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DeepAID: Interpreting and Improving Deep Learning-based Anomaly
Detection in Security Applications

DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications

Conference on Computer and Communications Security (CCS), 2021

23 September 2021

Dongqi Han

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Papers citing "DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications"

16 / 16 papers shown

Title
A Hard-Label Black-Box Evasion Attack against ML-based Malicious Traffic Detection Systems Zixuan Liu Yi Zhao Zhuotao Liu Qi Li Chuanpu Fu Guangmeng Zhou Ke Xu AAML 74 0 0 16 Oct 2025
UniNet: A Unified Multi-granular Traffic Modeling Framework for Network SecurityIEEE Transactions on Cognitive Communications and Networking (TCCN), 2025 Binghui Wu D. Divakaran M. Gurusamy 203 2 0 06 Mar 2025
A Comparative Analysis of DNN-based White-Box Explainable AI Methods in Network SecurityEURASIP Journal on Information Security (EURASIP J. Inf. Secur.), 2025 Osvaldo Arreche Mustafa Abdallah AAML 393 6 0 14 Jan 2025
Visually Analyze SHAP Plots to Diagnose Misclassifications in ML-based Intrusion Detection Maraz Mia Mir Mehedi Ahsan Pritom Tariqul Islam Kamrul Hasan AAML 132 1 0 04 Nov 2024
XG-NID: Dual-Modality Network Intrusion Detection using a Heterogeneous Graph Neural Network and Large Language ModelExpert systems with applications (ESWA), 2024 Yasir Ali Farrukh S. Wali I. Khan Nathaniel D. Bastian 827 19 0 27 Aug 2024
Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection Jun Liu Chaoyun Zhang Jiaxu Qian Ming-Jie Ma Si Qin Chetan Bansal Qingwei Lin Saravan Rajmohan Dongmei Zhang AI4TS 144 29 0 24 May 2024
AnoGAN for Tabular Data: A Novel Approach to Anomaly Detection Aditya Singh Pavan Reddy 186 1 0 05 May 2024
AI for DevSecOps: A Landscape and Future Opportunities Michael Fu Jirat Pasuksmit Chakkrit Tantithamthavorn 158 18 0 07 Apr 2024
Genos: General In-Network Unsupervised Intrusion Detection by Rule Extraction Ruoyu Li Qing Li Yu Zhang Dan Zhao Xi Xiao Yong Jiang 134 8 0 28 Mar 2024
HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs) Tarek Ali Panos Kostakos 167 69 0 27 Sep 2023
FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security AnalysisConference on Computer and Communications Security (CCS), 2023 Yiling He Jian Lou Zhan Qin Kui Ren FAtt AAML 142 14 0 10 Aug 2023
Kairos: Practical Intrusion Detection and Investigation using Whole-system ProvenanceIEEE Symposium on Security and Privacy (IEEE S&P), 2023 Zijun Cheng Qiujian Lv Jinyuan Liang Yan Wang Degang Sun Thomas Pasquier Xueyuan Han 194 76 0 09 Aug 2023
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion DetectionEuropean Symposium on Security and Privacy (Euro S&P), 2023 Giovanni Apruzzese Pavel Laskov J. Schneider 204 39 0 30 Apr 2023
SoK: Modeling Explainability in Security Analytics for Interpretability, Trustworthiness, and UsabilityARES (ARES), 2022 Dipkamal Bhusal Rosalyn Shin Ajay Ashok Shewale M. K. Veerabhadran Michael Clifford Sara Rampazzi Nidhi Rastogi FAtt AAML 202 14 0 31 Oct 2022
SoK: Explainable Machine Learning for Computer Security ApplicationsEuropean Symposium on Security and Privacy (Euro S&P), 2022 A. Nadeem D. Vos Clinton Cao Luca Pajola Simon Dieck Robert Baumgartner S. Verwer 290 61 0 22 Aug 2022
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.9K 19,183 0 16 Feb 2016