Online Social Networks (OSN) users. Our methodology analyzes commenters' preferences related to some user publications (e.g., posts or pictures) to infer sensitive attributes of that user. For classification performance, we tune Random Indexing (RI) to compute several embeddings for textual units (e.g., word, emoji), each one depending on a specific attribute value. RI guarantees the comparability of the generated vectors for the different values. To validate the approach, we consider three Facebook attributes: gender, age category and relationship status, which are highly relevant for targeted advertising or privacy threatening applications. By using an XGBoost classifier, we show that we can infer Facebook users' attributes from commenters' reactions to their publications with AUC from 94% to 98%, depending on the traits. |
| Databáze: | OpenAIRE |
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