Adversarial perturbations fool deepfake detectors with high accuracy.
arXiv research
A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Trend · papers per month
Study compares deepfake detection models, finding GenConViT superior.
FaceSigns embeds a secret watermark in images to authenticate and detect deepfakes.
Deepfake detection is formulated as a hypothesis testing problem to classify an image as genuine or GAN-generated. A robust statistics view of GANs is considered to bound the error probability for various GAN implementations in terms of their performance. The bounds are further simplified using a Euclidean approximatio…
OGAN attacks autoencoders to prevent deepfake creation.
Simple method detects deepfakes with few labeled samples.
Nowadays, organizations collect vast quantities of accounting relevant transactions, referred to as 'journal entries', in 'Enterprise Resource Planning' (ERP) systems. The aggregation of those entries ultimately defines an organization's financial statement. To detect potential misstatements and fraud, international au…
Advbox generates adversarial examples to test neural network robustness.
This paper maps the insurability of AI risks across various insurance products.