Analyzing the usefulness of the DARPA transparent computing E5 dataset in APT detection research

Guige Ouyang; Yongzhong Huang; Chenhao Zhang

doi:10.1117/12.2641011

2 December 2022 Analyzing the usefulness of the DARPA transparent computing E5 dataset in APT detection research

Guige Ouyang, Yongzhong Huang, Chenhao Zhang

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 122881N (2022) https://doi.org/10.1117/12.2641011
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

We witnessed a lot of examples of cases launched by Advanced Persistent Threat (APT) organization and the spectacular destructive power. The realistic data originate from occurred attack events almost is not available. Fortunately, there is some simulation dataset. Many previous works were chosen to evaluate their method on the Defense Advanced Research Projects Agency (DARPA) Transparent Computing Engagement 3 dataset that contains attack behaviors implemented by a highly skilled team. Meanwhile, with the rapid update development of computer technology and the competition between detection means and attacking methods is becoming increasingly fierce, this dataset is outmoded, it exists the enormous gap between current cyber attacks and the DARPA TC E3 dataset. In this work, we provide the statistical information of DARPA TC E5 and compare it with DARPA TC E3. We analyze the practicality of the more advanced DARPA Transparent Computing Engagement 5 dataset.

Citation Download Citation

Guige Ouyang, Yongzhong Huang, and Chenhao Zhang "Analyzing the usefulness of the DARPA transparent computing E5 dataset in APT detection research", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 122881N (2 December 2022); https://doi.org/10.1117/12.2641011

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