Resource-constrained but widely deployed IoT devices require a new approach to ensure secure and reliable communications. That is why, in recent years, the paramount effort has been applied in lightweight cryptography. Because of its unpredictable nature, chaos is regarded as a potential candidate in cryptographic applications. Chaos mode of operation is observed not only in deliberately designed oscillators but also in switching DC-DC converters, which are part of almost every embedded design. The use of a built-in chaos source may improve performance, energy consumption, PCB area, and cost of IoT devices. In this research, the regions of robust chaos were identified using numerical analysis, and the performance of a real buck DC-DC converter under peak-current-mode control was studied experimentally. It was shown that a compensating ramp acts as a switch between different operating regimes. Despite minor performance degradation, chaos mode can be used for secure communications in IoT networks.

Chaos-based wireless communication systems offer promising opportunities for enhancing the physical-layer security of IoT devices. However, their successful integration depends on the ability to maintain robust chaotic behavior under environmental fluctuations, component tolerances, and parameter variations. This study investigates the nonlinear dynamics and hybrid synchronization of a modified Colpitts chaotic oscillator with a tunable base bias voltage. A comprehensive analysis is conducted through numerical simulations, SPICE-level modelling, and experimental validation using an analog prototype. While the simplified mathematical model shows only a DC offset shift with the added bias voltage, the SPICE simulations and hardware measurements reveal qualitative changes in the oscillator's dynamics. These findings underscore the importance of experimental verification, as idealized models often fail to capture critical behaviors in nonlinear systems. Hybrid synchronization is demonstrated between the analog oscillator and its FPGA-based digital counterpart, implemented using fixed-point arithmetic and the Euler–Cromer method. Despite model simplifications, effective synchronization is achieved via the Pecora–Carroll technique, highlighting that preserving the oscillator’s core dynamic structure is more critical than exact waveform replication. This result supports the practical use of chaos-based synchronization in resource-constrained secure communication systems.

Chaos-based wireless communication systems can enhance the physical-layer security of IoT devices, but their reliability depends on stable chaotic behavior under real conditions. We investigate a modified Colpitts oscillator with a tunable base bias voltage, introduced as an independent control parameter to flexibly adjust nonlinear regimes. Using numerical studies, SPICE simulations, and hardware experiments, we show that simplified numerical models predict only a DC offset shift, whereas realistic implementations reveal qualitative changes in the dynamics, highlighting the need for experimental validation. We further demonstrate hybrid synchronization between the analog oscillator and an FPGA-based digital model. Despite model simplifications and non-idealities, synchronization is successfully achieved using the Pecora–Carroll method, showing that preserving the core dynamic structure is more critical than exact waveform replication. These results clarify the constraints of idealized models for predicting dynamical patterns while confirming the robustness of hybrid synchronization for secure, resource-constrained communication systems.

Simple memristive circuits are attractive chaos sources for secure communication, random-number generation, and chaotic sensing. Reliable operation, however, requires knowing where in parameter space the chaos persists and where periodic windows or coexisting attractors make it fragile. This paper constructs an operating map for an improved memristive diode-bridge band-pass-filter circuit in its two accessible tuning parameters, set by the filter capacitance and the feedback resistance ratio. Two-parameter bifurcation maps and Lyapunov exponent fields give the global layout of the plane; numerical continuation traces the stable and unstable periodic-orbit branches that organise it; and phase portraits, power spectra, component-level SPICE simulation, and prototype measurements characterise representative regimes. The plane separates into broad chaotic regions, higher-period windows, a period-adding window, and a multistability zone. A chaotic interval is reported as robust chaos only when the tracked periodic branches are all unstable, the Lyapunov exponent is positive throughout, and initial-condition scans detect no coexisting attractor; the continuation shows the same period-doubling mechanism bounding the chaotic regions in both parameters. Mapping the dimensionless results to component values yields design guidance for reaching candidate robust-chaos regions and avoiding fragile and multistable zones, including a hardware-confirmed limit on inductor loss beyond which the chaotic band collapses.

The use of chaotic sequences for secure data transmission offers a promising means of protecting information against eavesdropping attacks. Unlike the conventional approach that relies on dedicated chaos oscillators, this study explores the feasibility of utilizing switching power supplies-already integrated into IoT devices for power delivery-as built-in chaos generators, eliminating the need for additional circuitry. This approach has the potential to reduce both cost and system complexity in chaos-based secure IoT communication systems. SPICE simulations are employed to examine the feasibility of synchronizing buck converters via a chaotic drive signal implemented in the feedback loop, as well as to evaluate synchronization performance under parameter deviations. The results show that two buck converters can achieve synchronization with a high correlation coefficient $(>0.9)$ using a chaotic drive signal, while still maintaining the desired output voltage level.

The proliferation of Internet of Things (IoT) devices and services creates not only significant benefits but also new security threats. Classical information encryption techniques are not suitable for resource-constrained edge modules, thereby generating the demand for lightweight and efficient data protection algorithms. This work presents a novel dynamical parameter estimation scheme for chaotic oscillators, applied to physical-layer authentication (PLA). The proposed approach relies on the receiver’s capability to estimate a selected parameter of the transmitter’s oscillator determined by circuit configuration from the received chaotic signal using a locally synchronized oscillator, thereby enabling secure authentication based on a hardware-encoded identifier. The scheme is intended to complement a chaos-based wireless sensor network (WSN) architecture, where sensor nodes (SNs) implement analog chaotic oscillators, and the gateway operates discrete-time models. The Vilnius chaotic oscillator was chosen to validate the proposed PLA scheme. A rigorous bifurcation analysis of analytical, SPICE and discrete oscillator models was first conducted to identify parameter regions that preserve chaotic dynamics, establishing correspondence between models to guarantee the feasibility of parameter estimation across implementations. The digital realization of the parameter estimator demonstrated accurate and stable operation, with a small and nearly constant estimation relative error not exceeding 1.01%. Key performance metrics were analyzed, including estimation time, precision, and noise robustness. A tradeoff between estimation speed and accuracy was identified, particularly under noisy channel conditions. Finally, the influence of the receiver’s native oscillator parameter on distinguishable transmitter parameter ranges was demonstrated, highlighting the configurability and security potential of the proposed system against unauthorized transmissions.