Large-scale security analytics

In 2018, 53,000 successful cyber-attacks have been reported - with each attack costing around $3.86 million on average.

In order to detect and prevent these cyber-attacks, we need to collect and analyse a large volume of security event data. 

Therefore, the security analytics systems should be able to scale up for analysing the increasing amount of security event data. In this project, we investigated the scalability (i.e., how easily the system can grow to deal with increasing amount of data) of a security analytics system and proposed an optimal solution that enables a security analytics system to scale efficiently. 

Our project highlights the importance of scalability and helps a security operator by automatically enabling the system to deal with increasing volume of security event data.

Securing our future


Computer Science

Anying Xiang
Rudong Su
Sicheng Xin
Xueying Guo

vote for this project: sf08

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