Securing IoT Communication with the Integration of Quantum Cryptography and Machine Learning
Keywords:
Iot, Quantum Key Distribution (Qkd) Protocols, Cryptography, Machine Learning.Abstract
The rapid implementation of the Internet of Things (IoT) has raised security concerns, therefore revealing significant vulnerabilities in many sectors, including smart cities, healthcare, and agriculture. This extensive analysis of quantum computing and IoT security devices delineates the advantages of quantum algorithms and the potential for securing communication. Protocols including quantum concepts such as superposition, entanglement, and quantum interference, leading to safe key distribution and authentication procedures, are examined. This paper introduces a novel strategy to reduce the risks that quantum computing presents to IoT systems, which current cryptography solutions fail to adequately address. Quantum computers may use these vulnerabilities to undermine key-pair formation and get private keys from transaction signatures. These transaction signatures are optimized for low-power, cost-effective microcontrollers, such as the ESP32, making the solution accessible for a diverse array of IoT devices. The report features a case study on a post-quantum secure portable device for detecting blood oxygen levels and heart rate, demonstrating the practical advantages and efficacy of the suggested method in improving IoT security against quantum threats. The review addresses quantum key distribution (QKD) protocols, quantum authentication methods proposed as solutions, and the difficulties associated with implementing quantum cryptography techniques in IoT systems. This review assesses the feasibility of quantum-enabled communication, explores its applications across several industries, and examines existing quantum software tools. The objective is to provide a basis for future research and effective practical solutions in the dynamic realm of IoT security.
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Castiglione, J. G. Esposito, V. Loia, M. Nappi, C. Pero and M. Polsinelli, "Integrating Post-Quantum Cryptography and Blockchain to Secure Low-Cost IoT Devices," in IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2024.3485796.
Dr. B. Sathananth, J. Selvin Jeba Singh, Exploring The Intersection Of Quantum Computing And Internet Of Things Security: A Comprehensive Survey, Issn (Print): 2393-8374, (Online): 2394-0697, Volume-6, Issue-7, 2019.
Aryyama Kumar Jana1, Srija Saha, Integrating Machine Learning with Cryptography to Ensure Dynamic Data Security and Integrity, International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.538 , Volume 11 Issue X Oct 2023- Available at www.ijraset.com
Udoh, I.S. and Kotonya, G. (2018), Developing IoT applications: challenges and frameworks. IET Cyber-Physical Systems: Theory & Applications, 3: 65-72. https://doi.org/10.1049/iet-cps.2017.0068.
Sun, Li, and Qinghe Du. 2018. "A Review of Physical Layer Security Techniques for Internet of Things: Challenges and Solutions" Entropy 20, no. 10: 730. https://doi.org/10.3390/e20100730.
A. A. A. El-Latif, B. Abd-El-Atty, M. S. Hossain, S. Elmougy and A. Ghoneim, "Secure Quantum Steganography Protocol for Fog Cloud Internet of Things," in IEEE Access, vol. 6, pp. 10332-10340, 2018, doi: 10.1109/ACCESS.2018.2799879.
Usenko, Vladyslav C., and Radim Filip. 2016. "Trusted Noise in Continuous-Variable Quantum Key Distribution: A Threat and a Defense" Entropy 18, no. 1: 20. https://doi.org/10.3390/e18010020.
Alshammari, Majid R., and Khaled M. Elleithy. 2018. "Efficient and Secure Key Distribution Protocol for Wireless Sensor Networks" Sensors 18, no. 10: 3569. https://doi.org/10.3390/s18103569.
Thomford, Nicholas Ekow, Dimakatso Alice Senthebane, Arielle Rowe, Daniella Munro, Palesa Seele, Alfred Maroyi, and Kevin Dzobo. 2018. "Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery" International Journal of Molecular Sciences 19, no. 6: 1578. https://doi.org/10.3390/ijms19061578.
M. Elhoseny, G. Ramírez-González, O. M. Abu-Elnasr, S. A. Shawkat, N. Arunkumar and A. Farouk, "Secure Medical Data Transmission Model for IoT-Based Healthcare Systems," in IEEE Access, vol. 6, pp. 20596-20608, 2018, doi: 0.1109/ACCESS.2018.2817615.
Xie, J., Hu, Yp., Gao, Jt. et al. Efficient identity-based signature over NTRU lattice. Frontiers Inf Technol Electronic Eng 17, 135–142 (2016). https://doi.org/10.1631/FITEE.1500197.
Broadbent, A., Schaffner, C. Quantum cryptography beyond quantum key distribution. Des. Codes Cryptogr. 78, 351–382 (2016). https://doi.org/10.1007/s10623-015-0157-4.
J. Yuan and X. Li, "A Reliable and Lightweight Trust Computing Mechanism for IoT Edge Devices Based on Multi-Source Feedback Information Fusion," in IEEE Access, vol. 6, pp. 23626-23638, 2018, doi: 10.1109/ACCESS.2018.2831898.
A. Aslam and E. Curry, "Towards a Generalized Approach for Deep Neural Network Based Event Processing for the Internet of Multimedia Things," in IEEE Access, vol. 6, pp. 25573-25587, 2018, doi: 10.1109/ACCESS.2018.2823590.
Bendavid, Ygal, Nasour Bagheri, Masoumeh Safkhani, and Samad Rostampour. 2018. "IoT Device Security: Challenging “A Lightweight RFID Mutual Authentication Protocol Based on Physical Unclonable Function” https://doi.org/10.3390/s18124444. Sensors 18, no. 12: 4444.
Möller, M., Vuik, C. On the impact of quantum computing technology on future developments in high-performance scientific computing. Ethics Inf Technol 19, 253–269 (2017). https://doi.org/10.1007/s10676-017-9438-0.
I. Bhardwaj, A. Kumar and M. Bansal, "A review on lightweight cryptography algorithms for data security and authentication in IoTs," 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC), Solan, India, 2017, pp. 504-509, doi: 10.1109/ISPCC.2017.8269731.
Q. Yang and S. -J. Yoo, "Optimal UAV Path Planning: Sensing Data Acquisition Over IoT Sensor Networks Using Multi-Objective Bio-Inspired Algorithms," in IEEE Access, vol. 6, pp. 13671-13684, 2018, doi: 10.1109/ACCESS.2018.2812896.
Ruan, Y., Chen, H., Tan, J. et al. Quantum computation for large-scale image classification. Quantum Inf Process 15, 4049–4069 (2016). https://doi.org/10.1007/s11128-016-1391-z.
Vermaas, P.E. The societal impact of the emerging quantum technologies: a renewed urgency to make quantum theory understandable. Ethics Inf Technol 19, 241–246 (2017). https://doi.org/10.1007/s10676-017-9429-1.
Broadbent, A., Schaffner, C. Quantum cryptography beyond quantum key distribution. Des. Codes Cryptogr. 78, 351–382 (2016). https://doi.org/10.1007/s10623-015-0157-4.
Usenko, Vladyslav C., and Radim Filip. 2016. "Trusted Noise in Continuous-Variable Quantum Key Distribution: A Threat and a Defense" https://doi.org/10.3390/e18010020.Entropy 18, no. 1: 20.
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