🔬

Towards Deep Learning Models Resistant to Adversarial Attacks

📅 2017
technical research breakthrough
🔵 Rare

📖 Description

Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander M ? adry MIT [email address redacted] Makelov MIT [email address redacted] Schmidt MIT [email address redacted] Dimitris Tsipras MIT [email address redacted] Vladu MIT [email address redacted] Abstract Recent work has demonstrated that deep neural networks are vulnerable to adversarial examples?inputs that are almost indistinguishable from natural data and yet classi?ed incor- rectly by the network. In fact, some of the latest ?ndings suggest that the existence of adversarial attacks may be an inherent weakness of deep learning models. To address this problem, we study the adversarial robustness of neural networks through the lens of robust optimization. This approach provides us with a broad and unifying view on much of the prior work on this topic. Its principled nature also enables us to identify methods for both training and attacking neural networks that are reliable and, in a certain sense, universal. In particular, they spe...

📊 Game Impacts

Not verified in game

Which variables this event was proposed to move, and in which direction. The magnitudes are held in the corpus but are not shown here, because they have not been verified against the shipped game. They come from pdoom-data. They describe what an event was proposed to do, not what the shipped game does with it. Most events in the corpus are flavour: they are shown for colour and do not move any game variable. Only a small minority reach the systems below, and several of the variables listed here are not read by the game at all yet. Treat this table as a design proposal under review, not as a measurement of play. Corrections and arguments are welcome — the suggestion links at the foot of this page go straight to the data repo.

Variable Direction Condition
Research proposed: up Always
Papers proposed: up Always
Vibey Doom proposed: up Always

💭 Reactions

🔬 Safety Researcher Reaction: Not recorded
📰 Media Reaction: Not recorded
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🔗 Sources

🏷️ Event Metadata

Think this event's metadata could be improved? Category and tags describe the real-world event and are maintained in pdoom-data. Rarity, game impacts and p(doom) effects are game-mechanical values owned by pdoom1. Each link below goes to the repository that decides that field.

📁 Category Technical Research Breakthrough → Suggest different category
⭐ Rarity 🔵 Rare → Suggest different rarity
🏷️ Tags (0) → Suggest tag changes
📊 Game Impacts (3) 3 variable changes → Suggest impact changes
☢️ p(Doom) Impact Not recorded → Suggest p(doom) change
📝 General Metadata Year, description, reactions → Comprehensive review

🤝 Found an Issue?

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