Systematic Review of 6G-IoT Privacy Risks, Emerging Threats, Mitigation Strategies, and Cybersecurity

Background: Sixth-generation (6G) wireless networks are expected to deliver unprecedented connectivity, with device densities surpassing one million per km², sub-millisecond latency, and AI-native architectures. While these advances promise transformative applications in healthcare, autonomous systems, and smart cities, they also introduce complex cybersecurity and privacy challenges that extend far beyond those of previous generations. Objective: This review systematically synthesizes emerging evidence on cybersecurity risks and privacy challenges in 6G-enabled Internet of Things (IoT) ecosystems, identifies critical vulnerabilities, and evaluates proposed mitigation strategies within the context of anticipated 6G and quantum computing timelines. Methods: A systematic literature review was conducted following PRISMA guidelines across IEEE Xplore, ACM Digital Library, Science Direct, Springer Link, and standards bodies (NIST, ITU-R, 3GPP). From 847 records, 50 studies (2023–2025) met inclusion criteria. Data were extracted on risk categories, privacy implications, and mitigation strategies, with methodological rigor assessed using a CASP-adapted framework. Results: Five major risk domains were identified: (1) AI-native vulnerabilities, including adversarial ML and model poisoning; (2) cryptographic obsolescence under quantum computing; (3) IoT device vulnerabilities, with 60% of breaches linked to unpatched firmware; (4) distributed edge computing risks; and (5) novel communication-medium threats (terahertz, VLC, molecular). Privacy challenges center on precision localization, cross-device behavioral profiling, and regulatory misalignment with automated 6G systems. Promising mitigation strategies include Zero Trust architectures, post-quantum cryptography, blockchain-based identity management, and AI-enhanced detection systems. Conclusions: Traditional perimeter-based models are inadequate for 6G-IoT. The convergence of massive device connectivity and quantum-era threats demands urgent adoption of quantum-resistant cryptography, adaptive Zero Trust frameworks, and privacy-by-design architectures. The next five years represent a critical window for coordinated action among academia, industry, and policymakers to ensure that 6G fulfills its transformative potential securely, privately, and ethically.

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Publication Details

Journal
Asian Journal of Advanced Research and Reports
Published
2025-09-10
DOI
https://doi.org/10.9734/ajarr/2025/v19i91151
Citations
1
Primary Topic
Digital Transformation in Law
Type
article
Field-Weighted Citation Impact
3.09
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article

Systematic Review of 6G-IoT Privacy Risks, Emerging Threats, Mitigation Strategies, and Cybersecurity

Emma Junior Emmanuel
1 citations
Asian Journal of Advanced Research and Reports
Digital Transformation in Law
3.09
article

Systematic Review of 6G-IoT Privacy Risks, Emerging Threats, Mitigation Strategies, and Cybersecurity

Emma Junior Emmanuel
article en
1 citations

Abstract

Background: Sixth-generation (6G) wireless networks are expected to deliver unprecedented connectivity, with device densities surpassing one million per km², sub-millisecond latency, and AI-native architectures. While these advances promise transformative applications in healthcare, autonomous systems, and smart cities, they also introduce complex cybersecurity and privacy challenges that extend far beyond those of previous generations. Objective: This review systematically synthesizes emerging evidence on cybersecurity risks and privacy challenges in 6G-enabled Internet of Things (IoT) ecosystems, identifies critical vulnerabilities, and evaluates proposed mitigation strategies within the context of anticipated 6G and quantum computing timelines. Methods: A systematic literature review was conducted following PRISMA guidelines across IEEE Xplore, ACM Digital Library, Science Direct, Springer Link, and standards bodies (NIST, ITU-R, 3GPP). From 847 records, 50 studies (2023–2025) met inclusion criteria. Data were extracted on risk categories, privacy implications, and mitigation strategies, with methodological rigor assessed using a CASP-adapted framework. Results: Five major risk domains were identified: (1) AI-native vulnerabilities, including adversarial ML and model poisoning; (2) cryptographic obsolescence under quantum computing; (3) IoT device vulnerabilities, with 60% of breaches linked to unpatched firmware; (4) distributed edge computing risks; and (5) novel communication-medium threats (terahertz, VLC, molecular). Privacy challenges center on precision localization, cross-device behavioral profiling, and regulatory misalignment with automated 6G systems. Promising mitigation strategies include Zero Trust architectures, post-quantum cryptography, blockchain-based identity management, and AI-enhanced detection systems. Conclusions: Traditional perimeter-based models are inadequate for 6G-IoT. The convergence of massive device connectivity and quantum-era threats demands urgent adoption of quantum-resistant cryptography, adaptive Zero Trust frameworks, and privacy-by-design architectures. The next five years represent a critical window for coordinated action among academia, industry, and policymakers to ensure that 6G fulfills its transformative potential securely, privately, and ethically.

Asian Journal of Advanced Research and ReportsVol. 19(9)
Prairie View A&M University (US)
Openalex Percentile: Top 8%
Digital Transformation in Law
3.09
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