Leon Kersten (Eindhoven University of Technology), Kim Beelen (Eindhoven University of Technology), Emmanuele Zambon (Eindhoven University of Technology), Chris Snijders (Eindhoven University of Technology), Luca Allodi (Eindhoven University of Technology)

The alert investigation processes junior (Tier-1) analysts follow are critical to attack detection and communication in Security Operation Centers (SOCs). Yet little is known on how analysts conduct alert investigations, which information they consider, and when. In this work, we collaborate with a commercial SOC and employ two think-aloud experiments. The first is to evaluate the alert investigation process followed by professional T1 analysts, and identify criticalities within. For the second experiment, we develop an alert investigation support system (AISS), integrate it into the SOC environment, and evaluate its effect on alert investigations with another cohort of T1 analysts. The experiments observe five and four analysts, respectively, conducting 400 and 36 investigations, respectively. Our results show that the analysts’ natural analysis process differs between analysts and types of alerts and that the AISS aids the analyst in gathering more relevant information while performing fewer actions for critical security alerts.

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Tu Le (University of California, Irvine), Zixin Wang (Zhejiang University), Danny Yuxing Huang (New York University), Yaxing Yao (Virginia Tech), Yuan Tian (University of California, Los Angeles)

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Hanlei Zhang (Zhejiang University), Yijie Bai (Zhejiang University), Yanjiao Chen (Zhejiang University), Zhongming Ma (Zhejiang University), Wenyuan Xu (Zhejiang University)

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Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

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Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)