NEWSLETTER
Using Optimization to Solve Adversarial Problems | by W Brett Kennedy | Jan, 2025
An example of simultaneously optimizing two policies for two adversarial agents, looking specifically at the cat and mouse game.In the ...
Tag: Adversarial
Frequency Selective Adversarial Attack Against Deep Learning Based Wireless Signal Classifiers
Wireless communication is the foundation of modern systems and enables critical applications in the military, commercial and civil spheres. Its ...
Exploring the connectivity of spatial input modes: Perspectives on adversarial detection and interpretation of deep neural networks
Input space modal connectivity in deep neural networks is based on research on excessive input invariance, blind spots, and connectivity ...
MALT (Mesoscopic Almost Linearity Targeting): a new adversarial selection method based on assumptions of near-linearity at medium scale
Adversarial attacks are attempts to trick a machine learning model into making an incorrect prediction. They work by creating slightly ...
Cloud Removal from Satellite Images Using GAN (Generative Adversarial Networks) | by Aleksei Rozanov | June 2024
Building GAN from scratch in PythonPhoto by Michael and Diane Weidner in unpackthe idea of Generative Adversarial Networks, or GANs, ...
The rise of adversarial AI in cyber attacks
In cybersecurity, while artificial intelligence technologies have significantly strengthened our defense mechanisms against cyber threats, they have also ushered in ...
Are your conversations with AI secure? Exploring the depths of adversarial attacks on machine learning models
A major challenge facing LLM deployment is its susceptibility to adversarial attacks. These are sophisticated techniques designed to exploit model ...
Meet MedGAN: a deep learning model based on Wasserstein generative adversarial networks and graph convolutional networks for the design of novel molecules
The growing urgency of innovative medicines in various medical fields, such as antibiotics, cancer treatments, autoimmune disorders, and antiviral therapies, ...
Revealing Multiple Attacks on Image Classification: How One Adversarial Perturbation Can Fool Hundreds of Images
Adversarial attacks on image classification, a critical issue in ai security, involve subtle changes to images that mislead ai models ...
IBM Researchers Propose a New Adversarial Attack Framework Capable of Generating Adversarial Inputs for AI Systems Regardless of the Modality or Task
In the ever-evolving landscape of artificial intelligence, a growing concern has emerged. The vulnerability of ai models to adversarial evasion ...
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