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Cyber Threat Intelligence (CTI) is information describing threat vectors, vulnerabilities, and attacks and is often used as training data for AI-based cyber defense systems such as Cybersecurity Knowledge Graphs (CKG). There is a strong need to develop community-accessible datasets to train existing AI-based cybersecurity pipelines to efficiently and accurately extract meaningful insights from CTI. We have created an initial unstructured CTI corpus from a variety of open sources that we are using to train and test cybersecurity entity models using the spaCy framework and exploring self-learning methods to automatically recognize cybersecurity entities. We also describe methods to apply cybersecurity domain entity linking with existing world knowledge from Wikidata. Our future work will survey and test spaCy NLP tools, and create methods for continuous integration of new information extracted from text.
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Interim Report for Ubuntu-AI: A Bottom-up Approach to More Democratic and Equitable Training and Outcomes for Machine Learning
Artificial Intelligence (AI) can be a threat to creative arts and design, taking data and images without permission or compensation. But with AI becoming a global portal for human knowledge access, anyone resisting inclusion in its data inputs will become invisible to its outputs. This is the AI double bind, in which the threat of exclusion forces us to give up any claims of ownership to our creative endeavors. To address such problems, this project develops an experimental platform designed to return value to those who create it, using a case study on African arts and design. If successful, it will allow African creatives to work with AI instead of against it, creating new opportunities for funding, gaining wider dissemination of their work, and creating a database for machine learning that results in more inclusive knowledge of African arts and design for AI outputs.
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- Award ID(s):
- 2128756
- PAR ID:
- 10543852
- Publisher / Repository:
- researchgate
- Date Published:
- Subject(s) / Keyword(s):
- AI generative justice platform cooperative solidarity economy
- Format(s):
- Medium: X
- Location:
- https://www.researchgate.net/publication/374870830_Interim_Report_for_Ubuntu-AI_A_Bottom-up_Approach_to_More_Democratic_and_Equitable_Training_and_Outcomes_for_Machine_Learning
- Sponsoring Org:
- National Science Foundation
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