Data Mining for Cybersecurity

网络安全数据挖掘

• 批准号: CRC-2019-00041
• 负责人: Fung, Benjamin
• 金额: $ 7.29万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=695899
• 关键词: Data; Mining; Cybersecurity

Cybersecurity professionals are swamped by volumes of data. There is a pressing need to identify malicious activities and convert them to interpretable knowledge so that timely and effective actions can be taken. Recently, deep learning, a subarea of artificial intelligence, has shown many promising breakthroughs in many areas. The objective of this research program is to enhance the deep learning capability of the cybersecurity and privacy communities with an emphasis on malware analysis and authorship anonymization. The results will strengthen the protection of critical cyber infrastructures in Canada and support freedom of expression in the world movement for democracy.

网络安全专业人员被大量数据淹没。有紧迫的需求 确定恶意活动并将其转换为可解释的知识，以便 可以采取及时有效的行动。最近，深度学习，一个子区域 人工智能在许多领域表现出许多有希望的突破。这 该研究计划的目的是增强 网络安全和隐私社区，重点是恶意软件分析和 作者匿名。结果将加强关键网络的保护 加拿大的基础设施并支持世界运动中的言论自由 民主。