xumengwei / MobileDL
Detecting and analyzing deep learning usage on smartphone apps
☆31Updated 10 months ago
Related projects ⓘ
Alternatives and complementary repositories for MobileDL
- ☆27Updated 2 months ago
- On-device Machine Learning model analyzer and extractor for Android Apps, check out our USENIX Security'21 paper "Mind Your Weight(s): A …☆27Updated 2 years ago
- This is the implementation repository of our ICSE'22 paper: Muffin: Testing Deep Learning Libraries via Neural Architecture Fuzzing.☆30Updated 2 years ago
- LibD: Scalable and Precise Third-party Library Detection in Android Markets☆68Updated 5 years ago
- ☆22Updated 3 years ago
- An Empirical Study of AI Techniques in Mobile Applications☆12Updated 5 months ago
- This is the artifact for paper “Are Machine Learning Cloud APIs Used Correctly? (#421)” in ICSE2021☆15Updated 3 years ago
- DNN Coverage Based Testing Study☆16Updated 4 years ago
- ☆17Updated 3 years ago
- A novel and interpretable ML-based approach to classify malware with high accuracy and explain the classification result meanwhile.☆26Updated 2 years ago
- Adversarial Robustness for Code☆16Updated 3 years ago
- This is the implement repository of our upcoming ESEC/FSE 2020 paper: Deep Learning Library Testing via Effective Model Generation.☆54Updated last year
- Project FlowCog (2017)☆26Updated 6 years ago
- Implementation of DeepIntent: Deep Icon-Behavior Learning for Detecting Intention-Behavior Discrepancy in Mobile Apps☆34Updated 2 years ago
- ☆74Updated last year
- This repository contains the implementation and the evaluation of our ESEC/FSE 2020 paper: Detecting Numerical Bugs in Neural Network Ar…☆26Updated 3 years ago
- Learning Security Classifiers with Verified Global Robustness Properties (CCS'21) https://arxiv.org/pdf/2105.11363.pdf☆26Updated 2 years ago
- Robustness of on-device Models: AdversarialAttack to Deep Learning Models on Android Apps☆16Updated 2 years ago
- ☆25Updated last year
- This is the implementation repository of our incoming ESEC/FSE 2021 paper: Exposing Numerical Bugs in Deep Learning via GradientBack-prop…☆13Updated 2 years ago
- Code for the paper: "Adversarial Examples for Models of Code"☆17Updated 4 years ago
- [ICLR 2021] "Generating Adversarial Computer Programs using Optimized Obfuscations" by Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shi…☆26Updated 3 years ago
- Flow analysis using Soot☆51Updated 4 years ago
- DLFuzz: An Efficient Fuzzing Testing Framework of Deep Learning Systems☆51Updated 6 years ago
- Code for ICML 2021 paper: How could Neural Networks understand Programs?☆122Updated 2 weeks ago
- This repository contains the dataset of our ISSTA 2018 paper: An Empirical Study on TensorFlow Program Bugs.☆30Updated 4 years ago
- ☆15Updated 2 years ago
- [ICSE 2023] Differentiable interpretation and failure-inducing input generation for neural network numerical bugs.☆12Updated 10 months ago