Physical Unclonable Functions (PUFs) offer a promising solution for authentication of IoT devices as they provide unique fingerprints for the underlying devices through their challenge-response pairs. However, PUFs have been shown to be vulnerable to modeling attacks. In this paper, we propose a novel protocol to thwart such vulnerability by limiting the adversary's ability to intercept the whole challenge bits exchanged with IoT nodes. We split the challenge bits over multiple messages and engage one or multiple helper nodes in the dissemination process. We further study the implications of various parts of the challenge patterns on the modeling attack and propose extensions of our protocol that exploit bits scrambling and padding to ameliorate the attack resiliency. The experimental results extracted from a 16-bit and a 64-bit arbiter-PUF implemented on FPGA demonstrate the effectiveness of the proposed methods in boosting the robustness of IoT authentication.

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One way for an attacker to break a system is to perturb it. Expected effects are countermeasure deactivation or data corruption to disclose sensitive information. The prevention of such actions relies on detection of abnormal operating conditions. Digital sensors can play this role. A digital sensor is built out of the very same standard cells as the user logic to be protected. This ensures the advantage that the sensor and the user logic are exposed to the same stress. Balancing True positives and False negatives is a tough question in field of sensors. This is a general issue, and the best way to mitigate this paradox is to thoroughly investigate their properties, through simulations and real experiments. This results in characterizations, which in turn allows for intuitions on how to handle sensing values. In this paper, we exhibit the complex relationships between propagation times in logic and environmental conditions. Those results reinforce the relevance of the digital sensor versus the adversarial manipulation of environmental conditions: fewer false alarms are raised even if temperature (resp. voltage) is extreme, provided the effect is balanced by voltage (resp. temperature). Owing to the complex relationship between propagation delays, temperature and voltage, this cannot happen with a set of independent temperature and voltage sensors.

Fault Injection Attacks (FIA) have received a lot of attention in recent years. An adversary launches such an attack to abusively take control over the system or to leak sensitive data. Laser illumination has been considered as an effective technique to launch FIA. The laser-based FIAs are mainly used when the adversary opts to target a specific location in the target circuit. However, thanks to the miniaturization of transistors and moving towards smaller feature size, even small laser spots may illuminate more than one gate; making the attack more detectable when the circuitries are equipped with embedded fault detection mechanisms such as digital sensors. In this paper, we use timeto-digital convertors, aka digital sensors, to detect the laser shots. We show that by embedding these digital sensors in the target circuitry, the IR drop caused by the laser illumination can be sensed with a high accuracy. An alarm will be raised when the fault is detected. The simulation results show the high accuracy of the proposed scheme in detecting laser-based FIAs.

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