Mingrui Ma

Mingrui Ma

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publications

CVDF DYNAMIC—A Dynamic Fuzzy Testing Sample Generation Framework Based on BI-LSTM and Genetic Algorithm

Published in Sensors, 2022

TLDR: This paper proposes CVDF DYNAMIC, a fuzzy testing sample generation framework which utilizes genetic algorithm and BI-LSTM neural network. Experimental results demonstrate that CVDF DYNAMIC can generate dynamic samples with high quality and strong path depth detection ability.

Recommended citation: Ma M, Han L, Qian Y. CVDF DYNAMIC—A Dynamic Fuzzy Testing Sample Generation Framework Based on BI-LSTM and Genetic Algorithm[J]. Sensors, 2022, 22(3): 1265. http://jkpathfinder.github.io/files/paper1.pdf

Detection method for c language family based on graph neural network and generic vulnerability analysis framework

Published in Netinfo Security, 2022

TLDR: This paper proposes CSVDM for static vulnerability detection tasks of C family languages. By combining Graph Neural Network with Generic Vulnerability Analysis Framework, CSVDM can perform high-precision multi-class classification tasks.

Recommended citation: ZHU Lina, MA Mingrui, ZHU Dongzhao. Detection Method for C Language Family Based on Graph Neural Network and Generic Vulnerability Analysis Framework[J]. Netinfo Security, 2022, 22(10): 59-68. http://jkpathfinder.github.io/files/paper2.pdf

BTAD: A binary transformer deep neural network model for anomaly detection in multivariate time series data

Published in Advanced Engineering Informatics, 2023

TLDR: This article introduces the Bi-Transformer anomaly detection method for anomaly detection in multivariate time series data, and proposes corresponding enhancements such as an adaptive multi-head attention mechanism and a modified Decoder structure to further improve the performance of BTAD. Experimental results on multiple mainstream multivariate time series datasets demonstrate that BTAD exhibits outstanding overall anomaly detection performance.

Recommended citation: Ma M, Han L, Zhou C. BTAD: A binary transformer deep neural network model for anomaly detection in multivariate time series data[J]. Advanced Engineering Informatics, 2023, 56: 101949. http://jkpathfinder.github.io/files/paper3.pdf

Large language models are few-shot generators: Proposing hybrid prompt algorithm to generate webshell escape samples

Published in Arxiv Preprint, 2024

TLDR: This article introduces the Hybird Prompt algorithm, which combines the advantages of various prompt algorithms such as CoT, ToT, and SC. It generates webshell samples with high Escape Rate and Survival Rate through various components and hierarchical reasoning steps.

Recommended citation: Ma M, Han L, Zhou C. Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples[J]. arXiv preprint arXiv:2402.07408, 2024. https://arxiv.org/abs/2402.07408

Research and application of Transformer based anomaly detection model: A literature review

Published in Arxiv Preprint, 2024

TLDR: This article offers a detailed summary, synthesis, and analysis of transformer-based research and applications in the field of anomaly detection. To the best of our knowledge, this is also the first comprehensive review that focuses on the research related to Transformer in the context of anomaly detection.

Recommended citation: Ma M, Han L, Zhou C. Research and application of Transformer based anomaly detection model: A literature review[J]. arXiv preprint arXiv:2402.08975, 2024. https://arxiv.org/abs/2402.08975

Research and application of artificial intelligence based webshell detection model: A literature review

Published in Arxiv Preprint, 2024

TLDR: This article provides a detailed summary and synthesis of webshell detection solutions based on artificial intelligence technology, analyzes the shortcomings of existing solutions, and predicts the future development trends in the related field.

Recommended citation: Ma M, Han L, Zhou C. Research and application of artificial intelligence based webshell detection model: A literature review[J]. arXiv preprint arXiv:2405.00066, 2024. https://arxiv.org/abs/2405.00066

research

The National Key Research and Development Program of China

Key Project Member, Huazhong University of Science and Technology, 2022

As a core member of the project, responsible for neural network algorithm development, language model performance optimization, etc. As of now, multiple core algorithms have been successfully developed, including the Collaborative Analysis Log Search Algorithm, Automated Evidence Generation Algorithm, etc.

RUSTSBI Open-Source Community

Major Contributor, Core Member, Huazhong University of Science and Technology, 2023

Contirbuted to 2 Pull-Requests as a major contributor, both of which have been reviewed and merged. One is the modular driver for the GPIO peripheral, and the other is the parsing script for the unreleased D1 chipset.

The Fundamental Research Funds for the Central Universities, Grant: YCJJ20230464

Project Leader, Huazhong University of Science and Technology, 2023

Hosted the scientific research project “IntelliSense - Cross-Domain Implicit Space-Oriented Malicious Code Adversarial Detection and Source Tracking System”, passed the mid-term evaluation with full marks (Grade A), and has reached the standard of outstanding project completion.

reviewing

Official Reviewer for “Applied Intelligence”

Official Reviewer, Springer Nature, 2023

Official Reviewer for the SCI Journal “Applied Intelligence” (JCR Q2, IF 3.4). Main review directions include but are not limited to, deep learning, neural networks, curriculum learning, and contrastive learning.

Official Reviewer for “IEEE Transactions on Intelligent Transportation Systems (TITS)”

Official Reviewer, Institute of Electrical and Electronics Engineers, 2023

Official Reviewer for the TOP SCI Journal “IEEE Transactions on Intelligent Transportation Systems” (JCR Q1, IF 7.9). Main review directions include but are not limited to, neural network architecture and multivariate time series analysis. Relevant review works have been indexed by international databases (e.g. Web of Science, ORCID, etc.).

Official Reviewer for “Neurocomputing”

Official Reviewer, Elsevier, 2024

Official Reviewer for the SCI Journal “Neurocomputing” (JCR Q2, IF 5.5). Main review directions include but are not limited to, meta-learning, and data augmentation.

talks

teaching

Teaching Assistant for the Graduate Course “Computer Virus Propagation Models”

Teaching Assistant, Huazhong University of Science and Technology, School of Cyber Science and Engineering, 2022

Serving as a teaching assistant for the graduate theoretical course “Computer Viruses Propagation Models”, responsible for tasks including grading assignments, answering questions related to course content, evaluating course projects, etc.