Searcharxiv⌕ Search

arXiv subjects

Poonam Yadav

Publications and source records attributed to Poonam Yadav.

At least 37 records · Page 2Linked to original sources

Partial molecular orbitals in face-sharing 3$d$ manganese trimer: Comparative studies on Ba$_{4}$TaMn$_{3}$O$_{12}$ and Ba$_{4}$NbMn$_{3}$O$_{12}$

We present a molecular orbital candidate Ba$_{4}$TaMn$_{3}$O$_{12}$ with a face-sharing octahedra trimer, by comparing it with a related compound Ba$_{4}$NbMn$_{3}$O$_{12}$. The synthesis of the polycrystalline powder is optimized by suppressing the secondary impurity phase via x-ray diffraction. Magnetic susceptibility measurements on the optimized samples reveal a weak magnetic hysteresis with magnetic transitions consistent with heat capacity results. The effective magnetic moments from susceptibility indicate a strongly coupled $S=2$ antiferromagnetic trimer at around room temperature, whereas the estimated magnetic entropy from heat capacity suggests the localized $S=3/2$ timer. These results can be explainable by a partial molecular orbital state, in which three $t_{2g}$ electrons are localized in each Mn ion and one $e_{g}$ electron is delocalized over two-end Mn ions of the trimer based on density functional theory calculations. This unconventional 3$d$ orbital state is comprehended as a consequence of competition between the hybrid interatomic orbitals within the Mn trimer and the local moment formation by on-site Coulomb correlations.

cond-mat.str-el↗

Unveiling Internet Censorship: Analysing the Impact of Nation States' Content Control Efforts on Internet Architecture and Routing Patterns

Heightened interest from nation states to perform content censorship make it evermore critical to identify the impact of censorship efforts on the Internet. We undertake a study of Internet architecture, capturing the state of Internet topology with greater completeness than existing state-of-the-art. We describe our methodology for this, including the tooling we create to collect and process data from a wide range of sources. We analyse this data to find key patterns in nation states with higher censorship, discovering a funnelling effect wherein higher Internet censorship effort is reflected in a constraining effect on a state's Internet routing architecture. However, there are a small number of nation states that do not follow this trend, for which we provide an analysis and explanation, demonstrating a relationship between geographical factors in addition to geopolitics. In summary, our work provides a deeper understanding of how these censorship measures impact the overall functioning and dynamics of the Internet.

cs.NI↗

Noncollinear magnetic order, in-plane anisotropy, and magnetoelectric coupling in a pyroelectric honeycomb antiferromagnet Ni$_{2}$Mo$_{3}$O$_{8}$

Ni$_{2}$Mo$_{3}$O$_{8}$ is a pyroelectric honeycomb antiferromagnet exhibiting peculiar changes of its electric polarization at magnetic transitions. Ni$_{2}$Mo$_{3}$O$_{8}$ stands out from the isostructural magnetic compounds, showing an anomalously low magnetic transition temperature and unique magnetic anisotropy. We determine the magnetic structure of Ni$_{2}$Mo$_{3}$O$_{8}$ utilizing high-resolution powder and single-crystal neutron diffraction. A noncollinear stripy antiferromagnetic order is found in the honeycomb planes. The magnetic space group is \textit{P$_C$na}2$_1$. The in-plane magnetic connection is of the stripy type both for the $ab$-plane and the $c$-axis spin components. This is a simpler connection than the one proposed previously. The ferromagnetic interlayer order of the $c$-axis spin components in our model is also distinct. The magnetic anisotropy of Ni$_{2}$Mo$_{3}$O$_{8}$ is characterized by orientation-dependent magnetic susceptibility measurements on a single crystal, consistent with neutron diffraction analysis. The local magnetoelectric tensor analysis using our magnetic models provides new insights into its magnetoelectric coupling and polarization. Thus, our results deliver essential information for understanding both the unusual magnetoelectric properties of Ni$_{2}$Mo$_{3}$O$_{8}$ and the prospects for observation of exotic nonreciprocal, Hall, and magnonic effects characteristic to this compound family.

cond-mat.str-el↗

VINCY: A Smart-contract based Data Integrity and Validation Tooling for Automated Vehicle Incident Investigation

Automated Driving Systems (ADSs) are being manufactured at an accelerated rate, leading to improvements in traffic safety, reduced energy consumption, pollution, and congestion. ADS relies on various data streams from onboard sensors, external road infrastructure, and other vehicles to make driving decisions. For effective traffic accident reconstruction, investigators must produce, collect, store, and access real-time data. To ensure meaningful investigation, the data used by investigators must be accurate and maintain its integrity. In this paper, we propose a smart-contract based data integrity and validation tool for automated vehicle incident investigation during road trials, considering uncertainties in a real-world environment.

cs.NI↗

On the Effective throughput of Shadowed Beaulieu-Xie fading channel

Given the imperative for advanced wireless networks in the next generation and the rise of real-time applications within wireless communication, there is a notable focus on investigating data rate performance across various fading scenarios. This research delved into analyzing the effective throughput of the shadowed Beaulieu-Xie (SBX) composite fading channel using the PDF-based approach. To get the simplified relationship between the performance parameter and channel parameters, the low-SNR and the high-SNR approximation of the effective rate are also provided. The proposed formulations are evaluated for different values of system parameters to study their impact on the effective throughput. Also, the impact of the delay parameter on the EC is investigated. Monte-Carlo simulations are used to verify the facticity of the deduced equations.

cs.IT↗

Mitigating IoT Botnet DDos Attacks through MUD and eBPF based Traffic Filtering

As the prevalence of Internet-of-Things (IoT) devices becomes more and more dominant, so too do the associated management and security challenges. One such challenge is the exploitation of vulnerable devices for recruitment into botnets, which can be used to carry out Distributed Denial-of-Service (DDoS) attacks. The recent Manufacturer Usage Description (MUD) standard has been proposed as a way to mitigate this problem, by allowing manufacturers to define communication patterns that are permitted for their IoT devices, with enforcement at the gateway home router. In this paper, we present a novel integrated system implementation that uses a MUD manager (osMUD) to parse an extended set of MUD rules, which also allow for rate-limiting of traffic and for setting appropriate thresholds. Additionally, we present two new backends for MUD rule enforcement, one based on eBPF and the other based on the Linux standard iptables. The reported evaluation results show that these techniques are feasible and effective in protecting against attacks and in terms of their impact on legitimate traffic and on the home gateway.

cs.NI↗

Challenges in the Design and Implementation of IoT Testbeds in Smart-Cities: A Systematic Review

Advancements in wireless communication and the increased accessibility to low-cost sensing and data processing IoT technologies have increased the research and development of urban monitoring systems. Most smart city research projects rely on deploying proprietary IoT testbeds for indoor and outdoor data collection. Such testbeds typically rely on a three-tier architecture composed of the Endpoint, the Edge, and the Cloud. Managing the system's operation whilst considering the security and privacy challenges that emerge, such as data privacy controls, network security, and security updates on the devices, is challenging. This work presents a systematic study of the challenges of developing, deploying and managing urban monitoring testbeds, as experienced in a series of urban monitoring research projects, followed by an analysis of the relevant literature. By identifying the challenges in the various projects and organising them under the V-model development lifecycle levels, we provide a reference guide for future projects. Understanding the challenges early on will facilitate current and future smart-cities IoT research projects to reduce implementation time and deliver secure and resilient testbeds.

cs.DC↗

Significance of anonymity and privacy in improving inclusivity and diversity in Higher Education Learning Environments

Interactions between lecturers and students are the key to learning in the higher education environment. In this paper, the investigation pursues two different contexts to understand these interactions and the impact of anonymity and privacy in different interactions in the Computer Science (CS) department. The first context "different interaction between a lecturer and students" is investigated using phenomenological research approach by interviewing lecturer in CS ($N_a = 5$). The second context "the significance of anonymity and privacy in interactions" is investigated using a quantitative and qualitative questionnaire-based research method using an online student questionnaire ($N_b = 53$). The study finds a large gap between students' perception of preferred communication methods and the use of the same communication method. From the second context study, it is evident that "anonymity and privacy" in online surveys and module evaluations are preferred by all student participants, thus supporting diversity and inclusivity.

cs.CY↗

Resilient Edge: Can we achieve Network Resiliency at the IoT Edge using LPWAN and WiFi?

Edge computing has gained attention in recent years due to the adoption of many Internet of Things (IoT) applications in domestic, industrial and wild settings. The resiliency and reliability requirements of these applications vary from non-critical (best delivery efforts) to safety-critical with time-bounded guarantees. The network connectivity of IoT edge devices remains the central critical component that needs to meet the time-bounded Quality of Service (QoS) and fault-tolerance guarantees of the applications. Therefore, in this work, we systematically investigate how to meet IoT applications mixed-criticality QoS requirements in multi-communication networks. We (i) present the network resiliency requirements of IoT applications by defining a system model (ii) analyse and evaluate the bandwidth, latency, throughput, maximum packet size of many state-of-the-art LPWAN technologies, such as Sigfox, LoRa, and LTE (CAT-M1/NB-IoT) and Wi-Fi, (iii) implement and evaluate an adaptive system Resilient Edge and Criticality-Aware Best Fit (CABF) resource allocation algorithm to meet the application resiliency requirements using Raspberry Pi 4 and Pycom FiPy development board having five multi-communication networks. We present our findings on how to achieve 100% of the best-effort high criticality level message delivery using multi-communication networks

cs.NI↗

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation

Medical AI has tremendous potential to advance healthcare by supporting the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving provider and patient experience. We argue that unlocking this potential requires a systematic way to measure the performance of medical AI models on large-scale heterogeneous data. To meet this need, we are building MedPerf, an open framework for benchmarking machine learning in the medical domain. MedPerf will enable federated evaluation in which models are securely distributed to different facilities for evaluation, thereby empowering healthcare organizations to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status, and our roadmap. We call for researchers and organizations to join us in creating the MedPerf open benchmarking platform.

cs.LG↗

Revisiting IoT Device Identification

Internet-of-Things (IoT) devices are known to be the source of many security problems, and as such, they would greatly benefit from automated management. This requires robustly identifying devices so that appropriate network security policies can be applied. We address this challenge by exploring how to accurately identify IoT devices based on their network behavior, while leveraging approaches previously proposed by other researchers. We compare the accuracy of four different previously proposed machine learning models (tree-based and neural network-based) for identifying IoT devices. We use packet trace data collected over a period of six months from a large IoT test-bed. We show that, while all models achieve high accuracy when evaluated on the same dataset as they were trained on, their accuracy degrades over time, when evaluated on data collected outside the training set. We show that on average the models' accuracy degrades after a couple of weeks by up to 40 percentage points (on average between 12 and 21 percentage points). We argue that, in order to keep the models' accuracy at a high level, these need to be continuously updated.

cs.CR↗

Benchmarking TinyML Systems: Challenges and Direction

Recent advancements in ultra-low-power machine learning (TinyML) hardware promises to unlock an entirely new class of smart applications. However, continued progress is limited by the lack of a widely accepted benchmark for these systems. Benchmarking allows us to measure and thereby systematically compare, evaluate, and improve the performance of systems and is therefore fundamental to a field reaching maturity. In this position paper, we present the current landscape of TinyML and discuss the challenges and direction towards developing a fair and useful hardware benchmark for TinyML workloads. Furthermore, we present our four benchmarks and discuss our selection methodology. Our viewpoints reflect the collective thoughts of the TinyMLPerf working group that is comprised of over 30 organizations.

cs.PF↗

The Case for Retraining of ML Models for IoT Device Identification at the Edge

Internet-of-Things (IoT) devices are known to be the source of many security problems, and as such they would greatly benefit from automated management. This requires robustly identifying devices so that appropriate network security policies can be applied. We address this challenge by exploring how to accurately identify IoT devices based on their network behavior, using resources available at the edge of the network. In this paper, we compare the accuracy of five different machine learning models (tree-based and neural network-based) for identifying IoT devices by using packet trace data from a large IoT test-bed, showing that all models need to be updated over time to avoid significant degradation in accuracy. In order to effectively update the models, we find that it is necessary to use data gathered from the deployment environment, e.g., the household. We therefore evaluate our approach using hardware resources and data sources representative of those that would be available at the edge of the network, such as in an IoT deployment. We show that updating neural network-based models at the edge is feasible, as they require low computational and memory resources and their structure is amenable to being updated. Our results show that it is possible to achieve device identification and categorization with over 80% and 90% accuracy respectively at the edge.

cs.NI↗

Position paper: A systematic framework for categorising IoT device fingerprinting mechanisms

The popularity of the Internet of Things (IoT) devices makes it increasingly important to be able to fingerprint them, for example in order to detect if there are misbehaving or even malicious IoT devices in one's network. The aim of this paper is to provide a systematic categorisation of machine learning augmented techniques that can be used for fingerprinting IoT devices. This can serve as a baseline for comparing various IoT fingerprinting mechanisms, so that network administrators can choose one or more mechanisms that are appropriate for monitoring and maintaining their network. We carried out an extensive literature review of existing papers on fingerprinting IoT devices -- paying close attention to those with machine learning features. This is followed by an extraction of important and comparable features among the mechanisms outlined in those papers. As a result, we came up with a key set of terminologies that are relevant both in the fingerprinting context and in the IoT domain. This enabled us to construct a framework called IDWork, which can be used for categorising existing IoT fingerprinting mechanisms in a way that will facilitate a coherent and fair comparison of these mechanisms. We found that the majority of the IoT fingerprinting mechanisms take a passive approach -- mainly through network sniffing -- instead of being intrusive and interactive with the device of interest. Additionally, a significant number of the surveyed mechanisms employ both static and dynamic approaches, in order to benefit from complementary features that can be more robust against certain attacks such as spoofing and replay attacks.

cs.NI↗

SoK: Beyond IoT MUD Deployments -- Challenges and Future Directions

Due to the advancement of IoT devices in both domestic and industrial environments, the need to incorporate a mechanism to build accountability in the IoT ecosystem is paramount. In the last few years, various initiatives have been started in this direction addressing many socio-technical concerns and challenges to build an accountable system. The solution that has received a lot of attention in both industry and academia is the Manufacturer Usage Description (MUD) specification. It gives the possibility to the IoT device manufacturers to describe communications needed by each device to work properly. MUD implementation is challenging not only due to the diversity of IoT devices and manufacturer/operator/regulators but also due to the incremental integration of MUD-based flow control in the already existing Internet infrastructure. To provide a better understanding of these challenges, in this work, we explore and investigate the prototypes of three implementations proposed by different research teams and organisations, useful for the community to understand which are the various features implemented by the existing technologies. By considering that there exist some behaviours which can be only defined by local policy, we propose a MUD capable network integrating our User Policy Server(UPS). The UPS provides network administrators and endusers an opportunity to interact with MUD components through a user-friendly interface. Hence, we present a comprehensive survey of the challenges.

cs.NI↗

Suppression of long-range ordering and multiferroicity in Sr-substituted Ba3-xSrxMnNb2O9 (x = 1 and 3)

Effects of Sr substitution at A-site in ordered perovskite Ba3-xSrxMnNb2O9 (x = 1 and 3) have been investigated using X-ray diffraction, magnetization, dielectric/magnetodielectric and neutron diffraction measurements. The parent compound Ba3MnNb2O9 having a large spin (S=5/2) is known to exhibit type-II multiferroic properties with quasi 2D triangular lattice antiferromagnetic ground state. A slight perturbation in exchange interaction due to substitution of smaller size isovalent ion at the A-site in Ba3-xSrxMnNb2O9 (x = 1 and 3) has been found to alter the ground states drastically and hence the multiferroicity. The crucial role of various fluctuations (quantum and/or thermal), weak lattice distortion induced by Sr-substitution and slight imbalance between different fluctuations in determining the ground states and the multiferroicity is discussed and compared with the results of smaller spin compounds (S = 1/2 or 1).

cond-mat.str-el↗

Incommensurate charge and spin density wave order in electron doped SrMn1-xWxO3 (x= 0.08 to 0.1875)

Incommensurate (IC) charge-order (CO) and spin density wave (SDW) order in electron doped SrMn1-xWxO3-δ (x= 0.08 to 0.1875) have been studied using neutron diffraction.The study highlights the drastic effect of electron doping on the emergence of magnetic ground states which were not revealed in manganites before. With increasing (x) the crystal structure changes from simple tetragonal (P4/mmm) to an IC-CO modulated structure with super space-group P2/m(α\b{eta}0)00 having ab-planer ferro order of 3dx2-y2 orbitals in a compressed tetragonal (c 0.1, a different C-type AFM order with propagation vector k = (1/2,0,1/2), coexists with an incommensurate SDW order with k = (0.12, 0.38, 1/2).For compositions with 0.1625 < x < 0.175, while the structural features of CDW and orbital-order remain qualitatively the same, the magnetic interaction gets modified and results another SDW phase with single incommensurate propagation vector k = (0.07, 0.43, 1/2). A detail magnetic and structural phase-diagram, as a function of W substitution for SrMn1-xWxO3 (0.08 < x < 0.4) is presented.

cond-mat.mtrl-sci↗

Network Service Dependencies in Commodity Internet-of-Things Devices

We continue to see increasingly widespread deployment of IoT devices, with apparent intent to embed them in our built environment likely to accelerate if smart city and related programmes succeed. In this paper we are concerned with the ways in which current generation IoT devices are being designed in terms of their ill-considered dependencies on network connectivity and services. Our hope is to provide evidence that such dependencies need to be better thought through in design, and better documented in implementation so that those responsible for deploying these devices can be properly informed as to the impact of device deployment (at scale) on infrastructure resilience. We believe this will be particularly relevant as we feel that commodity IoT devices are likely to be commonly used to retrofit `smart' capabilities to existing buildings, particularly domestic buildings. To the existing body of work on network-level behaviour of IoT devices, we add \one~a protocol-level breakdown and analysis of periodicity, \two~an exploration of the service and infrastructure dependencies that will implicitly be taken in `smart' environments when IoT devices are deployed, and \three~examination of the robustness of device operation when connectivity is disrupted. We find that many devices make use of services distributed across the planet and thus appear dependent on the global network infrastructure even when carrying out purely local actions. Some devices cease to operate properly without network connectivity (even where their behaviour appears, on the face of it, to require only local information, e.g.,~the Hive thermostat). Further, they exhibit quite different network behaviours, typically involving significantly more traffic and possibly use of otherwise unobserved protocols, when connectivity is recovered after some disruption.

cs.NI↗