Paper accepted at ACM TOPS Journal

We are thrilled to announce that our paper “On generating network traffic datasets with synthetic attacks for intrusion detection” is accepted at ACM Transactions on Privacy and Security (TOPS) journal.

In this paper, TK researchers present the Intrusion Detection Dataset Toolkit (ID2T) to alleviate the problem of reproducing datasets with desired characteristics to enable an accurate replication of scientific results. ID2T facilitates the creation of labeled datasets by injecting synthetic attacks into background traffic.

Citation info:

• Carlos Garcia Cordero, Emmanouil Vasilomanolakis, Aidmar Wainakh, Max Mühlhäuser, and Simin Nadjm-Tehrani. 2020. On generating network traffic datasets with synthetic attacks for intrusion detection. ACM Trans. Priv. Sec. [To appear].