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Expecting (Targeted Ads)? Network Analysis of User Health Data Leakage in Fertility Tracking Apps

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arXiv:2606. 26276v1 Announce Type: new Abstract: While human factors in the privacy of fertility tracking apps -- health trackers that record user's menstrual or pregnancy data -- has been the subject of extensive study, little attention has been paid to the technical aspects of apps' data handling practices.

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Authors: Yeeun Jo, Shahanaasree Sivakumar, Mahnoor Jameel, Camille Cobb, Adam Bates, Brad Reaves
Released: 2026-06-26 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because Expecting (Targeted Ads)? Network Analysis of User Health Data Leakage in Fertility Tracking Apps overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: text, under, without, factor, leakage, model. Source: arxiv cs.CR (Cryptography and Security).
arXiv: 2606.26276

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