Security of Deep Learning Methodologies: Challenges and Opportunities
arXiv:1912.03735v13 citations
Originality Synthesis-oriented
AI Analysis
It highlights a gap in security research for AI practitioners, but is incremental as it reviews existing issues without new solutions.
The paper addresses the understudied security vulnerabilities of deep learning methodologies like transfer learning, identifying specific challenges and research opportunities.
Despite the plethora of studies about security vulnerabilities and defenses of deep learning models, security aspects of deep learning methodologies, such as transfer learning, have been rarely studied. In this article, we highlight the security challenges and research opportunities of these methodologies, focusing on vulnerabilities and attacks unique to them.