EDBT 2026 Demo / reviewers in the wild / expert
Ines Abdelaziz
dblp:432/5922
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0006-6868-4113ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Web and mobile security · 50% Systems and software security · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Web and mobile security › web security
online advertising security |
1.0 | 1 | 2026 | Is Contextual Advertising Safe? Analyzing Systemic Risks with Ads on YouTube · WWW 2026 |
Systems and software security
platform security |
1.0 | 1 | 2026 | Is Contextual Advertising Safe? Analyzing Systemic Risks with Ads on YouTube · WWW 2026 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Is Contextual Advertising Safe? Analyzing Systemic Risks with Ads on YouTube
Asmaa El Fraihi, Ines Abdelaziz, Oana Goga |
WWW | 2 |
| 2026 | A Year Under the DSA: Ad Transparency's Uneven LandscapeabstractThe Digital Services Act (DSA) has put platform accountability on center stage, requiring online platforms to provide greater transparency into how advertisements are targeted and delivered to users. Central to these obligations are two mechanisms: user-facing ad explanations, which inform individuals why they were shown a given ad, and public ad repositories, which are intended to enable independent auditing of advertising practices. This study provides the first multi-platform evaluation of these two mechanisms across Facebook, Instagram, YouTube and X. Using 48,511 user-facing “Why am I seeing this ad?” (WAIST) notices, and a systematic analysis of each platform’s public ad repository, we assess how well current implementations disclose the parameters and decision processes involved in targeting. To do so, we develop and apply an operational framework based on Articles 26 and 39 of the DSA—capturing the granularity, attribution of targeting and delivery choices, data source disclosures, and accuracy—and apply it across both user-facing notices and public ad repositories. Our findings show that transparency remains fragmented and inconsistent across platforms. User-facing explanations vary widely in precision and often omit key targeting information, while repositories provide incomplete, misattributed, and at times difficult-to-interpret targeting data. Moreover, discrepancies between explanations and repository entries undermine the reliability of both mechanisms. Overall, current transparency infrastructures fall short of the DSA’s expectations and highlight the need for clearer and more enforceable standards for advertising transparency moving forward. Abir Benzaamia, Asmaa El Fraihi, Ines Abdelaziz, Oana Goga |
Proc. Priv. Enhancing Technol. | 3 |