Papers by Guanhong Tao

3 papers
Threat Behavior Textual Search by Attention Graph Isomorphism (2024.eacl-long)

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Challenge: Existing methods to analyze malware behavior only disclose a subset of behaviors due to inherent difficulties.
Approach: They propose a novel malware behavior search technique that is based on graph isomorphism at the attention layers of Transformer models.
Outcome: The proposed technique outperforms state-of-the-art methods in a case study of 10 real-world malwares by 6-14%.
Backdooring Neural Code Search (2023.acl-long)

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Challenge: Neural code search models are used to find code snippets from online repositories . however, their security aspect is rarely studied .
Approach: They propose to use off-the-shelf code snippets from online repositories to find desired code . they propose to inject a backdoor into neural code search models which return buggy code if attacker modifies one variable/function name .
Outcome: The proposed attack outperforms baselines on two neural code search models by 60%.
Profiler: Black-box AI-generated Text Origin Detection via Context-aware Inference Pattern Analysis (2025.emnlp-main)

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Challenge: Existing methods to identify the origin of AI-generated texts fail to identify origin due to the high similarity of different LLMs.
Approach: They propose a black-box AI-generated text origin detection method which accurately predicts the origin of an input text by extracting distinct context inference patterns.
Outcome: The proposed method outperforms 10 state-of-the-art baselines and achieves a 25% increase in AUC score on average across natural language and code datasets.

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