6 citations · 25 across the 20 of their papers we have counts for
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cs.CL2023★ 6 cited
SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security
Zefang Liu
In this paper, we introduce SecQA, a novel dataset tailored for evaluating the performance of Large Language Models (LLMs) in the domain of computer security. Utilizing multiple-ch…
cs.CL2023★ 1 cited
Anomaly Detection of Command Shell Sessions based on DistilBERT: Unsupervised and Supervised Approaches
Zefang Liu, John Buford
Anomaly detection in command shell sessions is a critical aspect of computer security. Recent advances in deep learning and natural language processing, particularly transformer-ba…