Alternatives and similar repositories for Inverse_Collaborative_Inference

Users that are interested in Inverse_Collaborative_Inference are comparing it to the libraries listed below

• pasquini-dario / SplitNN_FSHA
  Privacy attacks on Split Learning
  ☆42Updated 3 years ago
• ksreenivasan / OOD_Federated_Learning
  ☆69Updated 2 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆56Updated 2 years ago
• Koukyosyumei / Attack_SplitNN
  reveal the vulnerabilities of SplitNN
  ☆31Updated 2 years ago
• SliencerX / Learning-to-Attack-Federated-Learning
  ☆19Updated 2 years ago
• zaixizhang / FLDetector
  The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…
  ☆83Updated 2 years ago
• AI-secure / CRFL
  CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)
  ☆72Updated 3 years ago
• git-disl / CPL_attack
  ☆37Updated 3 years ago
• AdrienBenamira / membership_inference_attack
  Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
  ☆60Updated 6 years ago
• wanglun1996 / secure-robust-federated-learning
  ☆55Updated 2 years ago
• fushuhao6 / Attack-Resistant-Federated-Learning
  ☆30Updated 5 years ago
• TinfoilHat0 / Defending-Against-Backdoors-with-Robust-Learning-Rate
  The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".
  ☆34Updated 2 years ago
• csong27 / property-inference-collaborative-ml
  Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
  ☆53Updated 6 years ago
• jinghuichen / Focused-Flip-Federated-Backdoor-Attack
  Github Repo for AAAI 2023 paper: On the Vulnerability of Backdoor Defenses for Federated Learning
  ☆37Updated 2 years ago
• jhcknzzm / Federated-Learning-Backdoor
  ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341
  ☆73Updated 2 years ago
• jeremy313 / FL-WBC
  Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…
  ☆40Updated 3 years ago
• LPD-EPFL / ByzantineMomentum
  Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)
  ☆22Updated 4 years ago
• najeebjebreel / FL-Defender
  FL-Defender: Combating Targeted Attacks in Federated Learning
  ☆1Updated 2 years ago
• ybdai7 / Chameleon-durable-backdoor
  [ICML 2023] Official code implementation of "Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning (htt…
  ☆41Updated 5 months ago
• KaiyuanZh / FLIP
  [ICLR 2023, Best Paper Award at ECCV’22 AROW Workshop] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning
  ☆56Updated 5 months ago
• vrt1shjwlkr / NDSS21-Model-Poisoning
  Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"
  ☆144Updated 2 years ago
• cchoquette / membership-inference
  Code for the paper: Label-Only Membership Inference Attacks
  ☆65Updated 3 years ago
• jgshu / Attacks-and-Defenses-in-Federated-Learning
  ☆37Updated 4 years ago
• epfml / byzantine-robust-optimizer
  Learning from history for Byzantine Robustness
  ☆23Updated 3 years ago
• yjlee22 / byzantineFL
  PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance
  ☆32Updated 7 months ago
• cpwan / Attack-Adaptive-Aggregation-in-Federated-Learning
  This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.
  ☆44Updated last year
• xinjianluo / featureinference-vfl
  ☆25Updated 3 years ago
• Suyi32 / Learning-to-Detect-Malicious-Clients-for-Robust-FL
  ☆18Updated 4 years ago
• krishnap25 / RFA
  Robust aggregation for federated learning with the RFA algorithm.
  ☆48Updated 2 years ago
• DistributedML / FoolsGold
  A sybil-resilient distributed learning protocol.
  ☆103Updated last year