Dealing with Security Alert Flooding: Using Machine Learning for Domain-independent Alert Aggregation

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	1-36
Number of pages	36
Journal	ACM Transactions on Privacy and Security
Volume	25
Issue number	18
DOIs	https://doi.org/10.1145/3510581
Publication status	Published - 2022

Research Field

@article{62c05ba780de4fa08eeeb5f4c873faad,

title = "Dealing with Security Alert Flooding: Using Machine Learning for Domain-independent Alert Aggregation",

author = "Max Landauer and Florian Skopik and Markus Wurzenberger and Andreas Rauber",

year = "2022",

doi = "10.1145/3510581",

language = "English",

volume = "25",

pages = "1--36",

journal = "ACM Transactions on Privacy and Security",

issn = "2471-2566",

publisher = "Association for Computing Machinery (ACM)",

number = "18",

}

TY - JOUR

T1 - Dealing with Security Alert Flooding: Using Machine Learning for Domain-independent Alert Aggregation

AU - Landauer, Max

AU - Skopik, Florian

AU - Wurzenberger, Markus

AU - Rauber, Andreas

PY - 2022

Y1 - 2022

U2 - 10.1145/3510581

DO - 10.1145/3510581

M3 - Article

SN - 2471-2566

VL - 25

SP - 1

EP - 36

JO - ACM Transactions on Privacy and Security

JF - ACM Transactions on Privacy and Security

IS - 18

ER -