Pacific Northwest National Laboratory reports that scientists are using generative AI to accelerate defense against cyberattacks, performing complex operations in minutes instead of weeks. A team led ...

Abstract: Space-air-ground integrated networks (SAGINs) face unprecedented security challenges due to their inherent characteristics, such as multidimensional heterogeneity and dynamic topologies.

Abstract: Deep neural networks are increasingly used in image processing tasks. However, deep learning models often show vulnerability when facing adversarial attacks. Active defense is an important ...

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...

ESET researchers provide insights into how PlushDaemon performs adversary-in-the-middle attacks using a previously undocumented network implant that we have named EdgeStepper, which redirects all DNS ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

AT&T is using a generative AI system to help control network operations, a move that the carrier said is a step toward greater network autonomy. Raj Savoor, VP of network analytics and automation at ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this work, we introduce auxiliary discriminator sequence generative adversarial ...

Generative AI is no longer a promise for the distant future for IT departments. It is on its way to becoming a practical tool that will change the way networks are managed. Traditional network ...

Offensive measures are “an important tool of the toolbox that we’ll be unafraid to use,” Alexei Bulazel said. “But that’s not to say we don’t need to do normal blocking-and-tackling cyber defense.” ...

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