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- GitHub - s2underground GhostNet: GhostNet
GhostNet is the overarching term for a collection of communications networks set up to allow users around the world to exchange information without relying on pre-established infrastructure
- GhostNet - Wikipedia
Since its discovery, GhostNet has attacked other government networks, for example Canadian official financial departments in early 2011, forcing them off-line Governments commonly do not admit such attacks, which must be verified by official but anonymous sources
- [1911. 11907] GhostNet: More Features from Cheap Operations
The proposed Ghost module can be taken as a plug-and-play component to upgrade existing convolutional neural networks Ghost bottlenecks are designed to stack Ghost modules, and then the lightweight GhostNet can be easily established
- Ghostnet - JS8Call - by Rick Donaldson - Substack
GhostNet is the overarching term for a collection of communications networks set up to allow users around the world to exchange information without relying on pre-established infrastructure
- GhostNet | CFR Interactives
GhostNet was a large-scale electronic espionage program used to spy on individuals, organizations, and governments The threat actors breached 1,295 computers in 103 countries over a two-year
- GhostNet: More Features From Cheap Operations - IEEE Xplore
Deploying convolutional neural networks (CNNs) on embedded devices is difficult due to the limited memory and computation resources The redundancy in feature m
- Inside GhostNet: The Cyber Espionage Operation That Shocked the World
GhostNet was a sophisticated cyber espionage operation targeting governments, embassies, NGOs, and even the Dalai Lama's offices Canadian researchers from the Information Warfare Monitor discovered GhostNet in 2009, finding it infected an astounding 1,295 computers across 103 countries
- GhostNet – PyTorch
The GhostNet architecture is based on an Ghost module structure which generate more features from cheap operations Based on a set of intrinsic feature maps, a series of cheap operations are applied to generate many ghost feature maps that could fully reveal information underlying intrinsic features
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