• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 15 matches

• 2024
• 
  Meenatchi Sundaram Muthu Selva Annamalai, Igor Bilogrevic, Emiliano De Cristofaro:
  FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting. NDSS 2024
• 
  Hossein Fereidooni, Alessandro Pegoraro, Phillip Rieger, Alexandra Dmitrienko, Ahmad-Reza Sadeghi:
  FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning. NDSS 2024
• 
  Torsten Krauß, Jan König, Alexandra Dmitrienko, Christian Kanzow:
  Automatic Adversarial Adaption for Stealthy Poisoning Attacks in Federated Learning. NDSS 2024
• 
  Phillip Rieger, Torsten Krauß, Markus Miettinen, Alexandra Dmitrienko, Ahmad-Reza Sadeghi:
  CrowdGuard: Federated Backdoor Detection in Federated Learning. NDSS 2024
• 2023
• 
  Tianyue Chu, Álvaro García-Recuero, Costas Iordanou, Georgios Smaragdakis, Nikolaos Laoutaris:
  Securing Federated Sensitive Topic Classification against Poisoning Attacks. NDSS 2023
• 
  Chunyi Zhou, Yansong Gao, Anmin Fu, Kai Chen, Zhiyang Dai, Zhi Zhang, Minhui Xue, Yuqing Zhang:
  PPA: Preference Profiling Attack Against Federated Learning. NDSS 2023
• 2022
• 
  Hossein Fereidooni, Alexandra Dmitrienko, Phillip Rieger, Markus Miettinen, Ahmad-Reza Sadeghi, Felix Madlener:
  FedCRI: Federated Mobile Cyber-Risk Intelligence. NDSS 2022
• 
  Mohammad Naseri, Jamie Hayes, Emiliano De Cristofaro:
  Local and Central Differential Privacy for Robustness and Privacy in Federated Learning. NDSS 2022
• 
  Gonzalo De La Torre Parra, Luis Selvera, Joseph Khoury, Hector Irizarry, Elias Bou-Harb, Paul Rad:
  Interpretable Federated Transformer Log Learning for Cloud Threat Forensics. NDSS 2022
• 
  Phillip Rieger, Thien Duc Nguyen, Markus Miettinen, Ahmad-Reza Sadeghi:
  DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection. NDSS 2022
• 2021
• 
  Xiaoyu Cao, Minghong Fang, Jia Liu, Neil Zhenqiang Gong:
  FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping. NDSS 2021
• 
  Sinem Sav, Apostolos Pyrgelis, Juan Ramón Troncoso-Pastoriza, David Froelicher, Jean-Philippe Bossuat, Joao Sa Sousa, Jean-Pierre Hubaux:
  POSEIDON: Privacy-Preserving Federated Neural Network Learning. NDSS 2021
• 
  Virat Shejwalkar, Amir Houmansadr:
  Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning. NDSS 2021
• 2020
• 
  Zhenfeng Zhang, Yuchen Wang, Kang Yang:
  Strong Authentication without Temper-Resistant Hardware and Application to Federated Identities. NDSS 2020
• 2014
• 
  Michael Dietz, Dan S. Wallach:
  Hardening Persona - Improving Federated Web Login. NDSS 2014