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ALLIX Kevin

Main Referenced Co-authors
KLEIN, Jacques  (27)
BISSYANDE, Tegawendé  (25)
LE TRAON, Yves  (10)
VEIBER, Lisa  (7)
ARSLAN, Yusuf  (5)
Main Referenced Keywords
Android (7); Android Security (4); machine learning (3); Deep Learning (2); Machine Learning (2);
Main Referenced Unit & Research Centers
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Trustworthy Software Engineering (TruX) (3)
ULHPC - University of Luxembourg: High Performance Computing (3)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Other (1)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Security Design and Validation Research Group (SerVal) (1)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > TruX - Trustworthy Software Engineering (1)
Main Referenced Disciplines
Computer science (31)

Publications (total 31)

The most downloaded
3821 downloads
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 https://hdl.handle.net/10993/27396

The most cited

637 citations (Scopus®)

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 https://hdl.handle.net/10993/27396

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
Peer Reviewed verified by ORBi

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.
Peer reviewed

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
Peer reviewed

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.
Peer reviewed

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).
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer Reviewed verified by ORBi

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
Peer Reviewed verified by ORBi

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
Peer reviewed

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
Peer Reviewed verified by ORBi

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).
Peer reviewed

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.
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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
Peer reviewed

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.

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