Search Results (154)

Physical-layer key generation (PLKG) is a technique that produces symmetric encryption keys by exploiting the inherent characteristics of wireless channels. It offers advantages including high physical-layer security, elimination of pre-shared keys, dynamic upgradability, and resistance to quantum attacks, making PLKG a promising security solution for next-generation (6G) networks. However, satellite communication channels exhibit high dynamics and long propagation delays. Characteristics such as large Doppler shifts, short coherence times, and orbital predictability pose severe challenges to PLKG, including reciprocity degradation, low key generation rate (KGR), and susceptibility to channel-prediction attacks. This work proposes a delay-Doppler domain time-hopping key generation scheme (KE-DD-TH) based on Orthogonal Time Frequency Space (OTFS) modulation for high-speed links between Low-Earth-Orbit (LEO)/Medium-Earth-Orbit (MEO) satellites and ground terminals in Ka/Ku bands. The scheme performs non-uniform sampling on the DD domain grid of OTFS symbols using an ephemeris-driven pseudo-random time-hopping sequence generated by cascaded linear feedback shift registers (LFSRs) and a nonlinear matrix transformation. Both legitimate parties estimate the channel only at time-hopping instants and multiply two adjacent estimates to construct an “equivalent channel” matrix, yielding a random source with high entropy, high reciprocity, and low predictability. The eavesdropper’s key disagreement rate (KDR) remains close to 0.5 under all signal-to-noise ratio (SNR) conditions, corresponding to the ideal random-guessing baseline. This indicates that Eve obtains negligible mutual information, i.e., $I(K_A;K_E)\approx 0$. By contrast, the conventional KE-DD scheme allows Eve’s KDR to degrade to 0.014 at 30 dB SNR, indicating near-complete key recovery. The generated keys pass all 12 randomness tests of the NIST SP 800-22 statistical test suite. Full article

We study underwater optical communication under photon-counting (Poisson) detection with realistic attenuation, background radiance, directionality, and pointing uncertainty. Information is embedded in (i) a temporal dictionary of pseudo-random noise (PRN) intensity sequences and (ii) an optional spatio-temporal extension, denoted SIM–TS (spatial-index modulation with temporal signaling), that combines temporal coding with spatial indexing across multiple transmit/receive apertures. For a fixed optical energy-per-symbol (photon budget), these structured waveforms increase observation dimensionality and improve maximum-likelihood separability under Poisson statistics. We present a layered modeling framework, derive the corresponding Poisson detection metrics, and use Monte Carlo evaluation to extract maximum range at a target symbol error rate. The results show that dimensional signaling provides a modest but repeatable gain in clear-water photon-limited regimes: at 100 kbps, SIM–TS increases the clear-water range from 593.8 m to 617.2 m at 450 nm (3.95%) and from 457.8 m to 473.4 m at 420 nm (3.41%) under fixed total power. In coastal water the gain falls below 1%, while in the 1 Gbps benchmark SIM–TS under fixed total power remains within about 2% of on–off keying (OOK) and the larger improvement under power combining is attributable primarily to increased photon budget. These rate–range trade-offs clarify when dimensional signaling yields practical gains and when attenuation, background, and misalignment dominate the link budget. Full article

The possibility of securing textual image data sharing exponentially strengthens when it harnesses the potential of cryptography as well as deep learning methods. A review of the existing literature showcases some interesting and productive initiatives; however, they are noted with issues, viz., increased reconstruction error, weak generation of pseudorandom keys, static threshold-based validation, etc. All these issues lead to suboptimal data integrity as well as confidentiality, which is a leading gap in research on neural optimised-based solutions. Therefore, the proposed system introduces an innovative Twister Pseudo Random and Barzilai–Borwein Gradient Autoencoder Neural Network (TPR-BBGAN) for secure textual image data sharing. The model introduces various novel operations, viz., feature extraction using fuzzy batch-normalised preprocessing, key extraction using the Barzilai–Borwein method, an autoencoder, and Mersenne Twister. The TPR-BBGAN determines the optimal threshold dynamically, contributing to a reduction in the reconstruction error while convergence performance is boosted. The experimental outcome shows that the TPR-BBGAN achieves a 12–20% enhancement in data confidentiality, a 6–17% enhancement in data integrity, a 30–46% reduction in bit-error rate, and a 6–20% increase in the Peak Signal-to-Noise Ratio (PSNR) in contrast to existing models. Full article

This work presents a novel high-speed random bit generation approach based on chaotic optical signals combined with a pseudo-random pulse amplitude modulation (PAM) sequence. Chaotic dynamics generated by a laser diode under optical feedback provide the physical entropy source. At the same time, the PAM signal is added as an amplitude-level transformation to enhance the statistical distribution of the digitized signal. Unlike conventional post-processing techniques such as least significant bit (LSB) extraction, which reduce the effective bit rate, the proposed method described in this article preserves the full 8-bit resolution of the analog-to-digital converter improving the distribution of amplitude levels. Experimental results show a significant improvement in compliance with the NIST SP 800-22 statistical test suite. The system operates at a sampling rate of 20 GSa/s, achieving a theoretical bit generation rate of 160 Gb/s. These results demonstrate that the proposed approach provides an alternative to conventional digital post-processing techniques while maintaining high throughput. Full article

Battery datasets, whether gathered experimentally or through simulation, are typically high-dimensional and complex, which complicates the direct interpretation of degradation behavior or anomaly detection. To overcome these limitations, this study introduces a framework that compresses battery signals into a low-dimensional representation using an autoencoder, enabling the extraction of informative features for state analysis. A central component of this work is the systematic comparison of latent representations obtained from two fundamentally different data sources: frequency-domain impedance data and time-domain voltage-current data. The close agreement of aging trajectories in both representations suggests that information traditionally derived from impedance analysis can also be captured directly from raw time-series signals. To better approximate real operating conditions, synthetic datasets are augmented with stochastic perturbations. In this context, latent spaces learned from idealized periodic inputs are contrasted with those derived from permuted and noise-contaminated signals. The resulting low-dimensional features are subsequently evaluated through a support vector machine with both linear and nonlinear kernel functions, allowing the categorization of battery states into fresh, aged and damaged conditions. The results demonstrate that the progression of battery degradation is consistently reflected in the latent space, independent of the input domain or signal quality. This robustness indicates that the proposed approach can effectively capture essential aging characteristics even under non-ideal conditions. Consequently, this framework provides a basis for developing advanced diagnostic strategies, including the design of pseudo-random excitation profiles for improved battery state assessment and optimized operational control. Full article

This paper proposes a novel four-dimensional strongly dissipative nonlinearly coupled hyperchaotic system, investigates its dynamical characteristics, and demonstrates its applicability through Deoxyribonucleic Acid (DNA)-encoded RGB image encryption. First, a four-dimensional nonlinearly coupled hyperchaotic system with strong dissipativity is constructed. Nonlinear dynamics analysis methods, including phase trajectory diagrams, Lyapunov exponent spectra, and bifurcation diagrams, are employed to thoroughly reveal the system’s complex dynamical evolution mechanisms. The analysis indicates that the system not only possesses a wide range of chaotic parameters but also exhibits rich phenomena of multiple coexisting attractors, demonstrating a high degree of multistability. This characteristic offers potential advantages for image encryption, as it increases the diversity of dynamical behaviors and enhances sensitivity to initial conditions. The physical realizability of the chaotic behavior is further verified through an analog circuit implementation. Consequently, the system supports the design of encryption algorithms with larger key spaces, stronger resistance to phase space reconstruction, and improved pseudo-randomness, making it particularly suitable for applications with extremely high security requirements. Subsequently, leveraging the highly random chaotic sequences generated by this system, combined with various DNA coding rules and operations, the RGB image components are scrambled and diffused for encryption. Security analysis demonstrates that the algorithm effectively passes examinations across multiple dimensions, including histogram analysis, information entropy, adjacent pixel correlation, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), and The Peak Signal-to-noise Ratio (PSNR). It achieves favorable encryption results, significantly enhances image resistance against attacks, and provides a reliable technical solution for the secure transmission of remote sensing and military images. Full article

Swim bladders in some teleost fish can act as gas-filled cavities that oscillate under acoustic pressure and transfer the sound energy to the inner ears. Quantifying the resonance frequency and damping of these oscillations is useful for linking swim bladder mechanics to hearing-related and behavioural questions, but many established direct-measure approaches have relied on open-water deployments and careful avoidance of boundary reflections, making experiments logistically demanding and difficult to reproduce (e.g., requiring deep-water sites, careful control of surface/boundary reflections, and complex deployment geometries). This study presents a compact laboratory methodology for estimating swim bladder resonance properties using a closed, fully water-filled, stainless-steel impedance tube. Broadband pseudorandom excitation is applied via an end-plate shaker, and the acoustic response of the system is recorded using wall-mounted hydrophones. Resonance peaks are identified using power spectral estimates of recorded signals, allowing resonance frequency and quality factor to be extracted from the peak location and −3 dB bandwidth. The approach is first established using inflated latex balloons as surrogate encapsulated gas cavities, providing a controlled benchmark for repeatability and interpretation. It is then applied to recently euthanised brown trout (Salmo trutta), where clear resonance features attributable to the swim bladder are observed and show systematic variation with body size. A coupled finite element model reproduces the principal resonance behaviour under the experimental loading and supports interpretation of the measured peaks as swim bladder resonance. The results provide a validated foundation for subsequent non-invasive measurements on live, free-swimming fish, as well as for future applications where swim bladder condition may be relevant to management or conservation. Full article

In this paper, a metasurface-enabled dual-channel optical image authentication based on polarization multiplexing is proposed. During encryption, authentication phases corresponding to dual-channel plaintext images are firstly calculated by using a sparse-constraint-driven authentication-holography (SCDAH) algorithm. Then, target transmission phase and geometric phase of metasurface to be designed are obtained accordingly by the composite phase modulation (CPM) principle. Next, the nanopillar-type metasurface unit is performed with parameter scanning to establish the transmission and geometric phase databases. Finally, the structural parameters of each nanopillar are determined on a pixel-by-pixel basis to complete the construction of polarization-multiplexing authentication metasurface (PMAM). During authentication, the PMAM are respectively illuminated by the left-handed circularly polarized (LCP) and right-handed circularly polarized (RCP) light to obtain pseudo-random images produced by far-field diffraction, and then the nonlinear correlation distribution between diffraction image and corresponding channel plaintext image is calculated, and the final authentication result of each channel is determined based on whether the signal-to-noise ratio of the nonlinear correlation distribution meets the standard. In fact, a new physical-characteristic-driven dual-channel optical image authentication technology is formed, where double identities of the user holding this PMAM can be simultaneously verified, breaking through the rigid constraint of conventional single metasurface-to-single image, meanwhile improving the capacity and efficiency for authentication metasurface from the perspective of physical mechanism. Numerical simulations are performed to demonstrate the feasibility of the proposed method, and the simulation results prove that the proposed method exhibits high feasibility and security as well as strong robustness against cropping attack, showing a promising application potential in the field of identity recognition and authentication. Full article

This paper presents a subtractive-dither-assisted background calibration technique for a 2 GS/s 12 bit pipelined analog-to-digital converter (ADC). A large 7 bit pseudo-random dither is injected in both the flash and the multiplying digital-to-analog converter (MDAC) to decorrelate the differential nonlinearity (DNL) errors caused by the inherent quantization error nonlinearity, capacitor mismatching, and inter-stage amplifier nonlinearity from the input signal. Designed in a 28 nm CMOS process with a 1 V supply, post-layout simulations demonstrate a 10.2 dB improvement in spurious-free dynamic range (SFDR), from 73.8 dB to 84.4 dB, with dithering enabled under a close-to-Nyquist input frequency of 985 MHz. Although the injected dither cannot be completely removed in the digital domain, the proposed ADC exhibits only a 0.5 dB degradation in signal-to-noise-and-distortion ratio (SNDR) for full-scale input, achieving an SNDR of 62.3 dB and an effective number of bits (ENOB) of 10.1 bits. Dithering also improves static performance, with DNL and INL optimized to +0.54/−0.53 LSBs and +0.85/−0.88 LSBs, respectively. Moreover, the proposed dither-based calibration technique introduces an additional power consumption of less than 2 mW. Full article

High-speed railway signaling equipment constitutes safety-critical infrastructure, wherein hardware failures may directly compromise operational safety. During the hardware prototyping and verification stage, structural testing is essential to detect latent faults in digital logic circuits and to ensure compliance with stringent safety integrity requirements. However, conventional test generation methods often suffer from long generation times and excessive test vector volume. To address these challenges, this study proposes a whale optimization-based dynamic compression Automatic Test-Pattern Generation (ATPG) algorithm. The proposed method integrates a discrete whale optimization algorithm (WOA) with a deterministic PODEM framework to dynamically compress generated test vectors. Additionally, a multi-path-sensitized PODEM enhanced with desensitization techniques is introduced to reduce backtracking and improve search efficiency. The proposed algorithm has been applied to the computer interlocking golden model netlist for testing purposes, achieving an impressive fault coverage rate of 100%. Test results from the ISCAS-85 standard circuit indicate that our approach significantly reduces both the length of the vector set and the time required for test generation when compared to traditional PODEMs without vector compression and pseudo-random combined PODEM vector generation methods. This advancement effectively enhances overall vector generation efficiency while maintaining comprehensive fault coverage. Full article

Dynamical systems with chaotic attractors are an interesting topic not only for their complex behavior but also due to their potential applications. Along with the chaos, systems can also present interesting features such as multistability, global basin of attractions, entangled basins of attraction, etc. The existence of chaotic systems with multistable hidden attractors increases complexity but also the number of potential applications. Several systems with hidden attractors have already been found by numerical search; however, it is usually not possible to substantially modify their equations or attractor geometry. In this study, an approach to generate multistable systems with a class of hidden attractors is proposed. The approach allows for the control of the amplitude and frequency of the chaotic signals of the different attractors as well as their location in the space by preserving a simple matrix form in the vector field. Particular cases with mono-stability and multistability are shown. Also, chaotic signals obtained through the approach are used in a pseudorandom number generator to obtain binary sequences which are tested under the Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications provided by the National Institute of Standards and Technology (NIST). Full article

The high peak-to-average power ratio (PAPR) in classical high-speed digital data transmission systems with orthogonal frequency division multiplexing (OFDM) limits energy efficiency and communication range. This paper proposes a method for randomizing OFDM signals via frequency coding using synthesized pseudorandom sequences with improved autocorrelation properties, obtained through machine learning, to minimize PAPR in complex, non-stationary hydroacoustic channels for communicating with underwater robotic systems. A neural network architecture was developed and trained to generate codes of up to 150 elements long based on an analysis of patterns in previously found best short sequences. The obtained class of OFDM signals does not require regular and accurate estimation of channel parameters while remaining resistant to various types of impulse noise, Doppler shifts, and significant multipath interference typical of the underwater environment. The attained spectral efficiency values (up to 0.5 bits/s/Hz) are relatively high for existing hydroacoustic communication systems. It has been shown that the peak power of such multi-frequency information transmission systems can be effectively reduced by an average of 5–10 dB, which allows for an increase in the communication range compared to classical OFDM methods in non-stationary hydrological conditions at acceptable bit error rates (from 10⁻² to 10⁻³ and less). The effectiveness of the proposed methods of randomization with synthesized codes and frequency coding for OFDM signals was confirmed by field experiments at sea on the shelf, over distances of up to 4.2 km, with sea waves of up to 2–3 Beaufort units and mutual movement of the transmitter and receiver. Full article

Speaker anonymization effectively conceals speaker identity in speech signals to protect privacy. To address issues in existing anonymization systems, including reduced voice distinguishability, limited anonymized voices, reliance on an external speaker pool, and vulnerability to privacy leakage against strong attackers, a novel distinguishability-driven voice generation for speaker anonymization via random projection and the Gaussian Mixture Model (GMM) is proposed. This method first applies the random projection to lower the dimensionality of the X-vectors from an external speaker pool, and then constructs a GMM in the reduced dimensional space to fit the generative model. By sampling from this generative model, anonymous speaker identity representations are generated, ultimately synthesizing anonymized speech that maintains both intelligibility and distinguishability. To ensure the anonymized speech remains sufficiently distinguishable from the original and prevents excessive similarity, a cosine similarity check is implemented between the original X-vector and pseudo-X-vector. Experimental results on the VoicePrivacy Challenge datasets demonstrate that the proposed method not only effectively protects speaker privacy across different attack scenarios but also preserves speech content integrity while significantly enhancing speaker distinguishability between original speakers and their corresponding pseudo-speakers, as well as among different pseudo-speakers. Full article

While tremendous progress has been made towards achieving highly efficient and practical Private Set Intersection (PSI) protocols during the last decade, the development of post-quantum PSI is still far from satisfactory. Existing post-quantum PSI protocols encounter a dilemma: while those based on fully homomorphic encryption (FHE) achieve low online communication, they suffer from significant online computation; conversely, protocols based on post-quantum Oblivious Pseudorandom Functions (OPRFs) exhibit excellent online computational performance but incur substantially high online communication. To overcome this dilemma, we present a lattice-based PSI protocol that achieves optimal online performance in both communication and computation. Our solution introduces two core innovations: a robust signal comparison algorithm based on RLWE key exchange, which determines the intersection through signal consistency rather than direct shared key comparison, and an optimized Oblivious Key–Value Stores (OKVS) implementation featuring a composite key–value mapping for efficient handling of high-dimensional RLWE polynomials. We implement the protocol and conduct extensive benchmarks in both symmetric and asymmetric set-size settings. The results show that our construction achieves the lowest online overhead in both computation and communication among all tests. For example, with asymmetric set sizes $(2^{12},11041)$, the online phase requires only $0.132$ s, yielding $19\times$ and $282\times$ improvements over FHE-based (CCS’21) and OPRF-based (EUROCRYPT’25) protocols, respectively. Even at $(2^{24},11041)$, our online communication time is only 0.201 s, which is $226\times$ and $184\times$ that of FHE-based and OPRF-based PSI, respectively. Additionally, our online communication overhead is the lowest in all tests; however, this comes at the cost of heavy offline communication overhead for very large set sizes, revealing a clear trade-off between pre-computation and online efficiency. This work addresses a critical gap in post-quantum PSI by delivering a protocol that achieves balanced online communication and computational overhead, thereby enabling broader practical deployment. Full article

We experimentally demonstrate an 80 Gbit/s Nyquist-dense wavelength division multiplexed (Nyquist-DWDM) transmission system operating in a simulated atmospheric turbulence channel. The system utilizes eight wavelength-tunable lasers with 100 GHz spacing, modulated by cascaded Mach–Zehnder modulators, to generate phase-locked Nyquist pulse sequences with a 10 GHz repetition rate and a temporal width of 66.7 ps. Each channel is synchronously modulated with a 10 Gbit/s pseudo-random bit sequence (PRBS) and transmitted through controlled weak turbulence conditions generated by a temperature-gradient convection chamber. Experimental measurements reveal that, as the turbulence intensity increases from $C_n^2=1.01\times {10}^{-16}$ to $5.71\times {10}^{-16} {\mathrm{m}}^{-2/3}$, the signal-to-noise ratio (SNR) of the edge channel (C29) and central channel (C33) decreases by approximately 6.5 dB while maintaining stable Nyquist waveform profiles and inter-channel orthogonality. At a forward-error-correction (FEC) threshold of $3.8\times {10}^{-3}$, the minimum receiver sensitivity is −17.66 dBm, corresponding to power penalties below 5 dB relative to the back-to-back condition. The consistent SNR difference (<2 dB) between adjacent channels confirms uniform power distribution and low inter-channel crosstalk under turbulence. These findings verify that Nyquist pulse shaping substantially mitigates phase distortion and scintillation effects, demonstrating the feasibility of high-capacity DWDM free-space optical (FSO) systems with enhanced spectral efficiency and turbulence resilience. The proposed configuration provides a scalable foundation for future multi-wavelength FSO links and hybrid fiber-wireless optical networks. Full article