Alternatives and similar repositories for AI-Security-for-IoT-and-Mobile:

Users that are interested in AI-Security-for-IoT-and-Mobile are comparing it to the libraries listed below

• csl-cqu / awesome-secure-federated-learning-papers
  ☆29Updated 2 years ago
• liuyugeng / ML-Doctor
  Code for ML Doctor
  ☆87Updated 8 months ago
• csong27 / property-inference-collaborative-ml
  Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
  ☆53Updated 5 years ago
• naiyeleo / ABS
  ABS: Scanning Neural Networks for Back-doors by Artificial Brain Stimulation
  ☆50Updated 2 years ago
• tribhuvanesh / knockoffnets
  Knockoff Nets: Stealing Functionality of Black-Box Models
  ☆95Updated 2 years ago
• AhmedSalem2 / ML-Leaks
  Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"
  ☆83Updated 3 years ago
• yziqi / adversarial-model-inversion
  Code for "Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment" (CCS 2019)
  ☆46Updated 5 years ago
• alps-lab / Trojan-Zoo
  TrojanZoo is a universal pytorch platform for conducting security researches (especially for backdoor attacks/defenses) for image classif…
  ☆19Updated 4 years ago
• garrisongys / STRIP
  This is for releasing the source code of the ACSAC paper "STRIP: A Defence Against Trojan Attacks on Deep Neural Networks"
  ☆55Updated 5 months ago
• AI-secure / Meta-Nerual-Trojan-Detection
  ☆64Updated 4 years ago
• PurduePAML / TrojanNN
  Trojan Attack on Neural Network
  ☆183Updated 3 years ago
• Kooscii / BadNets
  ☆94Updated 4 years ago
• nthu-datalab / On.the.Trade-off.between.Adversarial.and.Backdoor.Robustness
  Code for "On the Trade-off between Adversarial and Backdoor Robustness" (NIPS 2020)
  ☆17Updated 4 years ago
• cchoquette / membership-inference
  Code for the paper: Label-Only Membership Inference Attacks
  ☆65Updated 3 years ago
• columbia / pixeldp
  ☆64Updated 5 years ago
• inspire-group / privacy-vs-robustness
  Privacy Risks of Securing Machine Learning Models against Adversarial Examples
  ☆44Updated 5 years ago
• kangliucn / Fine-pruning-defense
  Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks (RAID 2018)
  ☆48Updated 6 years ago
• yuanchun-li / ModelDiff
  ☆18Updated 3 years ago
• csong27 / ml-model-remember
  Code for Machine Learning Models that Remember Too Much (in CCS 2017)
  ☆30Updated 7 years ago
• elliothe / Neural_Network_Weight_Attack
  Changing several bit which overwhelms the quantized CNN
  ☆42Updated 5 years ago
• jinyuan-jia / MemGuard
  ☆45Updated 5 years ago
• Testing4AI / DeepJudge
  Code release for DeepJudge (S&P'22)
  ☆51Updated 2 years ago
• pasquini-dario / SplitNN_FSHA
  Privacy attacks on Split Learning
  ☆40Updated 3 years ago
• ziqi-zhang / TEESlice-artifact
  ☆31Updated 2 weeks ago
• hyhmia / BlindMI
  ☆23Updated 2 years ago
• cake-lab / datafree-model-extraction
  CVPR 2021 Official repository for the Data-Free Model Extraction paper. https://arxiv.org/abs/2011.14779
  ☆71Updated last year
• jinyuan-jia / BadEncoder
  ☆81Updated 3 years ago
• trx14 / TrojanNet
  ☆85Updated last year
• yashkant / model-inversion-attack
  Implementation of the Model Inversion Attack introduced with Model Inversion Attacks that Exploit Confidence Information and Basic Counte…
  ☆84Updated 2 years ago
• bboylyg / NAD
  This is an implementation demo of the ICLR 2021 paper [Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks…
  ☆122Updated 3 years ago