Intel and the Georgia Institute of Technology have been selected to lead a Guaranteeing Artificial Intelligence (AI) Robustness against Deception (GARD) program team for the Defense Advanced Research Projects Agency (DARPA).
The goal of the GARD program is to establish theoretical ML system foundations that will not only identify system vulnerabilities and characterize properties to enhance system robustness, but also promote the creation of effective defenses. Through these program elements, GARD aims to create deception-resistant ML technologies with stringent criteria for evaluating their effectiveness.
The first phase of GARD will focus on enhancing object detection technologies through spatial, temporal and semantic coherence for both still images and videos.
Intel is the prime contractor in this four-year, multimillion-dollar joint effort to improve cybersecurity defenses against deception attacks on machine learning (ML) models.
“Intel and Georgia Tech are working together to advance the ecosystem’s collective understanding of and ability to mitigate against AI and ML vulnerabilities. Through innovative research in coherence techniques, we are collaborating on an approach to enhance object detection and to improve the ability for AI and ML to respond to adversarial attacks,” states Jason Martin, principal engineer at Intel Labs and principal investigator for the DARPA GARD program from Intel.