Demo Data from EDBT 2026 / reviewers in the wild / expert
Marguerite Delcourt
dblp:255/5050
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0002-8305-6581ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1 · 1 first-author · 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.
| Computer networks
1 paper |
Wireless sensing and localization · 100% | |
| Network and information security
1 paper |
Cyber-physical and IoT security · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless sensing and localization
source localization |
0.5 | 1 | 2021 | TDOA Source-Localization Technique Robust to Time-Synchronization Attacks · IEEE Trans. Inf. Forensics Secur. 2021 |
Wireless sensing and localization › range-based localization › time-based localization
time-difference-of-arrival localization |
0.5 | 1 | 2021 | TDOA Source-Localization Technique Robust to Time-Synchronization Attacks · IEEE Trans. Inf. Forensics Secur. 2021 |
Cyber-physical and IoT security › smart grid security
time synchronization attacks |
0.5 | 1 | 2021 | TDOA Source-Localization Technique Robust to Time-Synchronization Attacks · IEEE Trans. Inf. Forensics Secur. 2021 |
Methods — techniques the papers use, named apart from their topics
weighted least-squares estimation · 1.0residual analysis · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | TDOA Source-Localization Technique Robust to Time-Synchronization AttacksabstractIn this paper, we focus on the localization of a passive source from time difference of arrival (TDOA) measurements. TDOA values are computed with respect to pairs of fixed sensors that are required to be accurately time-synchronized. This constitutes a weakness as all synchronization techniques are vulnerable to delay injections. Attackers are able either to spoof the signal or to inject asymmetric delays in the communication channel. By nature, TDOA measurements are highly sensitive to time-synchronization offsets between sensors. We first illustrate that time-synchronization attacks can severely affect the localization process. With a delay of a few microseconds injected on one sensor, the resulting estimate might be several kilometers away from the true location of the unknown source. We show that residual analysis does not enable the detection and identification of time-synchronization attacks. Our main contribution is then to propose a two-step TDOA-localization technique that is robust against time-synchronization attacks. It uses a known source to define a weight for each pair of sensors, reflecting the confidence in their time synchronization. Our solution then uses the weighted least-squares estimator with the newly created weights and the TDOA measurements received from the unknown source. As a result, our method either identifies the network as being too corrupt to localize, or gives a corrected estimate of the unknown position along with a confidence metric. Numerical results illustrate the performance of our technique. Marguerite Delcourt, Jean-Yves Le Boudec |
IEEE Trans. Inf. Forensics Secur. | 1 |