AI for Information Security call for proposals — Fall 2024


About this CFP

AWS is committed to helping customers achieve the highest levels of security in the cloud. Our security services use cutting-edge machine learning algorithms to improve the security posture of AWS accounts. We aim to continue advancing possible solutions for some of the most challenging problems in information security. We are seeking to fund machine learning research on the following topics in information security:

  • Threat, intrusion, and anomaly detection for cloud security
  • Generative AI and foundation models for information security
  • Graph modeling and anomaly detection on graphs
  • Learning with limited/noisy labels and weakly supervised learning
  • ML for malware analysis and detection, with a focus on cloud environments or devices
  • Finding security vulnerabilities using ML
  • Causal inference for information security
  • Zero/one-shot learning for information security
  • Reinforcement learning for information security
  • Protecting and preserving data privacy in the cloud
  • Securing generative AI and foundation models

Timeline

Submission period: September 25, 2024 – November 6, 2024 (11:59PM Pacific Time)

Decision letters will be sent out February 2025

Award details

Selected Principal Investigators (PIs) may receive the following:

  • Unrestricted funds, no more than $80,000 USD on average
  • AWS Promotional Credits, no more than $40,000 USD on average

Awards are structured as one-year unrestricted gifts. The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel.

Eligibility requirements

Please refer to the ARA Program rules on the Rules and Eligibility page.

Proposal requirements

Proposals should be prepared according to the proposal template.

Selection criteria

AI for Information Security will make the funding decisions based on the potential impact to the research community and quality of the scientific content.

Expectations from recipients

To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.





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