Name
Title | ||
|---|---|---|
ACM KDD AI4Cyber/MLHat: Workshop on AI-enabled Cybersecurity Analytics and Deployable Defense |
Abstract | ||
|---|---|---|
Federal funding agencies and industry entities are seeking innovative approaches to address the ever-growing cybersecurity crisis. Increasingly, numerous cybersecurity thought leaders are indicating that Artificial Intelligence (AI)-enabled analytics can help tackle key cybersecurity tasks and deploy defenses. This half-day workshop, co-located with ACM KDD, sought to attain significant research contributions to various aspects of AI-enabled analytics for cybersecurity applications and deployable defense solutions from academics and practitioners. This workshop was a joint workshop of the 2021 AI-enabled Cybersecurity Analytics and 2021 International Workshop on Deployable Machine Learning for Security Defense. As such, we developed an interdisciplinary Program Committee with significant experience in various aspects of AI, cybersecurity, and/or deployable defense. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3534678.3542894 | KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sagar Samtani | 1 | 4 | 2.42 |
| Gang Wang | 2 | 0 | 0.34 |
| ali ahmadzadeh | 3 | 1 | 1.70 |
| Arridhana Ciptadi | 4 | 0 | 0.68 |
| Shanchieh Yang | 5 | 0 | 0.34 |
| Hsinchun Chen | 6 | 9569 | 813.33 |