Your Age Revealed by Facebook Picture Metadata

Eidizadehakhcheloo, Sanaz; Pijani, Bizhan Alipour; Imine, Abdessamad; Rusinowitch, Michaël

doi:10.1007/978-3-030-55814-7_22

Cited by 2 publications

(2 citation statements)

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“…Our work is related to [23,5] where gender and age are inferred from Facebook picture metadata. However, here we do not limit ourselves to specific attributes and our attacks apply to many social media by leveraging commenters' preferences related to pictures, posts, and status updates.…”

Section: Related Workmentioning

confidence: 99%

Divide-and-Learn: A Random Indexing Approach to Attribute Inference Attacks in Online Social Networks

Eidizadehakhcheloo

Pijani

Imine

et al. 2021

Data and Applications Security and Privacy XXXV

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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.

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Section: Related Workmentioning

confidence: 99%

Divide-and-Learn: A Random Indexing Approach to Attribute Inference Attacks in Online Social Networks

Eidizadehakhcheloo

Pijani

Imine

et al. 2021

Data and Applications Security and Privacy XXXV

Self Cite

View full text Add to dashboard Cite

show abstract

“…The third paper, "Your Age Revealed by Facebook Picture Metadata" [11] proposes to use machine learning algorithms to infer social media (e.g. Facebook) users' age from metadata related to their pictures.…”

Section: Selected Papersmentioning

confidence: 99%