arXiv subjects

Nikhil Kumar Rajput

Publications and source records attributed to Nikhil Kumar Rajput.

5 recordsLinked to original sources

arXiv2026

Post-Quantum Identity-Based TLS for 5G Service-Based Architecture and Cloud-Native Infrastructure

Cloud-native application platforms and latency-sensitive systems such as 5G Core networks rely heavily on certificate-based Public Key Infrastructure (PKI) and mutual TLS to secure service-to-service communication. While effective, this model introduces significant operational and performance overhead, which is further amplified in the post-quantum setting due to large certificates and expensive signature verification. In this paper, we present a certificate-free authentication framework for private distributed systems based on post-quantum Identity-Based Encryption(IBE). Our design replaces certificate and signature based authentication with identity-derived keys and identity-based key encapsulation, enabling mutually authenticated TLS connections without certificate transmission or validation. We describe an IBE-based replacement for private PKI, including identity lifecycle management, and show how it can be instantiated using a threshold Private Key Generator (T-PKG). We apply this framework to cloud-native application deployments and latency-sensitive 5G Core networks. In particular, we demonstrate how identity-based TLS integrates with the 5G Service-Based Architecture while preserving security semantics and 3GPP requirements, and we show how the same architecture can replace private PKI in Kubernetes, including its control plane, without disrupting existing trust domains or deployment models.

cs.CR↗

arXiv2025

Quantum State Preparation for Medical Data: Comprehensive Methods, Implementation Challenges, and Clinical Prospects

Quantum computing holds transformative potential for medical applications, yet efficiently preparing quantum states from complex medical data remains a fundamental challenge. This survey provides a comprehensive examination of current approaches for encoding medical information into quantum systems, analyzing theoretical principles, algorithmic advancements, and practical limitations. It discusses tensor network decomposition, variational quantum algorithms, quantum machine learning techniques, and specialized error mitigation strategies for medical computing. The findings indicate that quantum advantages in medicine rely on leveraging inherent data structures such as spatial correlations in imaging, temporal patterns in physiological signals, and hierarchical biological organization. While current hardware restricts implementations to small-scale problems, emerging methods show potential for near-term use. The study provides a structured framework for assessing when quantum state preparation outperforms classical approaches in medicine, along with implementation guidelines and performance benchmarks.

quant-ph↗

arXiv2025

Quantum Machine Learning: Unveiling Trends, Impacts through Bibliometric Analysis

Quantum Machine Learning (QML) is the intersection of two revolutionary fields: quantum computing and machine learning. It promises to unlock unparalleled capabilities in data analysis, model building, and problem-solving by harnessing the unique properties of quantum mechanics. This research endeavors to conduct a comprehensive bibliometric analysis of scientific information pertaining to QML covering the period from 2000 to 2023. An extensive dataset comprising 9493 scholarly works is meticulously examined to unveil notable trends, impact factors, and funding patterns within the domain. Additionally, the study employs bibliometric mapping techniques to visually illustrate the network relationships among key countries, institutions, authors, patent citations and significant keywords in QML research. The analysis reveals a consistent growth in publications over the examined period. The findings highlight the United States and China as prominent contributors, exhibiting substantial publication and citation metrics. Notably, the study concludes that QML, as a research subject, is currently in a formative stage, characterized by robust scholarly activity and ongoing development.

cs.DL↗

arXiv2024

Word frequency and sentiment analysis of twitter messages during Coronavirus pandemic

The COVID-19 epidemic has had a great impact on social media conversation, especially on sites like Twitter, which has emerged as a hub for public reaction and information sharing. This paper deals by analyzing a vast dataset of Twitter messages related to this disease, starting from January 2020. Two approaches were used: a statistical analysis of word frequencies and a sentiment analysis to gauge user attitudes. Word frequencies are modeled using unigrams, bigrams, and trigrams, with power law distribution as the fitting model. The validity of the model is confirmed through metrics like Sum of Squared Errors (SSE), R-squared ($R^2$), and Root Mean Squared Error (RMSE). High $R^2$ and low SSE/RMSE values indicate a good fit for the model. Sentiment analysis is conducted to understand the general emotional tone of Twitter users messages. The results reveal that a majority of tweets exhibit neutral sentiment polarity, with only 2.57\% expressing negative polarity.

cs.IR↗

arXiv2020

Complex Network Analysis of Indian Railway Zones

Indian Railway Network has been analyzed on the basis of number of trains directly linking two railway zones. The network has been displayed as a weighted graph where the weights denote the number of trains between the zones. It may be pointed out that each zone is a complex network in itself and may depict different characteristic features. The zonal network therefore can be considered as a network of complex networks. In this paper, self links, in-degree and out-degree of each zone have been computed which provides information about the inter and intra zonal connectivity. Degree passenger correlation which gives an idea about number of trains and passengers originating from a particular zone which might play a role in policy making decisions has also been studied. Some other complex network parameters like betweenness, clustering coefficient and cliques have been obtained to get more insight about the complex Indian zonal network.

physics.soc-ph↗