Collaborative Detection of Cyber Security
Threats in Big Data
Jiange Zhang, Yuanbo Guo, and Yue
Chen
State Key Laboratory of
Mathematical Engineering and Advanced Computing, Zhengzhou Information Science
and Technology Institute, China
Abstract: In the era of big data, it is a problem to be solved
for promoting the healthy development of the Internet and the Internet+,
protecting the information security of individuals, institutions and countries.
Hence, this paper constructs a collaborative detection system of cyber security
threats in big data. Firstly, it describes the log collection model of Flume,
the data cache of Kafka, and the data process of Esper; then it designs
one-to-many log collection, consistent data cache, Complex Event Processing
(CEP) data process using event query and event pattern matching; finally, it
tests on the datasets and analyzes the results from six aspects. The results
demonstrate that the system has good reliability, high efficiency and accurate
detection results; moreover, the system has the advantages of low cost and
flexible operation.
Keywords: Big data, cyber security, threat, collaborative
detection.