Publications | Dominik R. George

2025

Privacy at your Hands: Efficient Privacy-Enhancing Technologies for the Internet of Things

Dominik Roy George

Oct 2025

Proefschrift.

@phdthesis{53b28401e7aa4e96a08ab8435ffff55c,
  title = {Privacy at your Hands: Efficient Privacy-Enhancing Technologies for the Internet of Things},
  author = {George, Dominik Roy},
  year = {2025},
  month = oct,
  day = {30},
  publisher = {Eindhoven University of Technology},
  isbn = {978-90-386-6472-9},
  note = {Proefschrift.},
  language = {English},
  type = {Phd Thesis 1 (Research TU/e / Graduation TU/e)},
  school = {Mathematics and Computer Science}
}

IEEE IoTJ

ePPTM - Enhanced Privacy-Preserving Trajectory Matching on Autonomous Vehicles

Dominik Roy George, and Savio Sciancalepore

IEEE Internet Things J., Oct 2025

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2023

ACSAC
Remote Attestation with Constrained Disclosure

Michael Eckel, Dominik Roy George, Björn Grohmann, and 1 more author

In Annual Computer Security Applications Conference, ACSAC 2023, Austin, TX, USA, December 4-8, 2023, Oct 2023

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Trusted Platform Modules (TPMs) are used for remote attestation to ensure the authenticity and integrity of software running on a computer system. However, measuring software executed as containers or virtual machines can be challenging as it is measured concurrently, resulting in a jumbled measurement log that is difficult to disentangle. Moreover, disclosing the entire measurement log in traditional binary remote attestation raises privacy and intellectual property concerns. To address these issues, we propose a remote attestation method with constrained disclosure, allowing for selective disclosure of entries in the measurement log using a non-interactive zero-knowledge (NIZK) proof with Schnorr signatures. Our approach is evaluated for security and privacy and proven to be correct, sound, and satisfies the properties of a NIZK proof. Formal verification of our solution with ProVerif also supports our claims. Furthermore, the performance evaluation of our proof-of-concept implementation shows that our contribution is feasible, and the overhead introduced is negligible.
@inproceedings{DBLP:conf/acsac/EckelGGK23, author = {Eckel, Michael and George, Dominik Roy and Grohmann, Bj{\"{o}}rn and Krau{\ss}, Christoph}, title = {Remote Attestation with Constrained Disclosure}, booktitle = {Annual Computer Security Applications Conference, {ACSAC} 2023, Austin, TX, USA, December 4-8, 2023}, pages = {718--731}, publisher = {{ACM}}, year = {2023}, url = {https://doi.org/10.1145/3627106.3627118}, doi = {10.1145/3627106.3627118}, timestamp = {Mon, 04 Dec 2023 17:30:52 +0100}, biburl = {https://dblp.org/rec/conf/acsac/EckelGGK23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org}, }
SACMAT
Privacy-Preserving Multi-Party Access Control for Third-Party UAV Services

Dominik Roy George, Savio Sciancalepore, and Nicola Zannone

In Proceedings of the 28th ACM Symposium on Access Control Models and Technologies, SACMAT 2023, Trento, Italy, June 7-9, 2023, Oct 2023

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Third-Party Unmanned Aerial Vehicle (UAV) Services, a.k.a. Drone-as-a-Service (DaaS), are an increasingly adopted business model, which enables possibly unskilled users, with no background knowledge, to operate drones and run automated drone-based tasks. Although these services provide significant advantages, the resources provided by drones are typically owned by multiple parties. Thus, Third-Party UAV services require adopting multi-party access control solutions. In this context, the leakage of the access control policies specified by the data owners might disclose confidential information and, thus, they should be protected as well. In this work, we propose a privacy-preserving multi-party access control solution tailored to the application scenarios of Third-Party UAV Services. Our solution advances an existing privacy-preserving multi-party access control framework based on Secure Function Evaluation to fit the distributed and heterogeneous nature of drone deployments. Through an extensive experimental evaluation, we demonstrate our solution can perform private policy evaluation on constrained devices in a reasonable time while requiring limited communication, memory, and energy overhead.
@inproceedings{DBLP:conf/sacmat/GeorgeSZ23, author = {George, Dominik Roy and Sciancalepore, Savio and Zannone, Nicola}, editor = {Ranise, Silvio and Carbone, Roberto and Takabi, Daniel}, title = {Privacy-Preserving Multi-Party Access Control for Third-Party {UAV} Services}, booktitle = {Proceedings of the 28th {ACM} Symposium on Access Control Models and Technologies, {SACMAT} 2023, Trento, Italy, June 7-9, 2023}, pages = {19--30}, publisher = {{ACM}}, year = {2023}, url = {https://doi.org/10.1145/3589608.3593837}, doi = {10.1145/3589608.3593837}, timestamp = {Fri, 02 Jun 2023 01:00:00 +0200}, biburl = {https://dblp.org/rec/conf/sacmat/GeorgeSZ23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org}, }

2022

ACSAC
Privacy-Preserving Trajectory Matching on Autonomous Unmanned Aerial Vehicles

Savio Sciancalepore, and Dominik Roy George

In Annual Computer Security Applications Conference, ACSAC 2022, Austin, TX, USA, December 5-9, 2022, Oct 2022

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Autonomous Unmanned Aerial Vehicles (UAVs) are increasingly deployed nowadays, thanks to the additional features and enhanced flexibility they provide, e.g., for transportation and goods delivery. On the one hand, discovering in advance collisions occurring with other UAVs in the future could enhance the efficiency of the path planning, reducing further the delivery time and UAVs’ energy consumption. On the other hand, location and timestamps–key to detecting and avoiding collisions in advance–are sensitive and cannot be shared indiscriminately with untrusted entities. This paper solves the aforementioned challenging problem by proposing PPTM, a new protocol for efficient and effective privacy-preserving trajectory matching on autonomous UAVs. PPTM allows two UAVs, possibly not connected to the Internet, to discover any spatial and temporal collisions in their future paths, without revealing to the other party anything else than the colliding time and coordinates. To this aim, PPTM grounds on a dedicated tree-based algorithm, namely, Incremental Capsule Matching, tailored to the unique features of spatio-temporal data, and it also integrates a lightweight privacy-preserving proximity testing solution for performing private comparisons. We tested our solution on real devices with heterogeneous processing capabilities (a regular laptop, a tiny processing unit, and a mini-drone), showing that PPTM can perform privacy-preserving trajectory matching even in a few milliseconds, up to 98.27% quicker compared to the most efficient competing solution.
@inproceedings{DBLP:conf/acsac/SciancaleporeG22, author = {Sciancalepore, Savio and George, Dominik Roy}, title = {Privacy-Preserving Trajectory Matching on Autonomous Unmanned Aerial Vehicles}, booktitle = {Annual Computer Security Applications Conference, {ACSAC} 2022, Austin, TX, USA, December 5-9, 2022}, pages = {1--12}, publisher = {{ACM}}, year = {2022}, url = {https://doi.org/10.1145/3564625.3564626}, doi = {10.1145/3564625.3564626}, timestamp = {Sun, 25 Dec 2022 00:00:00 +0100}, biburl = {https://dblp.org/rec/conf/acsac/SciancaleporeG22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
IEEE CNS
PRM - Private Interference Discovery for IEEE 802.15 4 Networks

Dominik Roy George, and Savio Sciancalepore

In 10th IEEE Conference on Communications and Network Security, CNS 2022, Austin, TX, USA, October 3-5, 2022, Oct 2022

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Due to the mobile and pervasive nature of IoT networks, even more frequently, multiple IoT networks managed by different network administrators share the same spectrum and operate in the same area, leading to packet losses and degradation of the Quality of Service (QoS). Assuming the use of the widespread IEEE 802.15.4 communication technology, the most straightforward solution would be to allow the networks to share the local Radio Scheduling Table (RST) to optimize channel access. However, exchanging the RST can leak several key information, such as the topology of the network, the number of devices, and the channel access patterns. To address such problems, we present PRM, the first scheme for discovering in advance potential interferences among IEEE 802.15.4 networks, without exposing the whole RST to untrusted parties. Our solution adapts a protocol for Private Set Intersection, while combining it with an innovative iterative set division algorithm, making the whole solution feasible on constrained devices of the IoT domain. Our experimental performance assessment, carried out on heterogeneous devices, shows that PRM can discover colliding channel assignments in less than 1 sec. on more capable embedded devices (e.g., the Raspberry PI), while also being feasible for more constrained platforms (e.g., the ESPCopter), depending on the amount of used radio resources.
@inproceedings{DBLP:conf/cns/GeorgeS22, author = {George, Dominik Roy and Sciancalepore, Savio}, title = {{PRM} - Private Interference Discovery for {IEEE} 802.15 4 Networks}, booktitle = {10th {IEEE} Conference on Communications and Network Security, {CNS} 2022, Austin, TX, USA, October 3-5, 2022}, pages = {136--144}, publisher = {{IEEE}}, year = {2022}, url = {https://doi.org/10.1109/CNS56114.2022.9947236}, doi = {10.1109/CNS56114.2022.9947236}, timestamp = {Fri, 25 Nov 2022 09:04:32 +0100}, biburl = {https://dblp.org/rec/conf/cns/GeorgeS22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org}, }