arXiv Machine Learning July 9, 2026 By Raja Hasnain Anwar, Jonah O'Brien Weiss, Tiago Alves, Sandip Kundu

InferNet: Exploiting Aggregate GPU Profiles as Side-Channel for DNN Architecture Inference

Read the original on arXiv Machine Learning →

arXiv:2304. 03388v2 Announce Type: replace Abstract: Deep Neural Networks (DNNs) have become ubiquitous for their ability to solve problems across various domains, including computer vision, natural language processing, and speech recognition.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

Aug 6

One Surrogate to Fool Them All: Universal, Transferable, and Targeted Adversarial Attacks with CLIP

arXiv:2505. 19840v3 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) have achieved widespread success yet remain prone to adversarial attacks.

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arXiv Machine Learning

Jun 4

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks

arXiv:2606. 04317v1 Announce Type: cross Abstract: Deep neural networks are increasingly deployed across heterogeneous and partially untrusted environments, where models are distributed through cloud storage, CI/CD pipelines, containerized services, and edge execution platforms.

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arXiv Machine Learning

Jun 2

A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs

arXiv:2606. 02267v1 Announce Type: new Abstract: The vulnerability of deep neural networks to adversarial examples poses a significant challenge for real-world deployment.

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arXiv AI

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arXiv AI

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llms

arXiv Machine Learning

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arXiv:2606. 11098v1 Announce Type: cross Abstract: Recent deep learning approaches for network intrusion detection increasingly incorporate temporal architectures such as recurrent networks and Transformers, often reporting near-perfect performance on CIC-IDS2017.

By Zach Moczkodan (Royal Military College of Canada, Kingston, Canada), Hany Ragab (Royal Military College of Canada, Kingston, Canada)

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Related stories

One Surrogate to Fool Them All: Universal, Transferable, and Targeted Adversarial Attacks with CLIP

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks

A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs

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