On the Integration of Artificial Intelligence and Blockchain Technology: A Perspective About Security

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 3881 - 3897

Published: Jan. 1, 2024

As reliance on disruptive applications based Artificial Intelligence (AI) and Blockchain grows, the need for secure trustworthy solutions becomes ever more critical. Whereas much research has been conducted AI Blockchain, there is a shortage of comprehensive studies examining their integration from security perspective. Hence, this survey addresses such gap provides insights policymakers, researchers, practitioners exploiting Blockchain's evolving integration. Specifically, paper analyzes potential benefits as well related concerns, identifying possible mitigation strategies, suggesting regulatory measures, describing impact it public trust.

Language: Английский

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Securing internet of things using machine and deep learning methods: a survey

Cluster Computing, Journal Year: 2024, Volume and Issue: 27(7), P. 9065 - 9089

Published: April 16, 2024

Abstract The Internet of Things (IoT) is a vast network devices with sensors or actuators connected through wired wireless networks. It has transformative effect on integrating technology into people’s daily lives. IoT covers essential areas such as smart cities, homes, and health-based industries. However, security privacy challenges arise the rapid growth applications. Vulnerabilities node spoofing, unauthorized access to data, cyberattacks denial service (DoS), eavesdropping, intrusion detection have emerged significant concerns. Recently, machine learning (ML) deep (DL) methods significantly progressed are robust solutions address these issues in devices. This paper comprehensively reviews research focusing ML/DL approaches. also categorizes recent studies based highlights their opportunities, advantages, limitations. These insights provide potential directions for future challenges.

Language: Английский

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Machine Learning in Metaverse Security: Current Solutions and Future Challenges

ACM Computing Surveys, Journal Year: 2024, Volume and Issue: 56(8), P. 1 - 36

Published: March 28, 2024

The Metaverse, positioned as the next frontier of Internet, has ambition to forge a virtual shared realm characterized by immersion, hyper-spatiotemporal dynamics, and self-sustainability. Recent technological strides in AI, Extended Reality, 6G, blockchain propel Metaverse closer realization, gradually transforming it from science fiction into an imminent reality. Nevertheless, extensive deployment faces substantial obstacles, primarily stemming its potential infringe on privacy be susceptible security breaches, whether inherent underlying technologies or arising evolving digital landscape. provisioning is poised confront various foundational challenges owing distinctive attributes, encompassing immersive realism, hyper-spatiotemporally, sustainability, heterogeneity. This article undertakes comprehensive study facing leveraging machine learning models for this purpose. In particular, our focus centers innovative distributed architecture interactions across 3D worlds. Subsequently, we conduct thorough review existing cutting-edge measures designed systems while also delving discourse surrounding threats. As contemplate future systems, outline directions open research pursuits

Language: Английский

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The Role of Blockchain in Medical Data Sharing

Cryptography, Journal Year: 2023, Volume and Issue: 7(3), P. 36 - 36

Published: July 12, 2023

As medical technology advances, there is an increasing need for healthcare providers all over the world to securely share a growing volume of data. Blockchain powerful that allows multiple parties access and Given enormous challenge systems face in digitizing sharing health records, it not unexpected many are attempting improve processes by utilizing blockchain technology. By systematically examining articles published from 2017 2022, this review addresses existing gap methodically discussing state, research trends, challenges data exchange. The number on issue has increased, reflecting importance interest Recent blockchain-based advances include safe management systems, architectures, smart contract frameworks, encryption approaches. evaluation examines encryption, networks, how Internet Things (IoT) improves hospital workflows. findings show can patient care services

Language: Английский

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Optimizing Blockchain Analysis: Tackling Temporality and Scalability with an Incremental Approach with Metropolis-Hastings Random Walks

Published: Feb. 26, 2025

Language: Английский

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Exploring the influencing factors of blockchain technology adoption in national quality infrastructure: a Dual-Stage structural equation model and artificial neural network approach using TAM-TOE framework

Cogent Engineering, Journal Year: 2024, Volume and Issue: 11(1)

Published: June 26, 2024

This study explores the adoption of blockchain technology within Ethiopian National Quality Infrastructure (NQI). Data from 178 professionals representing various organizations and roles were collected to investigate key factors. By integrating Technology Acceptance Model (TAM) Technology-Organization-Environment (TOE) framework, external factors (Technology Compatibility, Relative Advantage, Government Support, Policy) internal (perceived usefulness, perceived ease use, intention use) examined. A dual-stage analytical approach involving partial least square-based structural equation model (PLS-SEM) artificial neural network (ANN) analyses was employed. The findings emphasize significance technological compatibility, top management support as determinants in NQI. Particularly, compatibility existing system emerges most influential factor adopting enhances understanding NQI context, providing valuable insights for successful implementation. It contributes knowledge this area offers practical implications quality infrastructure management.

Language: Английский

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Privacy and Security in Artificial Intelligence and Machine Learning Systems for Renewable Energy Big Data

Published: Jan. 15, 2024

This paper explores the critical intersection of security and privacy in advanced artificial intelligence (AI) machine learning (ML) with Internet Things (IoT) systems edge computing applied to big data renewable energy (RE) sector, where generated is grown exponentially, presenting unique challenges management, analysis, security. study discusses complexities anomaly detection (AD) RE data, examining evolving threats need for real-time processing. Through a comprehensive literature review proposal an innovative framework, we address AD evaluate effectiveness current solutions, propose robust strategies enhancing measures. The underscores continuous protocols' adaptation threats. It emphasizes importance regular audits compliance regulatory standards maintain resilience against cyber

Language: Английский

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An efficient blockchain‐based approach to improve the accuracy of intrusion detection systems

Electronics Letters, Journal Year: 2023, Volume and Issue: 59(18)

Published: Sept. 1, 2023

Abstract Intrusion Detection System (IDS) is a critical cybersecurity task that involves monitoring network traffic for malicious activity and taking appropriate action to stop it. However, insufficient training data or improperly chosen thresholds often limit the accuracy of such systems, resulting in high false‐positive rates. To improve an IDS, blockchain technology can be used as it provides secure, decentralized, immutable ledger track suspicious over time also identify intrusions globally. In this paper, authors propose novel methodology blockchain‐based IDS. The approach combines different intrusion detection algorithms using blockchain‐integrated architecture. It based on fusion principle weighted votes, which determine their results. tested system DARPA 99 MIT‐Lincoln Labs datasets rate two metrics. achieved 92.6% 7.4% rates, indicating proposed significantly increases while reducing rate, opening up new opportunities development highly accurate networks.

Language: Английский

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Beyond Supervised: The Rise of Self-Supervised Learning in Autonomous Systems

Information, Journal Year: 2024, Volume and Issue: 15(8), P. 491 - 491

Published: Aug. 16, 2024

Supervised learning has been the cornerstone of many successful medical imaging applications. However, its reliance on large labeled datasets poses significant challenges, especially in domain, where data annotation is time-consuming and expensive. In response, self-supervised (SSL) emerged as a promising alternative, leveraging unlabeled to learn meaningful representations without explicit supervision. This paper provides detailed overview supervised limitations imaging, underscoring need for more efficient scalable approaches. The study emphasizes importance area under curve (AUC) key evaluation metric assessing SSL performance. AUC offers comprehensive measure model performance across different operating points, which crucial applications, false positives negatives have consequences. Evaluating methods based allows robust comparisons ensures that models generalize well real-world scenarios. reviews recent advances demonstrating their potential revolutionize field by mitigating challenges associated with learning. Key results show techniques, optimizing metrics like AUC, can significantly improve diagnostic accuracy, scalability, efficiency image analysis. findings highlight SSL’s capability reduce dependency present path forward effective solutions.

Language: Английский

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Game of Coding: Beyond Trusted Majorities

2022 IEEE International Symposium on Information Theory (ISIT), Journal Year: 2024, Volume and Issue: unknown, P. 2850 - 2855

Published: July 7, 2024

Language: Английский

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