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Emmanuel M. Drakakis

Publications and source records attributed to Emmanuel M. Drakakis.

3 recordsLinked to original sources

QT-PUF: Quantum Tunneling Leakage Based PUF for Implantable IoMT Devices

The Internet of Medical Things (IoMT) marks a shift toward decentralized healthcare, enabling continuous monitoring and personalized care through connected wearable and implantable devices. However, ensuring the trust and integrity of these devices themselves remains a major challenge, as physical compromise or counterfeiting can directly endanger patient safety, privacy, and data integrity. This work presents QT-PUF, a gate-tunneling-leakage-based physical unclonable function (PUF) that leverages quantum-mechanical gate leakage resulting from process-induced variations in standard CMOS devices. A differential readout circuit with a pseudo-resistor I-to-V frontend is proposed to convert the picoampere-level leakage variations into digital responses. Unlike existing PUFs such as those based on memory, ring oscillators, or arbiters, which are less suitable for ultralow-power IoMT devices (due to additional circuitry, power overhead, or poor stability), QT-PUF requires no external excitation or stabilization and operates under static bias. Simulation-based measurements for a $\mathbf{65}$~nm CMOS process demonstrate an entropy of $\mathbf{0.9999998}$, an FHD of $\mathbf{0.5001}$, and an average power (energy) consumption of $\mathbf{96.04}$~nW/bit ($\mathbf{19.21}$~fJ/bit, respectively) at $\mathbf{1.2\,V}$ and $\mathbf{35\,^{\circ}C}$ for the proposed PUF. It operates reliably across $\mathbf{0.9}\text{--}\mathbf{1.3}$~V and $\mathbf{0}\text{--}\mathbf{100\,^{\circ}C}$ with an average BER below $\mathbf{0.000163}$ across $\mathbf{1.0}\text{--}\mathbf{1.3}$~V and $\mathbf{10}\text{--}\mathbf{70\,^{\circ}C}$ within the operating conditions of typical implantable devices.

cs.CR

Window functions and sigmoidal behaviour of memristive systems

A common approach to model memristive systems is to include empirical window functions to describe edge effects and non-linearities in the change of the memristance. We demonstrate that under quite general conditions, each window function can be associated with a sigmoidal curve relating the normalised time-dependent memristance to the time integral of the input. Conversely, this explicit relation allows us to derive window functions suitable for the mesoscopic modelling of memristive systems from a variety of well-known sigmoidals. Such sigmoidal curves are defined in terms of measured variables and can thus be extracted from input and output signals of a device and then transformed to its corresponding window. We also introduce a new generalised window function that allows the flexible modelling of asymmetric edge effects in a simple manner.

cond-mat.mes-hall

Quantitative Measure of Hysteresis for Memristors Through Explicit Dynamics

We introduce a mathematical framework for the analysis of the input-output dynamics of externally driven memristors. We show that, under general assumptions, their dynamics comply with a Bernoulli differential equation and hence can be nonlinearly transformed into a formally solvable linear equation. The Bernoulli formalism, which applies to both charge- and flux-controlled memristors when either current- or voltage-driven, can, in some cases, lead to expressions of the output of the device as an explicit function of the input. We apply our framework to obtain analytical solutions of the i-v characteristics of the recently proposed model of the Hewlett-Packard memristor under three different drives without the need for numerical simulations. Our explicit solutions allow us to identify a dimensionless lumped parameter that combines device-specific parameters with properties of the input drive. This parameter governs the memristive behavior of the device and, consequently, the amount of hysteresis in the i-v. We proceed further by defining formally a quantitative measure for the hysteresis of the device for which we obtain explicit formulas in terms of the aforementioned parameter and we discuss the applicability of the analysis for the design and analysis of memristor devices.

cond-mat.mes-hall