超级预测"技术奇点"来自人工智能的风险
Petar Radanliev1, David De Roure1, Carsten Maple2
1Oxford e-Research Centre, Department of Engineering Sciences, University of Oxford, Oxford, UK.
概括
本研究引入了管理人工智能 (AI) 风险的新框架,重点关注系统应对网络威胁和AI故障的弹性. 它预测新出现的AI驱动的网络风险,并开发基于AI的防御策略.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 网络安全 网络安全
背景情况:
- 人工智能 (AI) 的日益集成带来了新的网络安全挑战.
- 传统的安全措施对复杂的AI驱动威胁和潜在的系统故障是不够的.
研究的目的:
- 制定一个预测和抵消AI相关网络安全风险的框架.
- 分析系统对内部和外部故障和妥协的响应.
- 探索AI在防御AI特定网络威胁中的作用.
主要方法:
- 构建与AI和网络安全相关的多个风险预测.
- 综合预测与现有的文献和数据来源.
- 开发用于人工智能驱动的网络防御的新方法.
主要成果:
- 一个新的框架来抵消人工智能风险,强调系统弹性.
- 预测人工智能集成带来的新兴网络风险.
- 使用人工智能防御人工智能攻击和流设备的方法.
结论:
- 确保所有系统的安全是不可行的;重点必须转向弹性和响应.
- 人工智能可以用于先进的网络防御和预防AI相关威胁.
- 新型人工智能驱动的方法对于未来的网络安全至关重要.
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