Quantum algorithms and complexity in healthcare applications: a systematic review with machine learning-optimized analysis

Frontiers in Computer Science, Год журнала: 2025, Номер 7

Опубликована: Май 7, 2025

This paper presents a systematic review of quantum computing approaches to healthcare-related computational problems, with an emphasis on quantum-theoretical foundations and algorithmic complexity. We adopt optimized machine learning methodology—combining Particle Swarm Optimization (PSO) Latent Dirichlet Allocation (LDA)—to analyze the literature identify key research themes at intersection healthcare. A total 63 peer-reviewed studies were analyzed, 41 categorized under first domain 22 second. approach revealed two primary directions: (1) for artificial intelligence in healthcare, (2) healthcare data security. highlight theoretical advances underlying these domains, from novel algorithms biomedical cryptographic protocols securing medical information. gradient boosting classifier further validates our taxonomy by reliably distinguishing between categories research, demonstrating robustness identified themes, accuracy 84.2%, precision 88.9%, recall F1-score 84.5%, area curve 0.875. Interpretability analysis using Local Interpretable Model-Agnostic Explanations (LIME) exposes features each category (e.g., references applications versus blockchain-based security frameworks), offering transparency into literature-driven categorization, latter showing most significant contributions topic assignment (ranging −0.133 +0.128). Our findings underscore that offer potential enhance security, optimize complex diagnostic computations, provide speedups health informatics. also outstanding challenges—such as need scalable error-tolerant hardware integration—that must be addressed translate advancements real-world clinical impact. study emphasizes importance hybrid quantum-classical models cross-disciplinary bridge gap cutting-edge theory its practical

Язык: Английский

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An Efficient Flow-Based Anomaly Detection System for Enhanced Security in IoT Networks

Sensors, Год журнала: 2024, Номер 24(22), С. 7408 - 7408

Опубликована: Ноя. 20, 2024

The growing integration of Internet Things (IoT) devices into various sectors like healthcare, transportation, and agriculture has dramatically increased their presence in everyday life. However, this rapid expansion exposed new vulnerabilities within computer networks, creating security challenges. These IoT devices, often limited by hardware constraints, lack advanced features, making them easy targets for attackers compromising overall network integrity. To counteract these issues, Behavioral-based Intrusion Detection Systems (IDS) have been proposed as a potential solution safeguarding networks. While IDS demonstrated ability to detect threats effectively, they encounter practical challenges due reliance on pre-labeled data the heavy computational power require, limiting deployment. This research introduces IoT-FIDS (Flow-based System IoT), lightweight efficient anomaly detection framework tailored environments. Instead employing traditional machine learning techniques, focuses identifying unusual behaviors examining flow-based representations that capture standard device communication patterns, services used, packet header details. By analyzing only benign traffic, network-based offers streamlined approach securing Our experimental results reveal can accurately most abnormal traffic patterns with minimal false positives, it feasible real-world implementations.

Язык: Английский

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A decentralized asynchronous federated learning framework for edge devices

Future Generation Computer Systems, Год журнала: 2024, Номер unknown, С. 107683 - 107683

Опубликована: Дек. 1, 2024

Язык: Английский

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An Applied Analysis of Securing 5G/6G Core Networks with Post-Quantum Key Encapsulation Methods

Electronics, Год журнала: 2024, Номер 13(21), С. 4258 - 4258

Опубликована: Окт. 30, 2024

Fifth Generation (5G) cellular networks have been adopted worldwide since the rollout began around 2019. It brought with it many innovations and new services, such as Enhanced Mobile Broadband (eMBB), Ultra Reliable Low-Latency Communications (URLLC), Massive Internet of Things (mIoT). Furthermore, 5G introduced a more scalable approach to network operations using fully software-based Virtualized Network Functions (VNF) in Core Networks (CN) rather than prior hardware-based approach. However, while this shift towards system design provides numerous significant benefits, increased interoperability, scalability, cost-effectiveness, also brings an cybersecurity risk. Security is crucial maintaining trust between vendors, operators, consumers. Cyberattacks are rapidly increasing number sophistication, we seeing zero-trust approaches. This means that even communications VNFs inside core must be scrutinized hardened against attacks, especially advent quantum computers. The National Institute Standards Technology (NIST), over past 10 years, has led efforts standardize post-quantum cryptography (PQC) protect attacks. paper covers custom implementation open-source free5GC CN, expand its HTTPS capabilities for by introducing PQC Key Encapsulation Methods (KEM) Transport Layer (TLS) v1.3. details integration focus on latency different KEMs initial handshakes VNFs, packet size, implications environment. work conducts security comparison PQC-equipped other CNs. presented results indicate negligible increase UE connection setup duration small data requirements, strongly indicating KEM’s benefits far outweigh any downsides when integrated into 6G services. To best our knowledge, first incorporating core. from effort demonstrate employing ciphers securing VNF only impact bandwidth usage, thus demonstrating cybersecurity.

Язык: Английский

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Special Issue on Intelligent Architectures and Platforms for Private Edge Cloud Systems

Future Generation Computer Systems, Год журнала: 2024, Номер 164, С. 107605 - 107605

Опубликована: Ноя. 5, 2024

Язык: Английский

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