Publications – AUTOPSY

AUTOMOTIVE Autonomous Vehicle AUTOPSY cloud computing Connected Cyber-Physical Systems (CPS) GDPR IoT PETs Privacy Privacy engineering framework Security Threat Analysis 
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2024
 Al-Momani, Ala'a;  Balenson, David;  Mann, Zoltán Ádám;  Pape, Sebastian;  Petit, Jonathan;  Bösch, Christoph
Navigating Privacy Patterns in the Era of Robotaxis Proceedings Article 
In: IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) 2024, International Workshop on Privacy Engineering (IWPE) 2024, pp. 32-39, 2024.
Abstract | Links | BibTeX | Tags: AUTOMOTIVE, AUTOPSY, IoT, PETs, Privacy
@inproceedings{ABMPPB24iwpe,

title = {Navigating Privacy Patterns in the Era of Robotaxis},

author = {Ala'a Al-Momani and David Balenson and Zoltán Ádám Mann and Sebastian Pape and Jonathan Petit and Christoph Bösch},

url = {https://ieeexplore.ieee.org/abstract/document/10628728},

doi = {10.1109/EuroSPW61312.2024.00011},

year  = {2024},

date = {2024-01-01},

booktitle = {IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) 2024, International Workshop on Privacy Engineering (IWPE) 2024},

pages = {32-39},

abstract = {Privacy engineering encompasses various method-ologies and tools, including privacy strategies and privacy patterns, aimed at achieving systems that inherently respect privacy. Despite the collection of numerous privacy patterns, their practical application remains under-explored. This paper investigates the applicability of privacy patterns in the context of robotaxis, a use case in the broader Mobility-as-a-Service (MaaS) ecosystem. Using the LINDDUN framework for privacy threat elicitation, we analyze existing privacy patterns to address identified privacy threats. Our findings reveal challenges in applying these patterns due to inconsis-tencies and a lack of guidance, as well as a lack of suitable privacy patterns for addressing several privacy threats. To fill the gaps, we propose ideas for new privacy patterns.},

keywords = {AUTOMOTIVE, AUTOPSY, IoT, PETs, Privacy},

pubstate = {published},

tppubtype = {inproceedings}

}

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Privacy engineering encompasses various method-ologies and tools, including privacy strategies and privacy patterns, aimed at achieving systems that inherently respect privacy. Despite the collection of numerous privacy patterns, their practical application remains under-explored. This paper investigates the applicability of privacy patterns in the context of robotaxis, a use case in the broader Mobility-as-a-Service (MaaS) ecosystem. Using the LINDDUN framework for privacy threat elicitation, we analyze existing privacy patterns to address identified privacy threats. Our findings reveal challenges in applying these patterns due to inconsis-tencies and a lack of guidance, as well as a lack of suitable privacy patterns for addressing several privacy threats. To fill the gaps, we propose ideas for new privacy patterns.
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https://ieeexplore.ieee.org/abstract/document/10628728
doi:10.1109/EuroSPW61312.2024.00011
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2023
 Pape, Sebastian;  Syed-Winkler, Sarah;  Garcia, Armando Miguel;  Chah, Badreddine;  Bkakria, Anis;  Hiller, Matthias;  Walcher, Tobias;  Lombard, Alexandre;  Abbas-Turki, Abdeljalil;  Yaich, Reda
A Systematic Approach for Automotive Privacy Management Proceedings Article 
In: CSCS '23: ACM Computer Science in Cars Symposium, Darmstadt, Germany, December 5th, 2023, ACM, 2023.
BibTeX | Tags: AUTOMOTIVE, AUTOPSY, GDPR, PETs, Privacy
@inproceedings{PSGCBHWLAY23cscs,

title = {A Systematic Approach for Automotive Privacy Management},

author = {Sebastian Pape and Sarah Syed-Winkler and Armando Miguel Garcia and Badreddine Chah and Anis Bkakria and Matthias Hiller and Tobias Walcher and Alexandre Lombard and Abdeljalil Abbas-Turki and Reda Yaich},

year  = {2023},

date = {2023-01-01},

booktitle = {CSCS '23: ACM Computer Science in Cars Symposium, Darmstadt, Germany, December 5th, 2023},

volume = {to appear},

publisher = {ACM},

keywords = {AUTOMOTIVE, AUTOPSY, GDPR, PETs, Privacy},

pubstate = {published},

tppubtype = {inproceedings}

}

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