Raspberry Pi

Le Raspberry Pi est un nano-ordinateur monocarte à processeur ARM de la taille d'une carte de crédit conçu par des professeurs du département informatique de l'université de Cambridge dans le cadre de la fondation Raspberry Pi. Le Raspberry Pi fut créé afin de démocratiser l'accès aux ordinateurs et au digital making (terme anglophone désignant à la fois la capacité de résolution de problèmes et les compétences techniques et informatiques). Cette démocratisation est possible en raison du coût réduit du Raspberry Pi, mais aussi grâce aux logiciels libres. Le Raspberry Pi permet l'exécution de plusieurs variantes du système d'exploitation libre GNU/Linux, notamment Debian ou Ubuntu, ainsi que des logiciels compatibles. Il fonctionne également avec le système d'exploitation Microsoft Windows : IoT Core, on ARM (pour l' relativement instable), celui de Google Android Pi et même une version de l'OS/MVT d'IBM accompagnée du système APL\360. Il est

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HolA: Holistic and Autonomous Attestation for IoT Networks

Eleonora Losiouk

Collective Remote Attestation (CRA) is a well-established approach where a single Verifier attests the integrity of multiple devices in a single execution of the challenge-response protocol. Current CRA solutions are well-suited for Internet of Things (IoT) networks, where the devices are distributed in a mesh topology and communicate only with their physical neighbours. Recent advancements on low-energy protocols, though, enabled the IoT devices to connected to the Internet, thus disrupting the concept of physical neighbour. In this paper, we propose HolA (Holistic and Autonomous Attestation), the first CRA scheme designed for Internet-like IoT networks. HolA provides defence against attacks targeting both the nodes and the network infrastructure. We deployed HolA on both a network of real devices (i.e., 5 Raspberry Pis) and a simulated environment (i.e., 1M devices in an Omnet++ network). Our results demonstrate that HolA can resist against a disruptive attacker that compromises up to half of the network devices and that tampers with network traffic. HolA can verify the integrity of 1M devices in around 12 s while the state-of-the-art requires 71 s. Finally, HolA requires 7 times less memory per device compared with the state-of-the-art.

SPRINGER INTERNATIONAL PUBLISHING AG2022

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SemiHD: Semi-Supervised Learning Using Hyperdimensional Computing

Samuel Bosch, Mohsen Imani

In the Internet of Things (IoT), the large volume of data generated by sensors poses significant computational challenges in resource-constrained environments. Most existing machine learning algorithms are unable to train a proper model using a significantly small amount of labeled data available in practice. In this paper, we propose SemiHD, a novel semi-supervised algorithm based on brain-inspired HyperDimensional (HD) computing. SemiHD performs the cognitive task by emulating neuron's activity in high-dimensional space. SemiHD maps data points into high-dimensional space and trains a model based on the available labeled data. To improve the quality of the model, SemiHD iteratively expands the training data by labeling data points which can be classified by the current model with high confidence. We also proposed a framework which enables users to trade accuracy for efficiency and select the desired reliability of the model in detecting out of scope data. We have evaluated SemiHD's accuracy and efficiency on a wide range of classification applications and two types of embedded devices: Raspberry Pi 3 and Kintex-7 FPGA. Our evaluation shows that SemiHD can improve the classification accuracy of supervised HD by 10.2% on average (up to 27.3%). In addition, we observe that SemiHD FPGA implementation achieves 7.11x faster and 12.6x energy efficiency as compared to the CPU implementation.

IEEE2019

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BioLocker: A Practical Biometric Authentication Mechanism based on 3D Fingervein

Fatma Betül Durak, Loïs Evan Huguenin-Dumittan, Serge Vaudenay

We design a consecution of protocols which allows organizations to have secure strong access control of their users to their desktop machines based on biometry. It provides both strong secure authentication and privacy. Moreover, our mechanism allows the system admins to grant a various level of access to their end-users by fine-tuning access control policy. Our system implements privacy-by-design. It separates biometric data from identity information. It is practical: we fully implemented our protocols as a proof of concept for a hospital. We use a 3D fingervein scanner to capture the biometric data of the user on a Raspberry Pi. For the biometry part, we developed an optimal way to aggregate scores using sequential distinguishers. It trades desired FAR and FRR against an average number of biometric captures.

Springer, Cham2020

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