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Found 6 papers, 3 papers with code
Embedding Attack Project (Work Report)
This report summarizes all the MIA experiments (Membership Inference Attacks) of the Embedding Attack Project, including threat models, experimental setup, experimental results, findings and discussion.
Deepfake Text Detection: Limitations and Opportunities
Several defenses have been proposed for deepfake text detection.
Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models
The potential for fraudulent claims based on such generated 'fake' medical images is significant, and we demonstrate successful attacks on both X-rays and retinal fundus image modalities.
T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification
T-Miner employs a sequence-to-sequence (seq-2-seq) generative model that probes the suspicious classifier and learns to produce text sequences that are likely to contain the Trojan trigger.
Deepfake Videos in the Wild: Analysis and Detection
AI-manipulated videos, commonly known as deepfakes, are an emerging problem.
Throwing Darts in the Dark? Detecting Bots with Limited Data using Neural Data Augmentation
We evaluate this idea and show our method can train a model that outperforms existing methods with only 1% of the labeled data.
