@inproceedings{cb570bbeb482462f8856fd152e03d9f3,
title = "The 4th Workshop on Artificial Intelligence-enabled Cybersecurity Analytics",
abstract = "Cybersecurity remains a grand societal challenge. Large and constantly changing attack surfaces are non-trivial to protect against malicious actors. Entities like the United States and the European Union have recently emphasized the value of Artificial Intelligence (AI) for advancing cybersecurity. For example, the National Science Foundation has called for AI systems that can enhance cyber threat intelligence, detect new and evolving threats, and analyze massive troves of cybersecurity data. The 4th Workshop on Artificial Intelligence-enabled Cybersecurity Analytics (co-located with ACM KDD) sought to make significant and novel contributions within these relevant topics. Submissions were reviewed by highly qualified AI for cybersecurity researchers and practitioners spanning academia and private industry firms.",
keywords = "analytics, artificial intelligence, cybersecurity, large language models, machine learning",
author = "Steven Ullman and Ampel, {Benjamin M.} and Sagar Samtani and Shanchieh Yang and Hsinchun Chen",
note = "Publisher Copyright: {\textcopyright} 2024 Copyright held by the owner/author(s).; 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2024 ; Conference date: 25-08-2024 Through 29-08-2024",
year = "2024",
month = aug,
day = "24",
doi = "10.1145/3637528.3671494",
language = "English (US)",
series = "Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
publisher = "Association for Computing Machinery",
pages = "6741--6742",
booktitle = "KDD 2024 - Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining",
}