Kevin Allix
Orcid: 0000-0003-3221-7266
According to our database1,
Kevin Allix
authored at least 36 papers
between 2012 and 2023.
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Bibliography
2023
DexBERT: Effective, Task-Agnostic and Fine-Grained Representation Learning of Android Bytecode.
IEEE Trans. Software Eng., October, 2023
Empir. Softw. Eng., 2023
LaFiCMIL: Rethinking Large File Classification from the Perspective of Correlated Multiple Instance Learning.
CoRR, 2023
Proceedings of the 24th Nordic Conference on Computational Linguistics, 2023
Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2023
2022
A Deep Dive Inside DREBIN: An Explorative Analysis beyond Android Malware Detection Scores.
ACM Trans. Priv. Secur., 2022
CoRR, 2022
The Devil is in the Details: Unwrapping the Cryptojacking Malware Ecosystem on Android.
Proceedings of the 22nd IEEE International Working Conference on Source Code Analysis and Manipulation, 2022
LuxemBERT: Simple and Practical Data Augmentation in Language Model Pre-Training for Luxembourgish.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022
Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022
Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022
Proceedings of the Machine Learning and Knowledge Extraction, 2022
Proceedings of the Applied Cryptography and Network Security Workshops, 2022
2021
Empir. Softw. Eng., 2021
Revisiting the VCCFinder approach for the identification of vulnerability-contributing commits.
Empir. Softw. Eng., 2021
Lessons Learnt on Reproducibility in Machine Learning Based Android Malware Detection.
Empir. Softw. Eng., 2021
DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection based on Image Representation of Bytecode.
CoRR, 2021
A Comparison of Pre-Trained Language Models for Multi-Class Text Classification in the Financial Domain.
Proceedings of the Companion of The Web Conference 2021, 2021
Comparing MultiLingual and Multiple MonoLingual Models for Intent Classification and Slot Filling.
Proceedings of the Natural Language Processing and Information Systems, 2021
Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021
2020
Proceedings of the 2020 USENIX Conference on Operational Machine Learning, 2020
Evaluating Pretrained Transformer-based Models on the Task of Fine-Grained Named Entity Recognition.
Proceedings of the 28th International Conference on Computational Linguistics, 2020
2016
Empirical assessment of machine learning-based malware detectors for Android - Measuring the gap between in-the-lab and in-the-wild validation scenarios.
Empir. Softw. Eng., 2016
Proceedings of the 13th International Conference on Mining Software Repositories, 2016
On the Lack of Consensus in Anti-Virus Decisions: Metrics and Insights on Building Ground Truths of Android Malware.
Proceedings of the Detection of Intrusions and Malware, and Vulnerability Assessment, 2016
2015
PhD thesis, 2015
Potential Component Leaks in Android Apps: An Investigation into a New Feature Set for Malware Detection.
Proceedings of the 2015 IEEE International Conference on Software Quality, 2015
Are Your Training Datasets Yet Relevant? - An Investigation into the Importance of Timeline in Machine Learning-Based Malware Detection.
Proceedings of the Engineering Secure Software and Systems - 7th International Symposium, 2015
2014
Proceedings of the IEEE International Conference on Communications, 2014
A Forensic Analysis of Android Malware - How is Malware Written and How it Could Be Detected?
Proceedings of the IEEE 38th Annual Computer Software and Applications Conference, 2014
Large-scale machine learning-based malware detection: confronting the "10-fold cross validation" scheme with reality.
Proceedings of the Fourth ACM Conference on Data and Application Security and Privacy, 2014
2012
CoRR, 2012