![]() ![]() | SUN, T., ALLIX, K., KIM, K., Zhou, X., KIM, D., Lo, D., Bissyande, T. F., & KLEIN, J. (01 September 2023). DexBERT: Effective, Task-Agnostic and Fine-Grained Representation Learning of Android Bytecode. IEEE Transactions on Software Engineering, 49 (10), 4691 - 4706. doi:10.1109/TSE.2023.3310874 ![]() |
![]() ![]() | LOTHRITZ, C., LEBICHOT, B., ALLIX, K., EZZINI, S., BISSYANDE, T. F. D. A., KLEIN, J., Boytsov, A., Lefebvre, C., & Goujon, A. (2023). Evaluating the Impact of Text De-Identification on Downstream NLP Tasks. In Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa). Tartu, Estonia: University of Tartu Library. ![]() |
![]() ![]() | SOUANI, B., KHANFIR, A., BARTEL, A., ALLIX, K., & LE TRAON, Y. (2022). Android Malware Detection Using BERT. In Z. Jianying, Applied Cryptography and Network Security Workshops (pp. 575–591). Berlin, Germany: Springer. doi:10.1007/978-3-031-16815-4_31 ![]() |
![]() ![]() | ARSLAN, Y., LEBICHOT, B., ALLIX, K., VEIBER, L., Lefebvre, C., Boytsov, A., Goujon, A., BISSYANDE, T. F. D. A., & KLEIN, J. (2022). Towards Refined Classifications Driven by SHAP Explanations. In A. Holzinger, P. Kieseberg, A. M. Tjoa, ... E. Weippl (Eds.), Machine Learning and Knowledge Extraction (pp. 68-81). Springer. ![]() |
![]() ![]() | LOTHRITZ, C., LEBICHOT, B., ALLIX, K., VEIBER, L., BISSYANDE, T. F. D. A., KLEIN, J., Boytsov, A., Goujon, A., & Lefebvre, C. (2022). LuxemBERT: Simple and Practical Data Augmentation in Language Model Pre-Training for Luxembourgish. In Proceedings of the Language Resources and Evaluation Conference, 2022 (pp. 5080-5089). ![]() |
![]() ![]() | SAMHI, J., GAO, J., DAOUDI, N., Graux, P., Hoyez, H., Sun, X., ALLIX, K., BISSYANDE, T. F. D. A., & KLEIN, J. (2022). JuCify: A Step Towards Android Code Unification for Enhanced Static Analysis. In 44th International Conference on Software Engineering (ICSE 2022). doi:10.1145/3510003.3512766 ![]() |
![]() ![]() | DAOUDI, N., ALLIX, K., BISSYANDE, T. F. D. A., & KLEIN, J. (May 2022). A Deep Dive inside DREBIN: An Explorative Analysis beyond Android Malware Detection Scores. ACM Transactions on Privacy and Security, 25 (2). doi:10.1145/3503463 ![]() |
![]() ![]() | ARSLAN, Y., LEBICHOT, B., ALLIX, K., VEIBER, L., Lefebvre, C., BOYTSOV, A., Goujon, A., BISSYANDE, T. F. D. A., & KLEIN, J. (2022). On the Suitability of SHAP Explanations for Refining Classifications. In In Proceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART 2022). doi:10.5220/0010827700003116 ![]() |
![]() ![]() | ARSLAN, Y., ALLIX, K., Lefebvre, C., Boytsov, A., BISSYANDE, T. F. D. A., & KLEIN, J. (2022). Exploiting Prototypical Explanations for Undersampling Imbalanced Datasets. In 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 1449-1454). doi:10.1109/ICMLA55696.2022.00228 ![]() |
![]() ![]() | SUN, T., DAOUDI, N., ALLIX, K., & BISSYANDE, T. F. D. A. (2021). Android Malware Detection: Looking beyond Dalvik Bytecode. In 2021 36th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW). doi:10.1109/ASEW52652.2021.00019 ![]() |
![]() ![]() | LOTHRITZ, C., ALLIX, K., LEBICHOT, B., VEIBER, L., BISSYANDE, T. F. D. A., & KLEIN, J. (2021). Comparing MultiLingual and Multiple MonoLingual Models for Intent Classification and Slot Filling. In 26th International Conference on Applications of Natural Language to Information Systems (pp. 367-375). Springer. doi:10.1007/978-3-030-80599-9_32 ![]() |
![]() ![]() | ARSLAN, Y., ALLIX, K., VEIBER, L., LOTHRITZ, C., BISSYANDE, T. F. D. A., KLEIN, J., & Goujon, A. (2021). A Comparison of Pre-Trained Language Models for Multi-Class Text Classification in the Financial Domain. In Companion Proceedings of the Web Conference 2021 (WWW '21 Companion), April 19--23, 2021, Ljubljana, Slovenia (pp. 260–268). New York, United States: Association for Computing Machinery. doi:10.1145/3442442.3451375 ![]() |
![]() ![]() | RIOM, T., SAWADOGO, D. D. A., ALLIX, K., BISSYANDE, T. F. D. A., MOHA, N., & KLEIN, J. (29 March 2021). Revisiting the VCCFinder approach for the identification of vulnerability-contributing commits. Empirical Software Engineering, 26. doi:10.1007/s10664-021-09944-w ![]() |
![]() ![]() | SAMHI, J., ALLIX, K., BISSYANDE, T. F. D. A., & KLEIN, J. (2021). A First Look at Android Applications in Google Play related to Covid-19. Empirical Software Engineering. doi:10.1007/s10664-021-09943-x ![]() |
![]() ![]() | DAOUDI, N., SAMHI, J., KABORE, A. K., ALLIX, K., BISSYANDE, T. F. D. A., & KLEIN, J. (2021). DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection Based on Image Representation of Bytecode. In Communications in Computer and Information Science. Springer. doi:10.1007/978-3-030-87839-9_4 ![]() |
![]() ![]() | DAOUDI, N., ALLIX, K., BISSYANDE, T. F. D. A., & KLEIN, J. (2021). Lessons Learnt on Reproducibility in Machine Learning Based Android Malware Detection. Empirical Software Engineering, 26. doi:10.1007/s10664-021-09955-7 ![]() |
![]() ![]() | LOTHRITZ, C., ALLIX, K., VEIBER, L., KLEIN, J., & BISSYANDE, T. F. D. A. (2020). Evaluating Pretrained Transformer-based Models on the Task of Fine-Grained Named Entity Recognition. In Proceedings of the 28th International Conference on Computational Linguistics (pp. 3750–3760). ![]() |
![]() ![]() | VEIBER, L., ALLIX, K., ARSLAN, Y., BISSYANDE, T. F. D. A., & KLEIN, J. (2020). Challenges Towards Production-Ready Explainable Machine Learning. In L. VEIBER, K. ALLIX, Y. ARSLAN, T. F. D. A. BISSYANDE, ... J. KLEIN, Proceedings of the 2020 USENIX Conference on Operational Machine Learning (OpML 20). USENIX Association. ![]() |
![]() ![]() | ALLIX, K., BISSYANDE, T. F. D. A., KLEIN, J., & LE TRAON, Y. (2016). AndroZoo: Collecting Millions of Android Apps for the Research Community. In Proceedings of the 13th International Workshop on Mining Software Repositories (pp. 468--471). New York, NY, USA, Unknown/unspecified: ACM. doi:10.1145/2901739.2903508 ![]() |
![]() ![]() | HURIER, M., ALLIX, K., BISSYANDE, T. F. D. A., KLEIN, J., & LE TRAON, Y. (2016). On the Lack of Consensus in Anti-Virus Decisions: Metrics and Insights on Building Ground Truths of Android Malware. In Detection of Intrusions and Malware, and Vulnerability Assessment - 13th International Conference (pp. 142--162). Springer. doi:10.1007/978-3-319-40667-1_8 ![]() |
![]() ![]() | ALLIX, K. (2015). Challenges and Outlook in Machine Learning-based Malware Detection for Android [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/24900 |
![]() ![]() | LI, L., ALLIX, K., LI, D., BARTEL, A., BISSYANDE, T. F. D. A., & KLEIN, J. (2015). Potential Component Leaks in Android Apps: An Investigation into a new Feature Set for Malware Detection. In The 2015 IEEE International Conference on Software Quality, Reliability and Security (QRS 2015). doi:10.1109/QRS.2015.36 ![]() |
![]() ![]() | LI, L., ALLIX, K., LI, D., BARTEL, A., BISSYANDE, T. F. D. A., & KLEIN, J. (2015). A Study of Potential Component Leaks in Android Apps. SnT Centre - University of Luxembourg. |
![]() ![]() | ALLIX, K., BISSYANDE, T. F. D. A., KLEIN, J., & LE TRAON, Y. (2015). Are Your Training Datasets Yet Relevant? - An Investigation into the Importance of Timeline in Machine Learning-Based Malware Detection. In Engineering Secure Software and Systems - 7th International Symposium ESSoS 2015, Milan, Italy, March 4-6, 2015. Proceedings (pp. 51-67). Springer International Publishing. doi:10.1007/978-3-319-15618-7_5 ![]() |
![]() ![]() | ALLIX, K., BISSYANDE, T. F. D. A., JEROME, Q., KLEIN, J., STATE, R., & LE TRAON, Y. (2014). Empirical assessment of machine learning-based malware detectors for Android: Measuring the Gap between In-the-Lab and In-the-Wild Validation Scenarios. Empirical Software Engineering, 1-29. doi:10.1007/s10664-014-9352-6 ![]() |
![]() ![]() | ALLIX, K., JEROME, Q., BISSYANDE, T. F. D. A., KLEIN, J., STATE, R., & LE TRAON, Y. (2014). A Forensic Analysis of Android Malware -- How is Malware Written and How It Could Be Detected? In Proceedings of the 2014 IEEE 38th Annual Computer Software and Applications Conference (pp. 384--393). Washington, DC, USA, Unknown/unspecified: IEEE Computer Society. doi:10.1109/COMPSAC.2014.61 ![]() |
![]() ![]() | JEROME, Q., ALLIX, K., STATE, R., & ENGEL, T. (2014). Using opcode-sequences to detect malicious Android applications. In IEEE International Conference on Communications, ICC 2014, Sydney Australia, June 10-14, 2014. Sydney, Australia: IEEE. doi:10.1109/ICC.2014.6883436 ![]() |
![]() ![]() | ALLIX, K., BISSYANDE, T. F. D. A., KLEIN, J., & LE TRAON, Y. (2014). Machine Learning-Based Malware Detection for Android Applications: History Matters! Luxembourg, Luxembourg: University of Luxembourg, SnT. |
![]() ![]() | ALLIX, K., BISSYANDE, T. F. D. A., JEROME, Q., KLEIN, J., STATE, R., & LE TRAON, Y. (2014). Large-scale Machine Learning-based Malware Detection: Confronting the "10-fold Cross Validation" Scheme with Reality. In Proceedings of the 4th ACM Conference on Data and Application Security and Privacy (pp. 163--166). New York, NY, USA, Unknown/unspecified: ACM. doi:10.1145/2557547.2557587 ![]() |
![]() ![]() | BARTEL, A., KLEIN, J., Monperrus, M., ALLIX, K., & LE TRAON, Y. (2012). In-Vivo Bytecode Instrumentation for Improving Privacy on Android Smartphones in Uncertain Environments. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/25161. |
![]() ![]() | BARTEL, A., KLEIN, J., Monperrus, M., ALLIX, K., & LE TRAON, Y. (2012). Improving Privacy on Android Smartphones Through In-Vivo Bytecode Instrumentation. Luxembourg, Unknown/unspecified: uni.lu. |