arXiv subjects

Poonam Yadav

Publications and source records attributed to Poonam Yadav.

At least 19 recordsLinked to original sources

arXiv2026

Toward a Unified Security and Privacy Framework for AI-Native 6G Networks

Sixth Generation (6G) communication networks are expected to evolve into AI-native, highly autonomous ecosystems that integrate communication, computing, sensing, and artificial intelligence. While these capabilities enable unprecedented connectivity and intelligent services, they also create a highly heterogeneous security and privacy landscape that cannot be addressed through isolated, technology-specific solutions. This paper presents a comprehensive survey of security and privacy in AI-native 6G networks from a cross-layer perspective. We first examine the fragmentation of existing security and privacy approaches across emerging technologies, network architectures, AI systems, and standardization efforts, motivating the need for a unified security and privacy framework. Building upon this framework, we develop a cross-layer threat taxonomy encompassing infrastructure, network and architectural, AI, privacy, and security management domains, and analyze representative threats across key AI-native 6G technologies. Furthermore, we map these threats to corresponding cross-layer countermeasures, including standards harmonization as a security function, and identify critical research gaps and future priorities for secure, interoperable, and trustworthy AI-native 6G ecosystems. Finally, we discuss future research directions toward realizing secure, privacy-preserving, resilient, and globally interoperable 6G networks. This survey provides researchers, practitioners, and standardization communities with a holistic foundation for the design, evaluation, and deployment of trustworthy AI-native 6G systems.

cs.CR↗

arXiv2026

Conditional spinodal decomposition in Li-Mg anodes for lithium metal batteries

The development of batteries with high energy density, short charging times and use of sustainable materials is critical for decarbonization. Magnesium (Mg)-based anodes for lithium (Li) metal batteries promote homogeneous Li plating, thereby avoiding the formation of Li dendrites that cause short circuits and battery failure. However, microstructural modifications induced by Li-alloying and their influence on battery operation remain elusive. Here, we unveil the previously unknown formation of an ordered B2 phase, which creates a conditional spinodal decomposition with the \b{eta}-body-centered cubic phase. Chemical fluctuations characteristic of spinodal decomposition give rise to uniformly dispersed Li-rich \b{eta}-BCC and Li-poor B2 continuous interconnected phases, with the former providing a fast diffusion pathway for Li diffusion towards the anode, hence decreasing the propensity for dendrite formation at elevated current density. This is achieved using Earth-abundant and inexpensive Mg.

cond-mat.mtrl-sci↗

arXiv2026

Design Insights into Partition Placement and Routing for DNN Inference in Multi-Hop Edge Networks

Partitioned DNN inference is a promising approach for latency-sensitive intelligent services in edge networks, since it allows different parts of a model to be executed across end devices, edge servers, and the cloud. However, in a multi-hop edge network, partition placement and inference traffic routing are inherently coupled: raw inputs, intermediate features, and final outputs may have very different sizes, while candidate nodes also differ in computation capability. In addition, both communication and computation delays can become congestion-dependent under load. In this paper, we study joint partition placement and routing for fixed-partition DNN inference over heterogeneous multi-hop edge networks. We consider a small number of DNN partitions, each placed at exactly one node without replication, and formulate a congestion-aware mixed discrete--continuous optimization problem that captures both routing and execution costs. To solve it, we develop a practical alternating framework that couples partition placement with congestion-aware forwarding updates. Through numerical evaluation on hierarchical, regular, synthetic irregular, and real backbone-inspired topologies, we show that split flexibility is particularly important in IoT--edge--cloud settings, while congestion-aware refinement becomes increasingly beneficial as the offered load grows. We further illustrate how the preferred operating point depends on the communication--computation tradeoff.

cs.NI↗

arXiv2026

Handling Interoperability Issues in 6G ORAN: Lessons Learned from Research Lab-based Integrations

As 6G networks continue to evolve, the Open Radio Access Network (ORAN) framework is gaining prominence for its promise of network flexibility, vendor-neutral architecture, and enhanced service delivery. However, achieving true interoperability across diverse hardware and software components from multiple vendors remains a critical challenge. This research focuses on identifying and addressing interoperability issues within 6G ORAN environments, leveraging insights from research lab-based integrations. By systematically analysing lab-based case studies, the study aims to uncover the root causes of integration failures, propose solutions to ensure smooth multi-vendor compatibility, and establish a set of best practices for future deployments. This work will contribute to developing robust guidelines for 6G ORAN ecosystems, accelerating seamless and scalable deployments in real-world networks.

cs.NI↗

arXiv2026

Interpretable Attention-Based Multi-Agent PPO for Latency Spike Resolution in 6G RAN Slicing

Sixth-generation (6G) radio access networks (RANs) must enforce strict service-level agreements (SLAs) for heterogeneous slices, yet sudden latency spikes remain difficult to diagnose and resolve with conventional deep reinforcement learning (DRL) or explainable RL (XRL). We propose \emph{Attention-Enhanced Multi-Agent Proximal Policy Optimization (AE-MAPPO)}, which integrates six specialized attention mechanisms into multi-agent slice control and surfaces them as zero-cost, faithful explanations. The framework operates across O-RAN timescales with a three-phase strategy: predictive, reactive, and inter-slice optimization. A URLLC case study shows AE-MAPPO resolves a latency spike in $18$ms, restores latency to $0.98$ms with $99.9999\%$ reliability, and reduces troubleshooting time by $93\%$ while maintaining eMBB and mMTC continuity. These results confirm AE-MAPPO's ability to combine SLA compliance with inherent interpretability, enabling trustworthy and real-time automation for 6G RAN slicing.

eess.SY↗

arXiv2025

Magnetic structure evolution and magnetoelastic coupling across the spin reorientation transition in TmCrO3

We present a comprehensive study of the magnetic structure evolution across the spin reorientation transition in orthorhombic (Pnma) TmCrO3. Magnetic susceptibility reveals canted antiferromagnetic (CAFM) ordering at T_N = 125 K, two compensation points (T_comp1 and T_comp2), followed by magnetization reversal with a magnetic susceptibility minimum between T_comp1 and T_comp2. Heat capacity shows a sharp lambda-type transition at T_N, associated with the long-range antiferromagnetic ordering of Cr, followed by a broad feature near 9 K. Neutron powder diffraction (NPD) establishes the Pn'm'a (Gamma2) magnetic structure below T_N. A gradual change in magnetic structure occurs during the spin-reorientation (SRO) transition below 30 K, where the magnetic symmetry transforms from Pn'm'a (Gamma2) to Pn'ma' (Gamma4) phase. However, below the SRO, neither Gamma2 nor Gamma4 alone adequately fit the intensity of magnetic reflections. A satisfactory refinement is achieved using the monoclinic subgroup P21'/c', derived from a combination of Gamma2 and Gamma4. The gradual SRO of Tm and Cr moments across the compensation regime is consistent with the magnetic symmetry P21'/c'. Furthermore, the ordered moments of Cr and Tm in TmCrO3 exhibit a complex, non-monotonic temperature dependence, with the Tm sublattice driving the spin-reorientation transition near the compensation point. Anomalies in the lattice parameters reveal strong magnetoelastic coupling, linking structural distortions to the SRO.

cond-mat.str-el↗

arXiv2025

Controlled growth of polar altermagnets via chemical vapor transport

Altermagnetic properties have been recently proposed in polar magnetic oxides, M$_{2}$Mo$_{3}$O$_{8}$ (M = Mn, Fe, Co, Ni), where improved characteristics of stronger magnetoelectric coupling and higher magnetic transition temperatures were observed. Thus, understanding their microscopic origins is of fundamental and technological importance. However, the difficulty in growing large single crystals hinders detailed experimental studies. Here, we report the successful growth of large single crystals of the pyroelectric antiferromagnet using two representative compounds, Fe$_{2}$Mo$_{3}$O$_{8}$ and NiZnMo$_{3}$O$_{8}$. Growth was optimized using various parameters, finding the transport agent density as a primary factor, which depends strongly on the position of the pellet, the starting powder form, and the volume of the ampule. We demonstrated a controlled growth method by manipulating the convection and diffusion kinetics. High-quality crystals were characterized by using single-crystal X-ray diffraction, Laue diffraction, magnetic susceptibility, and Raman spectroscopy. Manipulation of magnetic properties through nonmagnetic Zn doping was shown in NiZnMo$_{3}$O$_{8}$. Our results enable the detailed investigation and manipulation of their unconventional altermagnetic and multiferroic properties. This study provides crucial insight into the controlled growth of other functional quantum materials.

cond-mat.mtrl-sci↗

arXiv2025

Formal Verification of Physical Layer Security Protocols for Next-Generation Communication Networks (extended version)

Formal verification is crucial for ensuring the robustness of security protocols against adversarial attacks. The Needham-Schroeder protocol, a foundational authentication mechanism, has been extensively studied, including its integration with Physical Layer Security (PLS) techniques such as watermarking and jamming. Recent research has used ProVerif to verify these mechanisms in terms of secrecy. However, the ProVerif-based approach limits the ability to improve understanding of security beyond verification results. To overcome these limitations, we re-model the same protocol using an Isabelle formalism that generates sound animation, enabling interactive and automated formal verification of security protocols. Our modelling and verification framework is generic and highly configurable, supporting both cryptography and PLS. For the same protocol, we have conducted a comprehensive analysis (secrecy and authenticity in four different eavesdropper locations under both passive and active attacks) using our new web interface. Our findings not only successfully reproduce and reinforce previous results on secrecy but also reveal an uncommon but expected outcome: authenticity is preserved across all examined scenarios, even in cases where secrecy is compromised. We have proposed a PLS-based Diffie-Hellman protocol that integrates watermarking and jamming, and our analysis shows that it is secure for deriving a session key with required authentication. These highlight the advantages of our novel approach, demonstrating its robustness in formally verifying security properties beyond conventional methods.

cs.CR↗

arXiv2025

Gain-Assisted and Dynamically Controlled Optical Bistability for Quantum Logic Gate Applications

The propagation of a probe field in an N-type four level cold atomic system is investigated under the influence of multiple coherent fields. Coherent control of quantum interference enables switching of the probe field between transparency and gain regimes. Subsequent analysis focuses on how the introduction of gain in the probe transition lowers the threshold for optical bistability, thereby enhancing the nonlinear response of the system at reduced input intensities. A detailed analysis of optical bistability is presented, focusing on its threshold, stability, and switching efficiency as functions of field strengths and detunings. Structured light beams, specifically Laguerre Gaussian modes carrying orbital angular momentum, are employed to tailor the bistable characteristics. The impact of Orbital angular momentum through the topological charge and azimuthal phase is shown to significantly influence the bistable behavior. Based on these features, a theoretical scheme is proposed to realize a Controlled-NOT gate via dynamic modulation of bistability. These results highlight the potential of integrating nonlinear optical effects with structured light in cold atomic systems for implementing scalable quantum logic and advancing photonic information processing.

quant-ph↗

arXiv2025

Structural Inhomogeneities and Suppressed Magneto-Structural Coupling in Mn-Substituted GeCo2O4

A comprehensive study of Ge1-xMnxCo2O4 (GMCO) system was conducted using neutron powder diffraction (NPD), x-ray diffraction (XRD), Scanning electron microscopy, magnetometry, and heat capacity measurements. Comparative analysis with GeCo2O4 (GCO) highlights the influence of Mn substitution on the crystal and magnetic structure at low temperature. Surprisingly, phase separation is observed in GMCO with a targeted nominal composition of Ge0.5Mn0.5Co2O4. SEM/EDX analysis reveals that the sample predominantly consists of a Mn-rich primary phase with approximate stoichiometry Mn0.74Ge0.18Co2O4, along with a minor Ge-rich secondary phase of composition Ge0.91Mn0.19Co2O4. Although both GCO and GMCO crystallize in cubic symmetry at room temperature, a substantial difference in low-temperature structural properties has been observed. Magnetic and heat capacity data indicate ferrimagnetic ordering in the Mn-rich phase near TC = 108 K, while the Ge-rich phase exhibits antiferromagnetic order at TN = 22 K in GMCO. Analysis of heat capacity data reveals that the estimated magnetic entropy amounts to only 63% of the theoretical value expected in GMCO. A collinear ferrimagnetic arrangement is observed in the Mn rich phase below the magnetic ordering temperature, characterized by antiparallel spins of the Mn at A site and Co at B site along the c-direction. At 5 K, the refined magnetic moments are 2.31(3) for MnA and 1.82(3) uB for CoB in the Mn rich ferrimagnetic phase. The magnetic structure at 5 K in the Ge rich secondary phase is identical to the antiferromagnetic structure of the parent compound GeCo2O4. The refined value of the CoB moment in this phase at 5 K is 2.53(3) uB.

cond-mat.mtrl-sci↗

arXiv2025

Continuous-Variable Quantum Key Distribution with Composable Security and Tight Error Correction Bound towards Constrained-Device Implementations

Constrained devices, such as smart sensors, wearable devices, and Internet of Things nodes, are increasingly prevalent in society and rely on secure communications to function properly. These devices often operate autonomously, exchanging sensitive data or commands over short distances, such as within a room, house, or warehouse. In this context, continuous-variable quantum key distribution (CV-QKD) offers the highest secure key rate and the greatest versatility for integration into existing infrastructure. A key challenge in this setting, where devices have limited storage and processing capacity, is obtaining a realistic and tight estimate of the CV-QKD secure key rate within a composable security framework, with error correction (EC) consuming most of the storage and computational power. To address this, we focus on low-density parity-check (LDPC) codes with non-binary alphabets, which optimise mutual information and are particularly suited for short-distance communications. We develop a security framework to derive finite-size secret keys near the optimal EC leakage limit and model the related memory requirements for the encoding process in one-way error correction. This analysis facilitates the practical deployment of CV-QKD, particularly in constrained devices with limited storage and computational resources.

quant-ph↗

arXiv2024

Towards Achieving Energy Efficiency and Service Availability in O-RAN via Formal Verification

As Open Radio Access Networks (O-RAN) continue to expand, AI-driven applications (xApps) are increasingly being deployed enhance network management. However, developing xApps without formal verification risks introducing logical inconsistencies, particularly in balancing energy efficiency and service availability. In this paper, we argue that prior to their development, the formal analysis of xApp models should be a critical early step in the O-RAN design process. Using the PRISM model checker, we demonstrate how our results provide realistic insights into the thresholds between energy efficiency and service availability. While our models are simplified, the findings highlight how AI-informed decisions can enable more effective cell-switching policies. We position formal verification as an essential practice for future xApp development, avoiding fallacies in real-world applications and ensuring networks operate efficiently.

cs.NI↗

arXiv2024

User-Guided Verification of Security Protocols via Sound Animation

Current formal verification of security protocols relies on specialized researchers and complex tools, inaccessible to protocol designers who informally evaluate their work with emulators. This paper addresses this gap by embedding symbolic analysis into the design process. Our approach implements the Dolev-Yao attack model using a variant of CSP based on Interaction Trees (ITrees) to compile protocols into animators -- executable programs that designers can use for debugging and inspection. To guarantee the soundness of our compilation, we mechanised our approach in the theorem prover Isabelle/HOL. As traditionally done with symbolic tools, we refer to the Diffie-Hellman key exchange and the Needham-Schroeder public-key protocol (and Lowe's patched variant). We demonstrate how our animator can easily reveal the mechanics of attacks and verify corrections. This work facilitates security integration at the design level and supports further security property analysis and software-engineered integrations.

cs.CR↗

arXiv2024

Towards Resilient 6G O-RAN: An Energy-Efficient URLLC Resource Allocation Framework

The demands of ultra-reliable low-latency communication (URLLC) in ``NextG" cellular networks necessitate innovative approaches for efficient resource utilisation. The current literature on 6G O-RAN primarily addresses improved mobile broadband (eMBB) performance or URLLC latency optimisation individually, often neglecting the intricate balance required to optimise both simultaneously under practical constraints. This paper addresses this gap by proposing a DRL-based resource allocation framework integrated with meta-learning to manage eMBB and URLLC services adaptively. Our approach efficiently allocates heterogeneous network resources, aiming to maximise energy efficiency (EE) while minimising URLLC latency, even under varying environmental conditions. We highlight the critical importance of accurately estimating the traffic distribution flow in the multi-connectivity (MC) scenario, as its uncertainty can significantly degrade EE. The proposed framework demonstrates superior adaptability across different path loss models, outperforming traditional methods and paving the way for more resilient and efficient 6G networks.

cs.NI↗

arXiv2024

Grain boundaries control lithiation of solid solution substrates in lithium metal batteries

The development of sustainable transportation and communication systems requires an increase in both energy density and capacity retention of Li-batteries. Using substrates forming a solid solution with body centered cubic Li enhances the cycle stability of anode-less batteries. However, it remains unclear how the substrate microstructure affects the lithiation behavior. Here, we deploy a correlative, near-atomic scale probing approach through combined ion- and electron-microscopy to examine the distribution of Li in Li-Ag diffusion couples as model system. We reveal that Li regions with over 93.8% at.% nucleate within Ag at random high angle grain boundaries, whereas grain interiors are not lithiated. We evidence the role of kinetics and mechanical constraint from the microstructure over equilibrium thermodynamics in dictating the lithiation process. The findings suggest that grain size and grain boundary character are critical to enhance the electrochemical performance of interlayers/electrodes, particularly for improving lithiation kinetics and hence reducing dendrite formation.

cond-mat.mtrl-sci↗

arXiv2024

Structural and Magnetic properties of Ge0.5Mn0.5Co2O4 using neutron diffraction

The structural and magnetic properties of Ge0.5Mn0.5Co2O4 (GMCO) have been investigated in detail utilizing neutron powder diffraction (NPD), x-ray diffraction (XRD), DC magnetometry, and heat capacity analysis and compared with GeCo2O4. Despite both compounds exhibiting a cubic structure at room temperature, a substantial difference on low temperature structural properties have been observed for GMCO, indicating the effect of Mn substitution on crystal structure. The magnetic and heat capacity data reveal a ferrimagnetic ordering around 108 K in GMCO. A minor secondary phase is confirmed which undergoes long range AFM ordering at further lower temperatures. This secondary phase remains undetected in XRD due to identical lattice parameters. Furthermore, the analysis of heat capacity data indicates a broadening of the high-temperature transition, attributing to the short-range correlation persisting up to higher temperatures. The estimated magnetic entropy amounts is 63% of the value expected for GMCO. The missing entropy is likely linked with the short-range magnetic correlations persisting well above the transition temperature. Cation distribution at the A and B sites has been estimated in GMCO using NPD. Magnetic structures are also confirmed in the main phase as well as in the secondary phase using NPD analysis. The high-temperature transition corresponds to the ferrimagnetic ordering of A and B site cations in the main phase. A collinear ferrimagnetic arrangement of A and B site spins aligned parallel to c axis is observed. The average values of A and B site moments in the ferrimagnetic phase at 5 K are 2.31(3) and 1.82(3)mB, respectively, with the temperature dependence of moments following the expected power law behavior. The low-temperature ordering is attributed to the antiferromagnetic ordering of B site ions associated with the secondary phase, something similar to GeCo2O4.

cond-mat.str-el↗

arXiv2024

Introducing v0.5 of the AI Safety Benchmark from MLCommons

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use case (an adult chatting to a general-purpose assistant in English), and a limited set of personas (i.e., typical users, malicious users, and vulnerable users). We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0.5 benchmark. We plan to release version 1.0 of the AI Safety Benchmark by the end of 2024. The v1.0 benchmark will provide meaningful insights into the safety of AI systems. However, the v0.5 benchmark should not be used to assess the safety of AI systems. We have sought to fully document the limitations, flaws, and challenges of v0.5. This release of v0.5 of the AI Safety Benchmark includes (1) a principled approach to specifying and constructing the benchmark, which comprises use cases, types of systems under test (SUTs), language and context, personas, tests, and test items; (2) a taxonomy of 13 hazard categories with definitions and subcategories; (3) tests for seven of the hazard categories, each comprising a unique set of test items, i.e., prompts. There are 43,090 test items in total, which we created with templates; (4) a grading system for AI systems against the benchmark; (5) an openly available platform, and downloadable tool, called ModelBench that can be used to evaluate the safety of AI systems on the benchmark; (6) an example evaluation report which benchmarks the performance of over a dozen openly available chat-tuned language models; (7) a test specification for the benchmark.

cs.CL↗

arXiv2024

Data Authorisation and Validation in Autonomous Vehicles: A Critical Review

Autonomous systems are becoming increasingly prevalent in new vehicles. Due to their environmental friendliness and their remarkable capability to significantly enhance road safety, these vehicles have gained widespread recognition and acceptance in recent years. Automated Driving Systems (ADS) are intricate systems that incorporate a multitude of sensors and actuators to interact with the environment autonomously, pervasively, and interactively. Consequently, numerous studies are currently underway to keep abreast of these rapid developments. This paper aims to provide a comprehensive overview of recent advancements in ADS technologies. It provides in-depth insights into the detailed information about how data and information flow in the distributed system, including autonomous vehicles and other various supporting services and entities. Data validation and system requirements are emphasised, such as security, privacy, scalability, and data ownership, in accordance with regulatory standards. Finally, several current research directions in the AVs field will be discussed.

cs.RO↗