Martina Lindorfer
Associate Prof. Dipl.-Ing.in Dr.in techn. / BSc
Roles
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Associate Professor
Security and Privacy, E192-06 -
Women in Informatics
Coordinator
Courses
2023W
- Bachelor Thesis / 192.061 / PR
- Project in Computer Science 1 / 192.021 / PR
- Project in Computer Science 2 / 192.022 / PR
- Seminar for Master Students in Software Engineering & Internet Computing / 180.777 / SE
- Seminar for PhD Students / 192.060 / SE
Projects
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Fixing the Broken Bridge Between Mobile Apps and the Web
2023 – 2027 / Vienna Science and Technology Fund (WWTF) -
IoTIO: Analyzing and Understanding the Internet of Insecure Things
2020 – 2025 / Vienna Science and Technology Fund (WWTF)
Publications: 150264 / 175968 / 176906 / 78069 / 58517 / 80253 -
A European Network of Excellence in Managing Threats and
Vulnerabilities in the Future Internet: Europe for the World
2010 – 2014 / European Commission
Publications: 54010 / 54011 / 54022 / 57547 / 57548 / 57549 / 57550 -
i-Code: Real-time Malicious Code Identification
2010 – 2012 / European Commission
Publication: 54010 -
TRUDIE - Trust Relationships in Underground IT Economies
2009 – 2012 / Austrian Research Promotion Agency (FFG)
Publications: 53359 / 54010 / 54011
Publications
2022
- Position Paper: Escaping Academic Cloudification to Preserve Academic Freedom / Fiebig, T., Gürses, S., & Lindorfer, M. (2022). Position Paper: Escaping Academic Cloudification to Preserve Academic Freedom. Privacy Studies Journal, 51–68. https://doi.org/10.7146/psj.vi.132713
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A Comparative Analysis of Certificate Pinning in Android & iOS
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Pradeep, A., Paracha, M. T., Bhowmick, P., Davanian, A., Razaghpanah, A., Chung, T., Lindorfer, M., Vallina-Rodriguez, N., Levin, D., & Choffnes, D. (2022). A Comparative Analysis of Certificate Pinning in Android & iOS. In Proceedings of the 22nd ACM Internet Measurement Conference (pp. 605–618). ACM. https://doi.org/10.34726/3505
Download: PDF (1.54 MB)
Project: IoTIO (2020–2025) -
Comparing User Perceptions of Anti-Stalkerware Apps with the Technical Reality
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Fassl, M., Anell, S., Houy, S., Lindorfer, M., & Krombholz, K. (2022). Comparing User Perceptions of Anti-Stalkerware Apps with the Technical Reality. In Proceedings of the Eighteenth Symposium on Usable Privacy and Security (SOUPS 2022) (pp. 135–154). USENIX Association. https://doi.org/10.34726/3902
Download: Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee. (1.35 MB)
Project: IoTIO (2020–2025) -
Not that Simple: Email Delivery in the 21st Century
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Holzbauer, F., Ullrich, J., Lindorfer, M., & Fiebig, T. (2022). Not that Simple: Email Delivery in the 21st Century. In Proceedings of the 2022 USENIX Annual Technical Conference (pp. 295–308). USENIX Association. https://doi.org/10.34726/4024
Download: PDF (1.43 MB)
Project: IoTIO (2020–2025) -
No Spring Chicken: Quantifying the Lifespan of Exploits in IoT Malware Using Static and Dynamic Analysis
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Al Alsadi, A. A., Sameshima, K., Bleier, J., Yoshioka, K., Lindorfer, M., van Eeten, M., & Hernández Gañán, C. (2022). No Spring Chicken: Quantifying the Lifespan of Exploits in IoT Malware Using Static and Dynamic Analysis. In Yuji Suga, Kouichi Sakurai, Xuhua Ding, & Kazue Sako (Eds.), ASIA CCS ’22: Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security (pp. 309–321). Association for Computing Machinery. https://doi.org/10.1145/3488932.3517408
Project: IoTIO (2020–2025) -
ART-assisted App Diffing: Defeating Dalvik Bytecode Shrinking, Obfuscation, and Optimization with Android's OAT Compiler
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Bleier, J., & Lindorfer, M. (2022, May 23). ART-assisted App Diffing: Defeating Dalvik Bytecode Shrinking, Obfuscation, and Optimization with Android’s OAT Compiler [Poster Presentation]. 43rd IEEE Symposium on Security and Privacy, San Francisco, United States of America (the).
Project: IoTIO (2020–2025)
2021
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Tarnhelm: Isolated, Transparent & Confidential Execution of Arbitrary Code in ARM's TrustZone
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Quarta, D., Ianni, M., Machiry, A., Fratantonio, Y., Gustafson, E., Balzarotti, D., Lindorfer, M., Vigna, G., & Kruegel, C. (2021). Tarnhelm: Isolated, Transparent & Confidential Execution of Arbitrary Code in ARM’s TrustZone. In Proceedings of the 2021 Research on offensive and defensive techniques in the Context of Man At The End (MATE) Attacks. ACM, Austria. ACM. https://doi.org/10.1145/3465413.3488571
Project: IoTIO (2020–2025)
2020
- When Malware is Packin' Heat; Limits of Machine Learning Classifiers Based on Static Analysis Features / Aghakhani, H., Gritti, F., Mecca, F., Lindorfer, M., Ortolani, S., Balzarotti, D., Vigna, G., & Krügel, C. (2020). When Malware is Packin’ Heat; Limits of Machine Learning Classifiers Based on Static Analysis Features. In Network and Distributed System Security Symposium (NDSS). Internet Society. http://hdl.handle.net/20.500.12708/58307
- TXTing 101: Finding Security Issues in the Long Tail of DNS TXT Records / der Toorn, O. van, van Rijswijk-Deij, R., Fiebig, T., Lindorfer, M., & Sperotto, A. (2020). TXTing 101: Finding Security Issues in the Long Tail of DNS TXT Records. In 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). IEEE. https://doi.org/10.1109/eurospw51379.2020.00080
- FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic / van Ede, T., Bortolameotti, R., Continella, A., Ren, J., Dubois, D., Lindorfer, M., Choffnes, D., van Steen, M., & Peter, A. (2020). FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic. In Network and Distributed System Security Symposium (NDSS). Internet Society. http://hdl.handle.net/20.500.12708/58308
2018
- GuardION: Practical Mitigation of DMA-Based Rowhammer Attacks on ARM / van der Veen, V., Lindorfer, M., Fratantonio, Y., Padmanabha Pillai, H., Vigna, G., Kruegel, C., Bos, H., & Razavi, K. (2018). GuardION: Practical Mitigation of DMA-Based Rowhammer Attacks on ARM. In Detection of Intrusions and Malware, and Vulnerability Assessment (pp. 92–113). Springer. https://doi.org/10.1007/978-3-319-93411-2_5
- MineSweeper: An In-depth Look into Drive-by Cryptocurrency Mining and Its Defense / Konoth, R. K., Vineti, E., Moonsamy, V., Lindorfer, M., Kruegel, C., Bos, H., & Vigna, G. (2018). MineSweeper: An In-depth Look into Drive-by Cryptocurrency Mining and Its Defense. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. ACM. https://doi.org/10.1145/3243734.3243858
- Bug Fixes, Improvements, ... and Privacy Leaks - A Longitudinal Study of PII Leaks Across Android App Versions / Ren, J., Lindorfer, M., Dubois, D. J., Rao, A., Choffnes, D., & Vallina-Rodriguez, N. (2018). Bug Fixes, Improvements, ... and Privacy Leaks - A Longitudinal Study of PII Leaks Across Android App Versions. In Proceedings 2018 Network and Distributed System Security Symposium. Internet Society. https://doi.org/10.14722/ndss.2018.23143
- Panoptispy: Characterizing Audio and Video Exfiltration from Android Applications / Pan, E., Ren, J., Lindorfer, M., Wilson, C., & Choffnes, D. (2018). Panoptispy: Characterizing Audio and Video Exfiltration from Android Applications. In Proceedings on Privacy Enhancing Technologies (pp. 33–50). DeGruyter. https://doi.org/10.1515/popets-2018-0030
2017
- Obfuscation-Resilient Privacy Leak Detection for Mobile Apps Through Differential Analysis / Continella, A., Fratantonio, Y., Lindorfer, M., Puccetti, A., Zand, A., Kruegel, C., & Vigna, G. (2017). Obfuscation-Resilient Privacy Leak Detection for Mobile Apps Through Differential Analysis. In Proceedings 2017 Network and Distributed System Security Symposium. Internet Society. https://doi.org/10.14722/ndss.2017.23465
2016
- Drammer: Deterministic Rowhammer Attacks on Mobile Platforms / van der Veen, V., Fratantonio, Y., Lindorfer, M., Gruss, D., Maurice, C., Vigna, G., Bos, H., Razavi, K., & Giuffrida, C. (2016). Drammer: Deterministic Rowhammer Attacks on Mobile Platforms. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. ACM. https://doi.org/10.1145/2976749.2978406
- ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic / Ren, J., Rao, A., Lindorfer, M., Legout, A., & Choffnes, D. (2016). ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic. In Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services. ACM. https://doi.org/10.1145/2906388.2906392
- CuriousDroid: Automated User Interface Interaction for Android Application Analysis Sandboxes / Carter, P., Mulliner, C., Lindorfer, M., Robertson, W., & Kirda, E. (2016). CuriousDroid: Automated User Interface Interaction for Android Application Analysis Sandboxes. In Financial Cryptography and Data Security (pp. 231–249). Springer. https://doi.org/10.1007/978-3-662-54970-4_13
2015
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Malware through the looking glass : malware analysis in an evolving threat landscape
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Lindorfer, M. (2015). Malware through the looking glass : malware analysis in an evolving threat landscape [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2015.35065
Download: PDF (2.89 MB) -
MARVIN: Efficient and Comprehensive Mobile App Classification through Static and Dynamic Analysis
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Lindorfer, M., Neugschwandtner, M., & Platzer, C. (2015). MARVIN: Efficient and Comprehensive Mobile App Classification through Static and Dynamic Analysis. In 2015 IEEE 39th Annual Computer Software and Applications Conference. IEEE. https://doi.org/10.1109/compsac.2015.103
Project: SysSec (2010–2014)
2014
- Enter Sandbox: Android Sandbox Comparison / Neuner, S., van der Veen, V., Lindorfer, M., Huber, M., Georg, M., Mulazzani, M., & Weippl, E. (2014). Enter Sandbox: Android Sandbox Comparison. In Proceedings of the IEEE Mobile Security Technologies Workshop (MoST). IEEE. http://hdl.handle.net/20.500.12708/55124
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Skin Sheriff: A Machine Learning Solution for Detecting Explicit Images
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Platzer, C., Stuetz, M., & Lindorfer, M. (2014). Skin Sheriff: A Machine Learning Solution for Detecting Explicit Images. In Proceedings of the 2nd international workshop on Security and forensics in communication systems - SFCS ’14. IEEE. https://doi.org/10.1145/2598918.2598920
Project: SysSec (2010–2014) -
ANDRUBIS -- 1,000,000 Apps Later: A View on Current Android Malware Behaviors
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Lindorfer, M., Neugschwandtner, M., Weichselbaum, L., Fratantonio, Y., Veen, V. van der, & Platzer, C. (2014). ANDRUBIS -- 1,000,000 Apps Later: A View on Current Android Malware Behaviors. In 2014 Third International Workshop on Building Analysis Datasets and Gathering Experience Returns for Security (BADGERS). IEEE. https://doi.org/10.1109/badgers.2014.7
Project: SysSec (2010–2014) -
AndRadar: Fast Discovery of Android Applications in Alternative Markets
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Lindorfer, M., Volanis, S., Sisto, A., Neugschwandtner, M., Athanasopoulos, E., Maggi, F., Platzer, C., Zanero, S., & Ioannidis, S. (2014). AndRadar: Fast Discovery of Android Applications in Alternative Markets. In Detection of Intrusions and Malware, and Vulnerability Assessment (pp. 51–71). Springer. https://doi.org/10.1007/978-3-319-08509-8_4
Project: SysSec (2010–2014)
2013
- POSTER: Cross-Platform Malware: Write Once, Infect Everywhere / Lindorfer, M., Neumayr, M., Caballero, J., & Platzer, C. (2013). POSTER: Cross-Platform Malware: Write Once, Infect Everywhere. In ACM Conference on Computer and Communications Security (CCS). ACM Conference on Computer and Communications Security (CCS), Washington, USA, Non-EU. http://hdl.handle.net/20.500.12708/54855
- Take a Bite - Finding the Worm in the Apple / Lindorfer, M., Miller, B., Neugschwandtner, M., & Platzer, C. (2013). Take a Bite - Finding the Worm in the Apple. In International Conference on Information, Communications and Signal Processing (ICICS). IEEE. http://hdl.handle.net/20.500.12708/54856
- A View to a Kill: WebView Exploitation / Neugschwandtner, M., Lindorfer, M., & Platzer, C. (2013). A View to a Kill: WebView Exploitation. In USENIX Workshop on Large-Scale Exploits and Emergent Threats (LEET). USENIX. http://hdl.handle.net/20.500.12708/54854
2012
- Lines of Malicious Code: Insights Into the Malicious Software Industry / Lindorfer, M., Di Federico, A., Maggi, F., Milani Comparetti, P., & Zanero, S. (2012). Lines of Malicious Code: Insights Into the Malicious Software Industry. In Proceedings of the 28th Annual Computer Security Applications Conference (pp. 349–358). ACM. http://hdl.handle.net/20.500.12708/54349
2011
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Detecting Environment-Sensitive Malware
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Lindorfer, M., Kolbitsch, C., & Milani Comparetti, P. (2011). Detecting Environment-Sensitive Malware. In Proceedings of the 14th International Symposium on Recent Advances in Intrusion Detection (2011). Springer. http://hdl.handle.net/20.500.12708/54010
Projects: icode (2010–2012) / SysSec (2010–2014) / TRUDIE (2009–2012)
Supervisions
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Security and Privacy Concerns in Shared Configuration Repositories
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Jungwirth, G. (2023). Security and Privacy Concerns in Shared Configuration Repositories [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.94601
Download: PDF (933 KB) -
Android vs. iOS: : security of mobile Deep Links
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Steinböck, M. (2022). Android vs. iOS: : security of mobile Deep Links [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.93327
Download: PDF (2.15 MB) -
Curious apps: Large-scale detection of apps scanning your local network
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Hager, P. T. (2022). Curious apps: Large-scale detection of apps scanning your local network [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.98764
Download: PDF (1.35 MB) -
Tracing android apps based on ART ahead-of-time compilation profiles from Google Play
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Burtscher, L. (2022). Tracing android apps based on ART ahead-of-time compilation profiles from Google Play [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.90745
Download: PDF (1.22 MB) -
Large-scale Static Analysis of PII Leakage in IoT Companion Apps
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Schmidt, D. (2021). Large-scale Static Analysis of PII Leakage in IoT Companion Apps [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.86548
Download: PDF (2.16 MB) -
Dynamic iOS privacy analysis: Verifying App Store privacy labels
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Jirout, T. W. (2021). Dynamic iOS privacy analysis: Verifying App Store privacy labels [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.92880
Download: PDF (1.51 MB) -
Detecting neural network functions in binaries based on syntactic features
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Aschl, G. (2020). Detecting neural network functions in binaries based on syntactic features [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2020.66352
Download: PDF (2.41 MB) -
Current state of browser extension security and extension-based malware
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Neumayr, M. (2015). Current state of browser extension security and extension-based malware [Diploma Thesis]. reposiTUm. https://doi.org/10.34726/hss.2015.24755
Download: PDF (742 KB)