Using a Collated Cybersecurity Dataset for Machine Learning and Artificial Intelligence

Autor:	Hemberg, Erik, O'Reilly, Una-May
Rok vydání:	2021
Předmět:	Computer Science - Cryptography and Security Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	Artificial Intelligence (AI) and Machine Learning (ML) algorithms can support the span of indicator-level, e.g. anomaly detection, to behavioral level cyber security modeling and inference. This contribution is based on a dataset named BRON which is amalgamated from public threat and vulnerability behavioral sources. We demonstrate how BRON can support prediction of related threat techniques and attack patterns. We also discuss other AI and ML uses of BRON to exploit its behavioral knowledge. Comment: 5 pages, 2 Figures, 2 Tables, ACM KDD AI4Cyber: The 1st Workshop on Artificial Intelligence- enabled Cybersecurity Analytics at KDD'21
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2108.02618 Zobrazit plný text záznamu View this record from Arxiv