This paper provides a mathematical model that describes how deterministic and Gaussian jitter of an oscillating signal accumulated during a time interval are related to the bits of the binary-coded count value of the oscillations. The model is employed to propose a robust TRNG that has a simple interface (an initialization signal as input and the random bits as output) and that features auto-calibration to certify high entropy of the raw bits provided as well as to work at the highest throughput allowed by the available local Gaussian noise. The mathematical analysis is confirmed with experimental results of ring oscillator (RO) TRNGs described in VHDL and implemented in the programmable logic of Zynq family Xilinx FPGAs, using either another RO or the clock of the FPGA board to control the time interval of oscillations.

Security is essential in sensor nodes which acquire and transmit sensitive data. However, the constraints of processing, memory and power consumption are very high in these nodes. Cryptographic algorithms based on symmetric key are very suitable for them. The drawback is that secure storage of secret keys is required. In this work, a low-cost solution is presented to obfuscate secret keys with Physically Unclonable Functions (PUFs), which exploit the hardware identity of the node. In addition, a lightweight fingerprint recognition solution is proposed, which can be implemented in low-cost sensor nodes. Since biometric data of individuals are sensitive, they are also obfuscated with PUFs. Both solutions allow authenticating the origin of the sensed data with a proposed dual-factor authentication protocol. One factor is the unique physical identity of the trusted sensor node that measures them. The other factor is the physical presence of the legitimate individual in charge of authorizing their transmission. Experimental results are included to prove how the proposed PUF-based solution can be implemented with the SRAMs of commercial Bluetooth Low Energy (BLE) chips which belong to the communication module of the sensor node. Implementation results show how the proposed fingerprint recognition based on the novel texture-based feature named QFingerMap16 (QFM) can be implemented fully inside a low-cost sensor node. Robustness, security and privacy issues at the proposed sensor nodes are discussed and analyzed with experimental results from PUFs and fingerprints taken from public and standard databases.

This work presents a Very Large Scale Integration (VLSI) design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption. The sensed variable is estimated by a virtual sensor based on a configurable and programmable PieceWise-Affine hyper-Rectangular (PWAR) model. An algorithm is presented to find the best values of the programmable parameters given a set of (empirical or simulated) input-output data. The VLSI design of the trusted virtual sensor uses the fast authenticated encryption algorithm, AEGIS, to ensure the integrity of the provided virtual measurement and to encrypt it, and a Physical Unclonable Function (PUF) based on a Static Random Access Memory (SRAM) to ensure the integrity of the sensor itself. Implementation results of a prototype designed in a 90-nm Complementary Metal Oxide Semiconductor (CMOS) technology show that the active silicon area of the trusted virtual sensor is 0.86 mm ${}^2$ and its power consumption when trusted sensing at 50 MHz is 7.12 mW. The maximum operation frequency is 85 MHz, which allows response times lower than 0.25 $\mathsf{\mu }$ s. As application example, the designed prototype was programmed to estimate the yaw rate in a vehicle, obtaining root mean square errors lower than 1.1%. Experimental results of the employed PUF show the robustness of the trusted sensing against aging and variations of the operation conditions, namely, temperature and power supply voltage (final value as well as ramp-up time).

Physical Unclonable Functions (PUFs) have gained a great interest for their capability to identify devices uniquely and to be a lightweight primitive in cryptographic protocols. However, several reported attacks have shown that virtual copies (mathematical clones) as well as physical clones of PUFs are possible, so that they cannot be considered as tamper-resistant or tamper-evident, as claimed. The solution presented in this article is to extend the PUFs reported until now, which are only physical, to make them Behavioral and Physical Unclonable Functions (BPUFs). Given a challenge, BPUFs provide not only a physical but also a behavioral distinctive response caused by manufacturing process variations. Hence, BPUFs are more difficult to attack than PUFs since physical and behavioral responses associated to challenges have to be predicted or cloned. Behavioral responses that are obtained from several measurements of the physical responses taken at several sample times are proposed. In this way, the behavioral responses can detect if the physical responses are manipulated. The analysis done for current PUFs is extended to allow for more versatility in the responses that can be considered in BPUFs. Particularly, Jaccard instead of Hamming distances are proposed to evaluate the similarity of behavioral responses. As example to validate the proposed solution, BPUFs based on Static Random-Access Memories (SRAM BPUFs), with one physical and one behavioral responses to given challenges, were analyzed experimentally using integrated circuits fabricated in a 90-nm CMOS technology. If an attacker succeeds in cloning the physical responses as reported, but does not attack the way to obtain the behavioral responses, the attacker fails on SRAM BPUFs. The highest probability to succeed in cloning the behavioral responses with a brute-force attack was estimated from experimental results as $1.5 \cdot 10^{-34}$ , considering the influence of changes in the operating conditions (power supply voltage, temperature, and aging).

Nowadays, there is an increasing number of cameras placed on mobile devices connected to the Internet. Since these cameras acquire and process sensitive and vulnerable data in applications such as surveillance or monitoring, security is essential to avoid cyberattacks. However, cameras on mobile devices have constraints in size, computation and power consumption, so that lightweight security techniques should be considered. Camera identification techniques guarantee the origin of the data. Among the camera identification techniques, Physically Unclonable Functions (PUFs) allow generating unique, distinctive and unpredictable identifiers from the hardware of a device. PUFs are also very suitable to obfuscate secret keys (by binding them to the hardware of the device) and generate random sequences (employed as nonces). In this work, we propose a trusted camera based on PUFs and standard cryptographic algorithms. In addition, a protocol is proposed to protect the communication with the trusted camera, which satisfies authentication, confidentiality, integrity and freshness in the data communication. This is particularly interesting to carry out camera control actions and firmware updates. PUFs from Static Random Access Memories (SRAMs) are selected because cameras typically include SRAMs in its hardware. Therefore, additional hardware is not required and security techniques can be implemented at low cost. Experimental results are shown to prove how the proposed solution can be implemented with the SRAM of commercial Bluetooth Low Energy (BLE) chips included in the communication module of the camera. A proof of concept shows that the proposed solution can be implemented in low-cost cameras.