🤝 Cyberwarfare vulnerabilities for democracy
Research questions:
- What is the current state of cyberwarfare offense / defense balance?
- What are the game-theoretic incentives for international cyber offensives?
- How does the offense / defense balance forecast into the future?
- How does the ease of cyber offense forecast into the future?
- What can we do about cyberwarfare destabilization threats?
Other ideas for research questions:
- What is the cost for cyber attacks and how will this change in the future?
- What are the democracy destabilization threats?
- What if everyone can suddenly launch nation-scale cyber attacks? What happens then?
- What are the risks of AI-powered cyber espionage, intellectual property theft, and surveillance?
- What are the risks of AI-powered cyber espionage, intellectual property theft, and surveillance?
- What unity could help states avoid dangerous escalatory spirals? AI mediator development.
- What safety precautions can be built into AI cyberweapons to constrain effects and prevent blowback? Asimov's law of cyber offense weapons.
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- Make a new challenge for offense
- List of categorized challenges for offense
- Make a new challenge for defense
- List of categorized challenges for defense
Main uncertainty: How do we adequately model the threat landscape for any arbitrary system and what defines a defense solution vs an offense solution. We can easily make something that simulates identifying a Trojan file but since defense will need to cover every single download on the system, this by default seems to be worse off that attack capabilities, both in price, R&D efforts, and implementation difficulty. Additionally, how do we make a system that naturalistically simulates a system with default security measures implemented.
Potential solution: Wizard of Oz setup to literally act as the naturalistic. Fuzzy results but potential for a naturalistic cyber sandbox environment.
- Constraint is on scalability: If we simply run one naturalistic experiment for offense and one for defense, this would somewhat work. We can potentially also delegate this directly to an LLM prompted to be a system and take it from there.
Test on GPT-4, GPT-3, etc. to forecast it from past models to future models.
Properties of the parametric model:
- N national cyber attacks
- Incentives (see [2])
- Cost of cyber attacks
- Cyber capabilities forecasting