@inproceedings{82b320fee0c34d79bc468b8273a7c636,
title = "NetflowTotal: A cloud service integration platform for malicious traffic analysis and collaboration",
abstract = "Network security lacks the verification of real world net flow data, and lacks a platform to collect and integrate net flow data and threat intelligence, so as to generate an evaluation benchmark for machine learning on cybersecurity. NetFlowTotal develop many net flow analysis tools to detect malicious threats in the net flow data. Through the two-side market strategies, NetFlowTotal platform tie together two distinct groups of users in a network. One kind of user can upload net flow data to the NetFlowTotal platform to obtain security incidents reports; the other kind of user can share threat intelligence to the NetFlowTotal platform to obtain more associate threat intelligence according to global net flow data. The goal of this paper is to establish a net flow evaluation platform to provide real world dataset with security incidents reports for machine learning evaluation.",
keywords = "Cyber Threat Intelligence, MapReduce, Microservice, Serverless",
author = "Jeng, {Tzung Han} and Chan, {Wei Ming} and Luo, {Wen Yang} and Huang, {Chuan Chiang} and Chen, {Chien Chih} and Chen, {Yi Ming}",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 2nd International Conference on Computing and Big Data, ICCBD 2019 and its Workshop the International Conference on Computer, Software Engineering and Applications, CSEA 2019 ; Conference date: 18-10-2019 Through 20-10-2019",
year = "2019",
month = oct,
day = "18",
doi = "10.1145/3366650.3366669",
language = "???core.languages.en_GB???",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "154--160",
booktitle = "ICCBD 2019 - 2019 the 2nd International Conference on Computing and Big Data, Workshop CSEA 2019",
}