CAREER: SAIF: Security Assurance through AI and Formal Approaches for System-on-Chips

职业：SAIF：通过人工智能和片上系统的正式方法提供安全保证

• 批准号: 2339971
• 负责人: Farimah Farahmandi
• 金额: $ 55.1万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-03-01 至 2029-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2339971&HistoricalAwards=false
• 关键词: CAREER; SAIF; Security; Assurance; through

Integrated circuits are critical components in many vital electronic devices and systems, including those used in financial services, military and defense applications, healthcare systems, and business operations. Such circuits are subject to an ever-growing number of security vulnerabilities and attacks due to their complex functionality, increased interactions among numerous functional blocks, and connectivity to the internet. Any failure of security and trust requirements of such circuits can lead to sensitive information leakage, privacy violations, critical infrastructure damage, and potentially endanger of human life. Examining the security of such complex circuits is therefore critical, but at the same time challenging, in that it requires innovative solutions to tackle complexity, a large number of security vulnerabilities, and various methods of attack. This project develops an innovative artificial intelligence (AI)-assisted security verification framework called SAIF to address the following objectives: (i) provide high verification coverage, (ii) lower security verification time by orders of magnitude by taking humans out of the process, (iii) provide scalability of circuit complexity, and (iv) offer adaptability to new attack surfaces. SAIF provides the design and verification engineers with properties and tools to check for security vulnerabilities before fabrication. SAIF uses AI to develop a comprehensive database of security properties and rules, support functional security property generation, assist security rule generation and verification, and facilitate AI- test generation for security verification and validation. This project will integrate research and educational activities by developing a modified curriculum/syllabus for high schoolers, workforce development, minority recruiting, training/workshops for K-12 and undergraduate students, and disseminating research results through publications, seminars, tutorials, and panels.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

集成电路是许多重要电子设备和系统中的关键组件，包括用于金融服务、军事和国防应用、医疗保健系统和商业运营的电子设备和系统。这些电路由于其复杂的功能、众多功能块之间增加的交互以及与互联网的连接而受到越来越多的安全漏洞和攻击。这种电路的安全和信任要求的任何失败都可能导致敏感信息泄漏、隐私侵犯、关键基础设施损坏以及潜在的人类生命危险。因此，检查这种复杂电路的安全性至关重要，但同时也具有挑战性，因为它需要创新的解决方案来解决复杂性，大量的安全漏洞和各种攻击方法。该项目开发了一个创新的人工智能（AI）辅助安全验证框架，称为SAIF，以解决以下目标：（i）提供高验证覆盖率，（ii）通过将人类排除在过程之外，以数量级降低安全验证时间，（iii）提供电路复杂性的可扩展性，以及（iv）提供对新攻击表面的适应性。SAIF为设计和验证工程师提供了在制造之前检查安全漏洞的属性和工具。SAIF使用AI开发安全属性和规则的综合数据库，支持功能安全属性生成，辅助安全规则生成和验证，并促进AI测试生成以进行安全验证和确认。该项目将整合研究和教育活动，为高中生、劳动力发展、少数民族招聘、K-12和本科生培训/讲习班制定经修改的课程/教学大纲，并通过出版物、研讨会、辅导、该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准。