Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Journal of Hardware and Systems Security

Quantum-IoT Security: Advances, Challenges, and Future Directions

Ali Hassan

Published Apr 6, 2026• 1 citation
Publisher
DOI
10.1007/s41635-026-00179-z

Related papers

Securing the Internet of Things (IoT) in the Quantum Era: Challenges and Future Directions for Quantum-Resistant Cryptography

Maryam Al Washahi, Hothefa Shaker Jassim, Fadi Abdelfattah

•Jan 1, 2024•1 citation

Research Challenges and Future Work Directions in Quantum Computing-Based IoT Environment

Tarana Singh, Sagnik Datta, Keinisha Joshi +1 more

Studies in computational intelligence•Jan 1, 2026•0 citations

Quantum-empowered federated learning and 6G wireless networks for IoT security: Concept, challenges and future directions

Danish Javeed, Muhammad Shahid Saeed, Ijaz Ahmad +3 more

The Internet of Things (IoT) has revolutionized various sectors by enabling seamless device interaction. However, the proliferation of IoT devices has also raised significant security and privacy concerns. Traditional security measures often fail to address these concerns due to the unique characteristics of IoT networks, such as heterogeneity, scalability, and resource constraints. This survey paper adopts a thematic exploration approach for a comprehensive analysis to investigate the convergence of quantum computing, federated learning, and 6G wireless networks. This novel intersection is explored to significantly improve security and privacy within the IoT ecosystem. To enable several secure, intelligent IoT applications, quantum computing, with its superior computational capabilities, can strengthen encryption algorithms, making IoT data more secure. Federated learning, a decentralized machine learning approach, allows IoT devices to learn a shared model while keeping all the training data on the original device, thereby enhancing privacy. This synergy becomes even more crucial when integrated with the high-speed, low-latency capabilities of 6G networks, which can facilitate real-time, secure data processing and communication among many IoT devices. Second, we discuss the latest developments, offering an up-to-date overview of advanced solutions, available datasets, and key performance metrics and summarizing the vital insights, challenges, and trends in securing IoT systems. Third, we design a conceptual framework for integrating quantum computing in federated learning, adapted for 6G networks. Finally, we highlight the future advancements in quantum technologies and 6G networks and summarize the implications for IoT security, paving the way for researchers and practitioners in the field of IoT security.

Future Generation Computer Systems•Jun 13, 2024•126 citations

Rethinking IoT Security in the Era of Quantum Computing: Literature Reviews

Yacoub Hanna, Samet Tonyalı, Ricardo Harrilal-Parchment +1 more

Studies in computational intelligence•Jan 1, 2026•1 citation

Securing IoT in the Post-Quantum Era: Implementation, Challenges, and Future Directions

Muhammad Asghar Khan, Muhammad Attique Khan

The Internet of Things (IoT) is involved in almost every industry, paving the way for innovative applications, including smart cities, intelligent systems, smart homes, smart agriculture, healthcare, and more. However, due to their asset value, these applications are under continuous and evolving cyberattacks. Furthermore, the advent of quantum computing presents a severe threat to traditional cryptographic methods that typically secure IoT systems, potentially rendering existing security mechanisms ineffective against quantum-enabled attacks. To tackle quantum-enabled and traditional cyberattacks, post-quantum cryptography (PQC) has emerged as a promising solution for providing future-proof security for IoT devices and networks against the quantum computing threat. PQC algorithms can resist cyberattacks from classical and quantum computers, ensuring long-term security solutions. This article explores the integration of PQC into practical IoT systems. It highlights the vulnerabilities of classical cryptographic methods and the necessity of transitioning to quantum-resistant solutions. Moreover, the implementation of PQC on IoT systems is analyzed. By proactively exploring the opportunities and challenges associated with PQC, this research lays out future directions for implementing robust, scalable, and secure IoT systems.

IEEE Communications Standards Magazine•Jun 30, 2025•6 citations

QUANTUM ENHANCED SECURITY FRAMEWORKS FOR THE INTERNET OF THINGS: CHALLENGES AND FUTURE DIRECTIONS

International Conference on Cybersecurity and Digital Defense (ICyDD)•Oct 25, 2025•0 citations
The Internet of Things (IoT) has revolutionized various sectors by enabling seamless device interaction. However, the proliferation of IoT devices has also raised significant security and privacy concerns. Traditional security measures often fail to address these concerns due to the unique characteristics of IoT networks, such as heterogeneity, scalability, and resource constraints. This survey paper adopts a thematic exploration approach for a comprehensive analysis to investigate the convergence of quantum computing, federated learning, and 6G wireless networks. This novel intersection is explored to significantly improve security and privacy within the IoT ecosystem. To enable several secure, intelligent IoT applications, quantum computing, with its superior computational capabilities, can strengthen encryption algorithms, making IoT data more secure. Federated learning, a decentralized machine learning approach, allows IoT devices to learn a shared model while keeping all the training data on the original device, thereby enhancing privacy. This synergy becomes even more crucial when integrated with the high-speed, low-latency capabilities of 6G networks, which can facilitate real-time, secure data processing and communication among many IoT devices. Second, we discuss the latest developments, offering an up-to-date overview of advanced solutions, available datasets, and key performance metrics and summarizing the vital insights, challenges, and trends in securing IoT systems. Third, we design a conceptual framework for integrating quantum computing in federated learning, adapted for 6G networks. Finally, we highlight the future advancements in quantum technologies and 6G networks and summarize the implications for IoT security, paving the way for researchers and practitioners in the field of IoT security.
The Internet of Things (IoT) is involved in almost every industry, paving the way for innovative applications, including smart cities, intelligent systems, smart homes, smart agriculture, healthcare, and more. However, due to their asset value, these applications are under continuous and evolving cyberattacks. Furthermore, the advent of quantum computing presents a severe threat to traditional cryptographic methods that typically secure IoT systems, potentially rendering existing security mechanisms ineffective against quantum-enabled attacks. To tackle quantum-enabled and traditional cyberattacks, post-quantum cryptography (PQC) has emerged as a promising solution for providing future-proof security for IoT devices and networks against the quantum computing threat. PQC algorithms can resist cyberattacks from classical and quantum computers, ensuring long-term security solutions. This article explores the integration of PQC into practical IoT systems. It highlights the vulnerabilities of classical cryptographic methods and the necessity of transitioning to quantum-resistant solutions. Moreover, the implementation of PQC on IoT systems is analyzed. By proactively exploring the opportunities and challenges associated with PQC, this research lays out future directions for implementing robust, scalable, and secure IoT systems.