Blockchain-based delegated Quantum Cloud architecture for medical big data security

https://doi.org/10.1016/j.jnca.2021.103304Get rights and content

Abstract

Smart Healthcare systems compromise complex computations such as visualization of molecules, analysis of DNA, and therapy determination. These are considered to be complex problems that today's supercomputers are still facing. On the other hand, Quantum computing promises fast, efficient, and scalable computing resources that are sufficient to compute large and complex operations in exponential time. It is a fact that Quantum computing will adequately innovate the computation perspective. However, it is not a feasible solution yet as it is likely to be rare and highly expensive to produce. This paper presents a Quantum Cloud-as-a-service for an efficient, scalable, and secure solution for complex Smart Healthcare computations. Our novelty resides in the usage of Quantum Terminal Machines (QTM) and Blockchain technology to enhance the feasibility and security of the proposed architecture. Experimental results prove the feasibility of the architecture and the absolute security of the implemented Q-OTP encryption.

Introduction

A scalable Smart Healthcare system requires secure data collection, efficient and fast data processing, and systematic knowledge extraction (Demirkan, 2013). These applications are often computationally complex and require extensive and powerful computing resources. For instance, RNA sequencing requires at least 1.5–12 days or even more of computation time (Kukurba and Montgomery, 2015) using today's supercomputers. Moreover, healthcare data generated by sensors and health records reached 1024 gigabytes in the U.S. only (Transforming Health, 2013). Healthcare big data consist of large and complex Electronic Health Record (EHR) such as radiology images, annotations, immunization dates, medications, treatment plans, laboratory data, and test results. Apart from EHR, computation on medical data may include DNA computations, molecules visualization, treatment discovery, and so on. The complexity of big medical data resides in the volume, diversity, and speed at which it should be computed and managed (Frost & Sullivan: Drownin). The volume and variety of medical data create a complex exponential searching problem over uninstructed records. While the long computation time needed to manage these kinds of data contributes to a critical restriction of improvement that can be fatal in several cases (Javed et al., 2020; Singh, Azzaoui, Kim, Pan, Park; He et al., 2020; Chen et al., 2020; Alshammari et al., 2020b). Furthermore, the security and privacy of big medical data is another concern urging quick management. The most significant healthcare data breach caused by a third-party vendor happened in 2019 (Healthsecurity and Lates, 2020).

Reportedly, a Blackbaud ransomware attack mirrored the AMCA breach; the attack affected more than 10 million patient records. Medical big data are an essential resource to create better-personalized treatment and medical service for patients. However, the main issues that face medical big data are the complexity, volume, variety, and security. The current computation resources and security measurements have failed multiple times to provide the required and designed service. The recent Coronavirus disease 2019 (COVID-19) case has proved how limited our systems are in discovering a fast and efficient diagnostic process (Naudé, 2020; Wang et al., 2020).

From another perspective, Quantum Information Science is the next promising area of computation and data processing. By nature, Quantum computing merges classical information theory with Quantum physics theorems (Abrams and Lloyd, 1997; EL Azzaoui, 2020). Quantum computers utilize Quantum mechanical states of elementary particles, notably the internal angular momentum known as spin, to creates Quantum bits (Qubits). And according to Quantum physics law, a single Qubit holds a proportion of two values; 1, which accords to a spin up, and 0 for a spin down. Thus, a Quantum computer with n Qubits is capable of performing 2n Computations synchronously, leading to an exponential computation speed-up.

Quantum computers can be a promising solution to enhance the usability of big medical data by performing scalable complex computation and search algorithms on uninstructed data efficiently and improve the Quality of Service provided by intelligent healthcare systems. However, just like the early generation of classical computers, Quantum computers are scarce and likely to be expensive. To this end, we present in this paper a Blockchain-based delegated Quantum cloud architecture for medical big data processing and security. Blockchain is used for security purposes to select and authenticate the nodes that can participate, share, and use the Quantum service in the cloud. In addition, a Quantum server is hosted at the cloud layer to store and process medical-related big data securely, and Quantum Terminal Machines are used as a safe and cost-effective intermediate between classical users and Quantum servers at the cloud.

The following points summarize our main research contribution:

  • We propose a Blockchain-based delegated Quantum cloud architecture for secure medical data processing. Our proposed architecture is divided into three phases: the Blockchain-cluster generation phase, Quantum Terminal Machine phase, and the Quantum cloud-as-a-service phase.

  • Blockchain, as a distributed technology, secure communication between classical users such as smart hospitals, medical research institutions, and smart healthcare providers with the Quantum Terminal Machine at the edge layer. This phase generates secure authenticated clusters that can access the Quantum cloud and benefit from its computation power.

  • Quantum Terminal Machines, known as Quantum Images, is used as a secure medium between classical and Quantum cloud servers. Its primary role is to transform classical bits into Qubits and compile the results received by the Quantum cloud back to deciphered classical bits for the users.

  • Delegated Quantum cloud concept is utilized to securely compute patient sensitive data at the cloud layer while conserving the information secrecy (inputs and outputs) and computation security.

The rest of our proposed research paper is organized as follows; a brief background study that includes related works and the proposed architecture's consideration is depicted in the second section. The third section comprises the main idea overview along with the phase followed in the proposed architecture. A security analysis and performance evaluation are discussed in the fourth section. At the same time, the fifth section interprets a detailed discussion with the open research challenges. And finally, we conclude this work by the sixth section.

Section snippets

Related work

The complex nature of medical data urges the usage of a more powerful computation resource to reach the desired Quality of Service (QoS) and Quality of Experience (QoE). Quantum computers at the cloud layer are theoretically capable of providing fast and efficient computation and analysis of big medical data. In the following, we will discuss some of the main proposed ideas and protocols for Quantum Cloud-as-a-service.

System model

To secure medical data at the cloud level, improve the computation efficiency using Quantum technology, and solve the cost and feasibility dilemma of having Quantum machine at the user level, we propose in this paper a novel solution. Our proposed architecture can be divided into three layers: 1) Medical device layer, 2) Edge layer, 3) Cloud layer. The overview of the architecture is depicted in Fig. 1 bellow.

Quantum Machine Terminal

The Quantum Machine Terminal (QMT), also known as Quantum Image, is one of the main contributions of this paper. QMT is used as a medium between classical clients such as smart hospitals and Quantum Servers in the cloud. Thus, reducing the need to have a Quantum computer at the end-user level, which is not feasible in today's scenarios. Moreover, QMI enhances the security of communication between the client and the Quantum server using Quantum-based cryptography.

Evaluation and security analysis

To evaluate the first step (Blockchain-based Cluster Selection), we used Network Simulator-3 (ns-3), which relies on C++ to implement the smart city network models and Python for network topology. GO-Ethereum was deployed to implement the Blockchain. The simulation was performed on an intel core-i7 computer with 16 GB of RAM running under Ubuntu Linux. We put in use IBM Quantum Experience for the research's environment for the second and third steps. IBM Quantum Composer and IBM Quantum Lab

Conclusion

Quantum Computation in the cloud can surely provide the smart healthcare environment's desirable computation power and security. Our proposed Architecture deployed two leading technologies to create a better Quality of Service and assure better safety for smart healthcare. Blockchain will reduce the need of having a Quantum machine on the client-side, and it will provide secure access to honest devices and clients to the Quantum Cloud. Quantum Terminal (Quantum Image) at the edge layer will

Credit author statement

Abir EL Azzaoui: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Writing-Original Draft, Writing-Review & Editing. Pradip Kumar Sharma: Writing-Original Draft, Visualization. Jong Hyuk Park: Supervision, Project administration.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

This work was supported by the Survey and analysis of quantum information technology trends and regional strategy establishment research services Project funded by the Gangwon Technopark.

1. Abir El Azzaoui received a B.S. degree in computer science from the University of Picardie Jules-Verne, Amiens, France, and a master's degree in computer science and engineering, from Seoul National University of Science and Technology, Seoul, South Korea. She is currently pursuing her Ph.D degree in computer science and engineering, Seoul National University of Science and Technology with the Ubiquitous Computing Security (UCS) Laboratory, under the supervision of Prof. Jong Hyuk Park. Her

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    1. Abir El Azzaoui received a B.S. degree in computer science from the University of Picardie Jules-Verne, Amiens, France, and a master's degree in computer science and engineering, from Seoul National University of Science and Technology, Seoul, South Korea. She is currently pursuing her Ph.D degree in computer science and engineering, Seoul National University of Science and Technology with the Ubiquitous Computing Security (UCS) Laboratory, under the supervision of Prof. Jong Hyuk Park. Her current research interests include Quantum communication, Post-Quantum security, Blockchain, Internet-of-Things (IoT) security, and cloud security. She is also a reviewer of IEEE Access journal.

    2. Dr. Pradip Kumar Sharma is an Assistant Professor in Cybersecurity in the Department of Computing Science at the University of Aberdeen, UK. He received his Ph.D. in CSE (August 2019) from the Seoul National University of Science and Technology, South Korea. He also worked as a Postdoctoral Research Fellow in the Department of Multimedia Engineering at the Dongguk University, South Korea. He was a Software Engineer at MAQ Software, India, and involved on variety of projects, proficient in building largescale complex data warehouses, OLAP models, and reporting solutions that meet business objectives and align IT with business. He has published many technical research papers in leading journals from IEEE, Elsevier, Springer, MDPI, etc. Some of his research findings are published in the most cited journals. He has been an expert reviewer for IEEE Transactions, Elsevier, Springer, and MDPI journals and magazines. He is listed in the world's Top 2% Scientists for citation impact during the calendar year 2019 by Stanford University. Also, he received a top 1% reviewer in computer science by Publons Peer Review Awards (2018), 2019, Clarivate Analytics. He has also been invited to serve as the technical programme committee member and chair in several reputed international conferences such as IEEE CNCC 202, CSA 20202, IEEE ICC 2019, IEEE MENACOMM′19, 3ICT 2019, etc. Currently, he is Associate Editor of Human-centric Computing and Information Sciences (HCIS), Electronics (MDPI), and Journal of Information Processing Systems (JIPS) journals. He has been serving as a Guest Editor for international journals of certain publishers such as IEEE, Elsevier, Springer, MDPI, JIPS, etc. His current research interests are focused on the areas of Cybersecurity, Blockchain, Edge computing, SDN, and IoT security.

    3. Dr. Jong Hyuk (James J.) Park received Ph.D. degrees in the Graduate School of Information Security from Korea University, Korea. He is a professor at the Department of Computer Science and Engineering and Department of Interdisciplinary Bio IT Materials, Seoul National University of Science and Technology (SeoulTech), Korea. He has published about 200 research papers in international journals and conferences. His research interests include the IoT, human-centric ubiquitous computing, information security, digital forensics, vehicular cloud computing, and multimedia computing. He is a member of the IEEE Computer Society, KIPS, and KMMS. He got the best paper awards from ISA-2008 and ITCS-2011 conferences and the outstanding leadership awards from IEEE HPCC-2009, ICA3PP-2010, IEE ISPA-2011, PDCAT-2011, and IEEE AINA-2015. Furthermore, he got the outstanding research awards from the SeoulTech, in 2014. He has been serving as the Chair, the Program Committee, or the Organizing Committee Chair for many international conferences and workshops. He is also the Steering Chair of international conferences–MUE, FutureTech, CSA, CUTE, UCAWSN, and World IT Congress-Jeju. He is editor-in-chief of Human-centric Computing and Information Sciences (HCIS) by KIPS, The Journal of Information Processing Systems (JIPS) by KIPS, and Journal of Convergence (JoC) by KIPS CSWRG. In addition, he has been serving as a Guest Editor for international journals by some publishers: Springer, Elsevier, John Wiley, Oxford University Press, Emerald, Inderscience, and MDPI.

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