Feifei Li



ACM杰出科学家。1994-1997年在清华附中国家教委理科实验班学习,1997年入学清华大学电机系,后转学至新加坡南洋理工大学并于2002年本科毕业,获得计算机专业学士学位。2007年毕业于美国波士顿大学,获计算机专业博士学位。2007年到2011年担任美国佛罗里达州立大学计算机系终身教授(助理教授)。2011至今为美国犹他大学计算机系终身教授(先后为副教授、正教授)。2018年加入阿里巴巴担任集团副总裁,阿里云智能数据库系统事业部总裁、高级研究员,达摩院数据库首席科学家,达摩院数据库与存储实验室负责人。主要研究方向是据库系统架构设计及理论、大数据处理和分析系统设计和理论、海量结构和非结构数据的检索、挖掘和系统处理、大数据处理中的安全问题、大数据在云平台上的支持和处理等,至今在一流国际学术会议与期刊(CCF A类会议和期刊) 上发表论文100余篇。曾获NSF、ACM、IEEE、Visa、Google、HP、华为等多个奖项,获IEEE ICDE 2014 10年最有影响力论文奖、ACM SIGMOD 2016最佳论文奖、ACM SIGMOD 2015最佳系统演示奖、IEEE ICDE 2004最佳论文奖、美国NSF Career Award、中国基金委海外重点研发奖。担任多个国际一流学术期刊和学术会议的编委、主席。

Keynote Title

Scalable and Secure Data Management and Analaytics in the Cloud


With the increasing adoption of cloud computing as an infrastructure, large amount of data have been moved from on-premise deployment to a cloud environment, and many such data resides in a cloud database system. The remote access of data inevitably raises the issues and concerns on data security. Traditional database security mechanism such as access control, TDE, Data at Rest Encryption, BYOK and other technical solutions can only guarantee the protection of data during transmission, access, delivery, and storage. Once data is inside a cloud database kernel, it is still vulnerable and subject to insider attacks. Ensuring that data is protected by encryption when entering the database kernel for transaction and query processing for the entire duration is thus a key challenge. The use of cryptographic techniques such as homomorphism and semi-homomorphic encryption can solve this challenge, but at the same time introduce considerable performance degradation, and security weakness against complex queries and data processing. Providing an efficient full-fledged and scalable secure cloud database under a strict security system (such as semantic security model) needs to be carefully addressed by combining applied security, cryptography, and system technologies. In addition, cloud database systems also need to provide protection for integrity and tamper-resistance. This talk will introduce the preliminary work we have done using a hardware and software co-design approach in this direction and provide a overview of scalable and secure data management and analytics in the Cloud.