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Robust and Secure AI

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We identify three specific areas of focus to advance Robust and Secure AI for defense and national security:

• Improving the robustness of AI components and systems and the need to go beyond accuracy measurements to capture achievement of mission outcomes
• Designing for security challenges in modern AI systems including novel attack surfaces and patterns, as well as strategies for risk mitigation
• Developing processes and tools for testing, evaluating, and analyzing AI systems and adoption of comprehensive test and evaluation approaches

For each area, we identify ongoing work as well as challenges and opportunities in developing and deploying AI systems with confidence.

Funding

Department of Defense Contract No. FA8702-15-D-0002

History

Publisher Statement

This material is based upon work funded and supported by the Department of Defense under Contract No. FA8702-15-D-0002 with Carnegie Mellon University for the operation ofthe Software Engineering Institute, a federally funded research and development center. The view, opinions, and/or findings contained in this material are those of the author(s)and should not be construed as an official Government position, policy, or decision, unlessdesignated by other documentation. References herein to any specific commercial product, process, or service by trade name,trade mark, manufacturer, or otherwise, does not necessarily constitute or imply itsendorsement, recommendation, or favoring by Carnegie Mellon University or its Software Engineering Institute. NO WARRANTY. THIS CARNEGIE MELLON UNIVERSITY AND SOFTWARE ENGINEERING INSTITUTE MATERIAL IS FURNISHED ON AN “AS-IS” BASIS. CARNEGIE MELLON UNIVERSITY MAKES NO WARRANTIES OF ANY KIND, EITHER EXPRESSED OR IMPLIED, AS TO ANY MATTER INCLUDING, BUT NOT LIMITED TO, WARRANTY OF FITNESS FOR PURPOSE OR MERCHANTABILITY, EXCLUSIVITY, OR RESULTS OBTAINED FROM USE OF THE MATERIAL. CARNEGIE MELLON UNIVERSITY DOES NOT MAKE ANY WARRANTY OF ANY KIND WITH RESPECT TO FREEDOM FROM PATENT, TRADEMARK, OR COPYRIGHT INFRINGEMENT

Copyright Statement

©2021 Carnegie Mellon University This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution. Internal use:* Permission to reproduce this material and to prepare derivative works from this material for internal use is granted, provided the copyright and “No Warranty” statements are included with all reproductions and derivative works. External use:* This material may be reproduced in its entirety, without modification, and freely distributed in written or electronic form without requesting formal permission. Permission is required for any other external and/or commercial use. Requests for permission should be directed to the Software Engineering Institute at permission@sei.cmu.edu. * These restrictions do not apply to U.S. government entities.

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