arXiv subjects

Bhanu Prakash

Publications and source records attributed to Bhanu Prakash.

4 recordsLinked to original sources

arXiv2026

SNAS: A Multi-Layer Defense-in-Depth Architecture for Secure Egress in Sandboxed Workloads

Snowpark enables data engineering and AI/ML workloads in Snowflake by executing user-defined functions in secure sandboxes. Many of these workloads require external connectivity to access cloud APIs, external databases, or feature stores, creating a dependability challenge: how to provide transparent network access while preserving strict multi-tenant isolation and resource fairness. This paper presents Secure Network Access in Snowpark (SNAS), a production architecture for secure external communication from sandboxed workloads. SNAS combines Extended Berkeley Packet Filter (eBPF) packet filtering, Generic Network Virtualization Encapsulation (GENEVE) overlay networks, and distributed egress proxies for policy-driven egress control with low overhead. We describe the design, deployment, and measured production behavior of SNAS, including an eBPF-based bandwidth limiter using the Earliest Departure Time (EDT) algorithm, dual-tier policy enforcement, and safeguards for connection limiting and port exhaustion. SNAS is deployed across all Snowflake regions and supports large-scale production workloads including petabyte-scale data transfer and latency-sensitive external integrations.

cs.CR↗

arXiv2023

Odd symmetry planar Hall effect: A method of detecting current-induced in-plane magnetization switching

Type-x device attracts considerable interest in the field of spintronics due to its robust spin-orbit torque (SOT) induced magnetization switching, and easy deposition technique. However, universally applicable and straightforward detection of type-X magnetization reversal is still elusive, unlike type-Z switching, which employs DC-based anomalous Hall effect measurement. Here, we, demonstrated that the odd planar Hall signal (O-PHV) exhibits an odd symmetry with the application of an external magnetic field which motivates us to develop a reading mechanism for detecting magnetization switching of in-plane magnetized type-X devices. We verified our DC-based reading mechanism in the Pt/Co/NiFe/Pt stack where a thin Co layer is inserted to create dissimilar interfaces about the NiFe layer. Remarkably, the current-induced in-plane fields are found to be significantly large in Pt/Co/NiFe/Pt stack. Further, we successfully employed the O-PHV method to detect the current-induced magnetization switching. The pure DC nature of the writing and reading mechanism of our proposed type-X detection technique through O-PHV makes it the easiest in-plane magnetization detection technique. Moreover, the high repeatability and easy detection of our proposed method will open new avenues toward in-plane SOT switching based memory devices and sensors.

cond-mat.mes-hall↗

arXiv2020

Crucial Inflammatory Mediators and Efficacy of Drug Interventions in Pneumonia Inflated COVID-19: An Invivo Mathematical Modelling Study

The virus SARS-COV-2 caused disease COVID-19 has been declared a pandemic by WHO. Currently, over 210 countries and territories have been affected. Careful, well-designed drugs and vaccine for the total elimination of this virus seem to be the need of the hour. In this context, the invivo mathematical modelling studies can be extremely helpful in understanding the efficacy of the drug interventions. These studies can also help understand the role of the crucial inflammatory mediators and the behaviour of immune response towards this novel coronavirus. Motivated by these facts, in this paper, we study the invivo dynamics of Covid-19. The results obtained here are inline with some of the clinical findings for Covid-19. This invivo modelling study involving the crucial biomarkers of Covid-19 is the first of its kind and the results obtained from this can be helpful to researchers, epidemiologists, clinicians and doctors who are working in this field.

q-bio.PE↗

arXiv2020

Optimal Drug Regimen and Combined Drug Therapy and its Efficacy in the Treatment of COVID-19 : An Within-Host Modeling Study

The COVID-19 pandemic has resulted in more than 30.35 million infections and 9, 50, 625 deaths in 212 countries over the last few months. Different drug intervention acting at multiple stages of pathogenesis of COVID-19 can substantially reduce the infection induced mortality. The current within-host mathematical modeling studies deals with the optimal drug regimen and the efficacy of combined therapy in treatment of COVID-19. The drugs/interventions considered include Arbidol, Remdesivir, Inteferon (INF) and Lopinavir/Ritonavir. It is concluded that these drug interventions when administered individually or in combination reduce the infected cells and viral load. Four scenarios involving administration of single drug intervention, two drug interventions, three drug interventions and all the four have been discussed. In all these scenarios the optimal drug regimen is proposed based on two methods. In the first method these medical interventions are modeled as control interventions and a corresponding objective function and optimal control problem is formulated. In this setting the optimal drug regimen is proposed. Later using the the comparative effectiveness method the optimal drug regimen is proposed based on basic reproduction number and viral load. The average infected cell count and viral load decreased the most when all the four interventions were applied together. On the other hand the average susceptible cell count decreased the best when Arbidol alone was administered. The basic reproduction number and viral count decreased the best when all the four interventions were applied together reinstating the fact obtained earlier in the optimal control setting. These findings may help physicians with decision making in treatment of life-threatening COVID-19 pneumonia.

q-bio.PE↗