We are working on the following broad directions in our group. Some projects are not listed here – contact us for details about these.
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Recent Papers
- A Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks
- SwarmFuzz: Discovering GPS Spoofing Attacks in Drone Swarms
- AChecker: Statically Detecting Smart Contract Access Control Vulnerabilities
- Jujutsu: A Two-stage Defense against Adversarial Patch Attacks on Deep Neural Networks
- A Large-scale Empirical Study of Low-level Function Use in Ethereum Smart Contracts and Automated Replacement
- Characterizing Variability in Heterogeneous Edge Systems: A Methodology & Case Study
- LLTFI: Framework Agnostic Fault Injection for Machine Learning Applications (Tools and Artifact Track)
- Fault Injection for TensorFlow Applications
- eTainter: Detecting Gas-Related Vulnerabilities in Smart Contracts
- The Fault in Our Data Stars: Studying Mitigation Techniques against Faulty Training Data in ML Applications
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