TY - GEN
T1 - The 3rd Workshop on Artificial Intelligence-enabled Cybersecurity Analytics
AU - Samtani, Sagar
AU - Yang, Shanchieh
AU - Chen, Hsinchun
N1 - Publisher Copyright:
© 2023 Owner/Author.
PY - 2023/8/6
Y1 - 2023/8/6
N2 - Artificial Intelligence (AI) has gripped modern society as a viable approach to revolutionize operational capabilities across multiple industries. One critical application area that could stand to benefit from the capabilities of AI is cybersecurity. Increasingly, federal funding agencies such as the National Science Foundation are calling for enhanced AI-enabled analytics capabilities to improve cyber threat intelligence, cyber defense generation, and more. To this end, this half-day workshop, not in its third year at ACM KDD, sought to attain significant contributions related to various aspects of AI-enabled cybersecurity analytics. This workshop received a record number of submissions. Submissions were reviewed by a highly-qualified, interdisciplinary group of AI for cybersecurity researchers and practitioners spanning academia and private industry firms.
AB - Artificial Intelligence (AI) has gripped modern society as a viable approach to revolutionize operational capabilities across multiple industries. One critical application area that could stand to benefit from the capabilities of AI is cybersecurity. Increasingly, federal funding agencies such as the National Science Foundation are calling for enhanced AI-enabled analytics capabilities to improve cyber threat intelligence, cyber defense generation, and more. To this end, this half-day workshop, not in its third year at ACM KDD, sought to attain significant contributions related to various aspects of AI-enabled cybersecurity analytics. This workshop received a record number of submissions. Submissions were reviewed by a highly-qualified, interdisciplinary group of AI for cybersecurity researchers and practitioners spanning academia and private industry firms.
KW - analytics
KW - artificial intelligence
KW - cybersecurity
KW - large language models
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85171346637&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85171346637&partnerID=8YFLogxK
U2 - 10.1145/3580305.3599229
DO - 10.1145/3580305.3599229
M3 - Conference contribution
AN - SCOPUS:85171346637
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 5880
EP - 5881
BT - KDD 2023 - Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PB - Association for Computing Machinery
T2 - 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023
Y2 - 6 August 2023 through 10 August 2023
ER -