Aakanksha Saha On Leave
BSc MSc
Role
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PreDoc Researcher
Security and Privacy, E192-06
Publications
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ADAPT it! Automating APT Campaign and Group Attribution by Leveraging and Linking Heterogeneous Files
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Saha, A., Blasco, J., Cavallaro, L., & Lindorfer, M. (2024). ADAPT it! Automating APT Campaign and Group Attribution by Leveraging and Linking Heterogeneous Files. In RAID ’24: Proceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses (pp. 114–129). Association for Computing Machinery. https://doi.org/10.1145/3678890.3678909
Download: PDF (966 KB)
Project: IoTIO (2020–2025) - Exploring the Malicious Document Threat Landscape: Towards a Systematic Approach to Detection and Analysis / Saha, A., Blasco Alís, J., & Lindorfer, M. (2024). Exploring the Malicious Document Threat Landscape: Towards a Systematic Approach to Detection and Analysis. In 2024 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) (pp. 533–544). https://doi.org/10.1109/EuroSPW61312.2024.00065
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Connecting the .dotfiles: Checked-In Secret Exposure with Extra (Lateral Movement) Steps
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Jungwirth, G., Saha, A., Schröder, M., Fiebig, T., Lindorfer, M., & Cito, J. (2023). Connecting the .dotfiles: Checked-In Secret Exposure with Extra (Lateral Movement) Steps. In IEEE/ACM 20th International Conference on Mining Software Repositories (MSR) (pp. 322–333). https://doi.org/10.1109/MSR59073.2023.00051
Project: IoTIO (2020–2025) - Secrets in Source Code: Reducing False Positives using Machine Learning / Saha, A., Denning, T., Srikumar, V., & Kasera, S. K. (2020). Secrets in Source Code: Reducing False Positives using Machine Learning. In 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS). IEEE Xplore Digital Library. https://doi.org/10.1109/comsnets48256.2020.9027350