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--- master-projects-sciancalepore [2021/01/10 21:04] – external edit 127.0.0.1
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 ====== Some ideas for a Master Thesis ======
-If you are interested in the topics below, you can contact Savio Sciancalepore (s.sciancalepore * tue.nl (replace * with @) ).
+If you are interested in the topics below, you can contact Savio Sciancalepore (s.sciancalepore * tue.nl (replace * with @) ). You can also check some recent publications at ssciancalepore.win.tue.nl
+**Privacy-Enhancing Technologies (PETS) for Internet of Things (IoT) Deployments**
+Thanks to the increasing capability of embedding powerful microcontrollers, modern IoT devices are equipped with even more computational capabilities, getting slowly closer to IT deployments in terms of processing resources. However, two main limitations still stand: (i) many IoT devices, especially mobile ones, feature batteries with limited energy availability, requiring the devices to save energy as much as possible to achieve the planned operations while maximizing lifetime; and (ii) many IoT devices might operate unattended, even for short time periods. Therefore, adversaries active in the field may have the opportunity to physically capture such devices and access their contents, posing confidentiality and privacy issues.
+To mitigate such threats, our team at TU/e works on integrating PETS onboard various IoT devices. The integration presents various challenges, due to the limitations still existing in the computational capabilities of the devices, the peculiar nature of the Operating Systems (OS) onboard, and the energy limitations, requiring us either to adapt existing PETS to the specific use cases or to come up with new, ad-hoc solutions for the domain.
+Reference Papers:
+  - George, Dominik Roy, Savio Sciancalepore, and Nicola Zannone. "Privacy-Preserving Multi-Party Access Control for Third-Party UAV Services." Proceedings of the 28th ACM Symposium on Access Control Models and Technologies. 2023. [[https://dl.acm.org/doi/pdf/10.1145/3589608.3593837|PDF]]
+  - Sciancalepore, Savio, and Dominik Roy George. "Privacy-Preserving Trajectory Matching on Autonomous Unmanned Aerial Vehicles." Proceedings of the 38th Annual Computer Security Applications Conference. 2022. [[https://dl.acm.org/doi/pdf/10.1145/3564625.3564626|PDF]]
+**Physical-Layer Security in Internet of Things (IoT) Networks**.
+Physical-layer security (PLS) approaches leverage intrinsic characteristics of the devices or of their transmitted signals to provide various security services, such as authentication, spoofing detection, and jamming detection, to name a few. Such approaches require no cryptography operations from the involved devices, thus being very useful in contexts where such devices cannot afford to run expensive cryptography techniques, e.g., constrained IoT networks. Also, PLS approaches require no modifications to the transmitters, as they can use unencrypted and opportunistic signals emitted by the target devices. Thus, PLS approaches are also useful in contexts where modifying the transmitter is hard, e.g., for some specific IoT deployments or in satellite networks.
+At the same time, deploying PLS approaches in the wild requires dealing with a large variety of undesired side effects, e.g., the movements of the involved devices, variable noise affecting the communication channel, and temporal phenomena. Our team at TU/e works on improving the robustness of PLS approaches when deployed in the real world, so as to mitigate and overcome issues due to real-world operating conditions.
+Reference Papers:
+  - Oligeri, G., Sciancalepore, S., Raponi, S., & Di Pietro, R. (2022). PAST-AI: Physical-layer authentication of satellite transmitters via deep learning. IEEE Transactions on Information Forensics and Security, 18, 274-289. [[https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9936663|PDF]]
+  - Alhazbi, Saeif, Savio Sciancalepore, and Gabriele Oligeri. "BloodHound: Early Detection and Identification of Jamming at the PHY-layer." 2023 IEEE 20th Consumer Communications & Networking Conference (CCNC). IEEE, 2023. [[https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10059878|PDF]]
-  - **Low-Delay Service Access in Fog-Enabled IoT Ecosystems**. Fog computing has recently emerged as an innovative system architecture, especially for low-delay Internet of Things (IoT) applications. Thanks to the deployment of dedicated “Fog Nodes” geographically closer to where data are produced and/or requested, IoT devices can enjoy very reduced reporting data delay, as well as limited latencies in data access. However, authentication and authorization processes in Fog-enabled IoT ecosystems are usually handled by the Cloud, in a fully centralized fashion. Therefore, any time an IoT device would like to access resources available at the Fog layer, it should first connect to the Cloud to accomplish authentication. Moreover, when access control mechanisms are in place, the Fog Node should contact the services hosted in the Cloud to verify the possession of the correct set of attributes by the requesting IoT device. Especially in mobile and dynamic IoT ecosystems, these mechanisms are not flexible, and incur significant delays. In addition, given that Fog Nodes are deployed in the wild, they can be hacked by motivated adversaries, more easily than traditional Cloud servers. Therefore, they can collude among them and with the adversary, to track the IoT devices while they access services and move in the Fog-enabled IoT ecosystem. In this project, we aim to design, implement, and test a Low-Delay, Privacy-Preserving, and Anonymous Authentication and Authorization solution for Fog-Enabled IoT Ecosystems. The solution integrates tools such as Token-based Access Control strategies and Attribute-Based Encryption (ABE) solutions in the emerging Fog Computing architecture, creating a solution that can achieve low-delay authentication and authorization, while also providing protection against identity and location tracking by malicious Fog Nodes.