BppAttack: Stealthy and Efficient Trojan Attacks against Deep Neural Networks via Image Quantization and Contrastive Adversarial Learning | 0 | 0.34 | 2022 |
TRADER: trace divergence analysis and embedding regulation for debugging recurrent neural networks | 0 | 0.34 | 2020 |
ProFuzzer: On-the-fly Input Type Probing for Better Zero-Day Vulnerability Discovery | 3 | 0.38 | 2019 |
SLF: fuzzing without valid seed inputs | 6 | 0.42 | 2019 |
MODE: automated neural network model debugging via state differential analysis and input selection. | 22 | 1.01 | 2018 |
Debugging with intelligence via probabilistic inference. | 1 | 0.35 | 2018 |
LAMP: data provenance for graph based machine learning algorithms through derivative computation | 5 | 0.43 | 2017 |
A Hypervisor Level Provenance System to Reconstruct Attack Story Caused by Kernel Malware. | 0 | 0.34 | 2017 |
Automatic model generation from documentation for Java API functions. | 11 | 0.57 | 2016 |
ProTracer: Towards Practical Provenance Tracing by Alternating Between Logging and Tainting. | 29 | 0.79 | 2016 |
HERCULE: attack story reconstruction via community discovery on correlated log graph. | 13 | 0.63 | 2016 |
Accurate, Low Cost and Instrumentation-Free Security Audit Logging for Windows | 13 | 0.61 | 2015 |