Description
The main purpose of cryptography is to ensure secure communication. In order to achieve this goal, cryptographic schemes make an intensive use of random numbers. Given that the security of these schemes highly depends on these numbers, it is important to produce high-quality random numbers. Knowing that most cryptographic modules are nowadays implemented in logic devices, we investigated True Random Number Generators (TRNGs) that can be implemented in this kind of technology. Because of the critical nature of TRNGs in cryptographic schemes, their source and their quality must be evaluated in details.
Historically, TRNGS were considered as black boxes which produce sequences of random numbers. There were therefore solely evaluated using statistical tests. However, this consideration turns out to be not acceptable for security. Modern approaches (e.g. AIS 31) consist in characterizing sources of randomness and randomness extraction mechanisms.
In this talk, we will highlight the main challenges and modern approaches in TRNG security evaluation. One of these challenges is the characterization of the source of randomness. It leads us to consider various electronic noises that need to be characterized and for which, the contribution to the overall entropy need to be assessed.
Infos pratiques
Prochains exposés
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FeFET based Logic-in-Memory design, methodologies, tools and open challenges
Orateur : Cédric Marchand - University of Lyon - Lyon Institute of Nanotechnology (UMR CNRS 5270)
Data-centric applications such as artificial intelligence and the Internet of Things (IoT) impose increasingly stringent demands on the performance, the security and the energy efficiency of modern computing architectures. Traditional approaches are often unable to keep pace with these requirements making necessary to explore innovative paradigms such as in-memory computing. This paradigm is[…]-
SemSecuElec
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TrustSoC : a heterogeneous secure-by-design SoC architecture
Orateur : Raphaële Milan - Université Jean Monnet Saint-Etienne, CNRS, Laboratoire Hubert Curien UMR 5516
Since the 1970s, the complexity of systems on a chip has grown significantly. In order to improve system performance, manufacturers are integrating an increasing number of heterogeneous components on a single silicon chip. The incorporation of these components renders SoCs highly versatile yet significantly complex. Their multipurpose nature makes them suitable for use in a variety of domains,[…]-
SemSecuElec
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The influence of flicker noise on ring oscillator-based TRNGs
Orateur : Licinius-Pompiliu BENEA - Univ. Grenoble Alpes, CEA, LETI
Ring oscillators (ROs) are often used in true random number generators (TRNGs). The jitter of their clock signal, used as a source of randomness, stems from thermal and flicker noises. While thermal noise jitter is often identified as the main source of randomness, flicker noise jitter is not taken into account due to its autocorrelated nature which greatly complexifies modelling. However, it is a[…]-
SemSecuElec
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GDAv
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Hardware Trojan Horses and Microarchitectural Side-Channel Attacks: Detection and Mitigation via Hardware-based
MethodologiesOrateur : Alessandro PALUMBO - CentraleSupélec, IRISA, Inria
Hardware Trojan Horses that are software-exploitable can be inserted into microprocessors, allowing attackers to run unauthorized code or escalate privileges. Additionally, it has been demonstrated that attackers could observe certain microprocessor features - seemingly unrelated to the program's execution - to exfiltrate secrets or private data. So, even devices produced in secure foundries could[…]-
SemSecuElec
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Canaux auxiliaires
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Vulnérabilités micro-architecturales
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Cheval de Troie matériel
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Covert Communication Channels Based On Hardware Trojans: Open-Source Dataset and AI-Based Detection
Orateur : Alan Díaz Rizo - Sorbonne Université Lip6
The threat of Hardware Trojan-based Covert Channels (HT-CCs) presents a significant challenge to the security of wireless communications. In this work, we generate in hardware and make open-source a dataset for various HT-CC scenarios. The dataset represents transmissions from a HT-infected RF transceiver hiding a CC that leaks information. It encompasses a wide range of signal impairments, noise[…]-
SemSecuElec
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Apprentissage machine
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Cheval de Troie matériel
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Cryptanalytical extraction of complex Neural Networks in black-box settings
Orateur : Benoit COQUERET - INRIA, Thales CESTI
With the widespread development of artifical intelligence, Deep Neural Networks (DNN) have become valuable intellectual property (IP). In the past few years, software and hardware-based attacks targetting at the weights of the DNN have been introduced allowing potential attacker to gain access to a near-perfect copy of the victim's model. However, these attacks either fail against more complex[…]-
SemSecuElec
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Canaux auxiliaires
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Apprentissage machine
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