Paper Awards at the NDSS Symposium 2025

Two papers from TUDA – Technische Universität Darmstadt
received Distinguished Paper Awards at the NDSSSymposium 2025, one of the top four security conferences worldwide:

✅ Rieger et al., SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning NDSS, 2025 –https://www.ndss-symposium.org/wp-content/uploads/2025-1698-paper.pdf

✅ Kumari et al., VoiceRadar: Voice Deepfake Detection using Micro-Frequency and Compositional Analysis, NDSS, 2025 – https://www.ndss-symposium.org/wp-content/uploads/2025-3389-paper.pdf

Congrats to TUDA, ACES partner for receiving the Distinguished Paper Award at NDSS Symposium 2025 for both papers!!

0 Comments

Submit a Comment

Your email address will not be published. Required fields are marked *

Related content

9th IEEE International Conference on Fog and Edge Computing 2025 – A new paper from ACES consortium will be presented

A new paper from the ACES consortium - a collaboration between LAKE and SUPSI - has been accepted at the 9th IEEE International Conference on Fog and Edge Computing...
Technischen Universität Darmstadt

TECHNISCHEN UNIVERSITÄT DARMSTADT

TU Darmstadt (TUD) contributes to the ACES project by analyzing security risks and developing novel approaches to ensure the security and robustness of ACES systems...
Hiro Microdatacenters

HIRO MICRODATACENTERS

The Cognitive Framework is a platform designed to equip edge data centers (EMDCs) with autopoietic capabilities, allowing them to self-maintain and dynamically manage...
Martel Innovate

MARTEL INNOVATE

With MARTEL primarily focusing on providing the workflow management service that is implemented via Prefect Orchestration. This component orchestrates and executes...
Politécnica

UNIVERSIDAD POLITÉCNICA DE MADRID

Partners from UPM are working on the providing the sub- component that is responsible for graph queries and time series databases, building and analysing graphs using...
Idsia Supsi

SUPSI

The Cognitive Engine employs a self-hyperparameter tuning subcomponent to iteratively optimize complex black-box functions in a decentralized manner. In ACES, this...