Alejandro Guerra-Manzanares
Orcid: 0000-0002-3655-5804
According to our database1,
Alejandro Guerra-Manzanares
authored at least 21 papers
between 2019 and 2024.
Collaborative distances:
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Bibliography
2024
Experts still needed: boosting long-term android malware detection with active learning.
J. Comput. Virol. Hacking Tech., November, 2024
IEEE J. Biomed. Health Informatics, November, 2024
Machine Learning for Android Malware Detection: Mission Accomplished? A Comprehensive Review of Open Challenges and Future Perspectives.
Comput. Secur., March, 2024
J. Inf. Secur. Appl., 2024
Future Gener. Comput. Syst., 2024
CoRR, 2024
2023
On the application of active learning for efficient and effective IoT botnet detection.
Future Gener. Comput. Syst., April, 2023
Leveraging the first line of defense: a study on the evolution and usage of android security permissions for enhanced android malware detection.
J. Comput. Virol. Hacking Tech., March, 2023
Corrigendum to Concept drift and cross-device behavior: Challenges and implications for effective android malware detection Computers & Security, Volume 120, 102757.
Comput. Secur., 2023
Privacy-Preserving Machine Learning for Healthcare: Open Challenges and Future Perspectives.
Proceedings of the Trustworthy Machine Learning for Healthcare, 2023
2022
Android malware concept drift using system calls: Detection, characterization and challenges.
Expert Syst. Appl., 2022
On the relativity of time: Implications and challenges of data drift on long-term effective android malware detection.
Comput. Secur., 2022
Concept drift and cross-device behavior: Challenges and implications for effective android malware detection.
Comput. Secur., 2022
On the Application of Active Learning to Handle Data Evolution in Android Malware Detection.
Proceedings of the Digital Forensics and Cyber Crime - 13th EAI International Conference, 2022
2021
KronoDroid: Time-based Hybrid-featured Dataset for Effective Android Malware Detection and Characterization.
Comput. Secur., 2021
2020
Using MedBIoT Dataset to Build Effective Machine Learning-Based IoT Botnet Detection Systems.
Proceedings of the Information Systems Security and Privacy - 6th International Conference, 2020
Proceedings of the 6th International Conference on Information Systems Security and Privacy, 2020
2019
Differences in Android Behavior Between Real Device and Emulator: A Malware Detection Perspective.
Proceedings of the Sixth International Conference on Internet of Things: Systems, 2019
Towards the Integration of a Post-Hoc Interpretation Step into the Machine Learning Workflow for IoT Botnet Detection.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019
Proceedings of the 5th International Conference on Information Systems Security and Privacy, 2019
Hybrid Feature Selection Models for Machine Learning Based Botnet Detection in IoT Networks.
Proceedings of the 2019 International Conference on Cyberworlds, 2019