Blockchain Papers

Krishna Devarapu

International audience

Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne

The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. On the one hand, blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. On the other hand, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature. First, we introduce a new conceptual architecture which integrates blockchain and AI specific for COVID-19 fighting. Particularly, we highlight the key solutions that blockchain and AI can provide to combat the COVID-19 outbreak. Then, we survey the latest research efforts on the use of blockchain and AI for COVID-19 fighting in a wide range of applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.

Amin Fadaeddini, Babak Majidi, Mohammad Eshghi

No abstract is available for this record.

Vivian Brian Lobo, Jetso Analin, Ronald Melwin Laban, Shraddha S. More

Owing to enlarged digital data obtainability and artificial intelligence (AI) progressions, there are quite a few occasions that can be reconnoitered in healthcare. Deep learning (DL) and inductive transfer practices are turning healthcare data- such as phantasmagorias and videotapes-into powerful data sources for predictive analytics. At the present time, patients fail to have entree to his/her individual medicinal records and hang around ignorant of data importance or prominence. This paper directs to offer a gestalt of AI and blockchain and exhibit a roadmap for a blockchain-assisted decentralized bionetwork of private healthcare data to expediate new methodologies to drug discovery and precautionary healthcare. A protected and crystal-clear disseminated marketplace of personal data by means of blockchain and DL technology will circumvent challenges faced by authorities of a given healthcare system and restore custody all across private records that includes medicinal documents back to humans. It also proposes a novel type of utility cryptotoken named LifeCoin, which can be produced through the stationing of data on the blockchain-assisted open market to streamline transactions and expedite inventive reward schemes.

Morgan P. McBee, Chad Wilcox

No abstract is available for this record.

Hsin Hua Kung, Yafang Cheng, Hsiu-An Lee, Chien‐Yeh Hsu

No abstract is available for this record.

Fadila Zerka, Visara Urovi, Akshayaa Vaidyanathan, Samir Barakat · 11 authors

The utility of Artificial Intelligence (AI) in healthcare strongly depends upon the quality of the data used to build models, and the confidence in the predictions they generate. Access to sufficient amounts of high-quality data to build accurate and reliable models remains problematic owing to substantive legal and ethical constraints in making clinically relevant research data available offsite. New technologies such as distributed learning offer a pathway forward, but unfortunately tend to suffer from a lack of transparency, which undermines trust in what data are used for the analysis. To address such issues, we hypothesized that, a novel distributed learning that combines sequential distributed learning with a blockchain-based platform, namely Chained Distributed Machine learning C-DistriM, would be feasible and would give a similar result as a standard centralized approach. C-DistriM enables health centers to dynamically participate in training distributed learning models. We demonstrate C-DistriM using the NSCLC-Radiomics open data to predict two-year lung-cancer survival. A comparison of the performance of this distributed solution, evaluated in six different scenarios, and the centralized approach, showed no statistically significant difference (AUCs between central and distributed models), all DeLong tests yielded p -val >0.05. This methodology removes the need to blindly trust the computation in one specific server on a distributed learning network. This fusion of blockchain and distributed learning serves as a proof-of-concept to increase transparency, trust, and ultimately accelerate the adoption of AI in multicentric studies. We conclude that our blockchain-based model for sequential training on distributed datasets is a feasible approach, provides equivalent performance to the centralized approach.

Md. Abdur Rahman, M. Shamim Hossain, Mohammad Saiful Islam, Nabil Alrajeh · 5 authors

Recent advancements in the Internet of Health Things (IoHT) have ushered in the wide adoption of IoT devices in our daily health management. For IoHT data to be acceptable by stakeholders, applications that incorporate the IoHT must have a provision for data provenance, in addition to the accuracy, security, integrity, and quality of data. To protect the privacy and security of IoHT data, federated learning (FL) and differential privacy (DP) have been proposed, where private IoHT data can be trained at the owner's premises. Recent advancements in hardware GPUs even allow the FL process within smartphone or edge devices having the IoHT attached to their edge nodes. Although some of the privacy concerns of IoHT data are addressed by FL, fully decentralized FL is still a challenge due to the lack of training capability at all federated nodes, the scarcity of high-quality training datasets, the provenance of training data, and the authentication required for each FL node. In this paper, we present a lightweight hybrid FL framework in which blockchain smart contracts manage the edge training plan, trust management, and authentication of participating federated nodes, the distribution of global or locally trained models, the reputation of edge nodes and their uploaded datasets or models. The framework also supports the full encryption of a dataset, the model training, and the inferencing process. Each federated edge node performs additive encryption, while the blockchain uses multiplicative encryption to aggregate the updated model parameters. To support the full privacy and anonymization of the IoHT data, the framework supports lightweight DP. This framework was tested with several deep learning applications designed for clinical trials with COVID-19 patients. We present here the detailed design, implementation, and test results, which demonstrate strong potential for wider adoption of IoHT-based health management in a secure way.

Mehdi Benchoufi, Doug Altman, Philippe Ravaud

Quality of clinical research is undermined by severe misconducts, errors, frauds, which are detrimental to the trust it should arouse. In this perspective article, we show how Blockchain may trace and control processes of Clinical Trials preventing from the above issues or at least discourage them since they would become traceable and opposable. Then, we propose a short and doable program where, amidst the complex stream of events that a Clinical Trials consist of, we select sensitive and misconduct-prone steps that could dramatically benefit from Blockchain, through either simple core features as traceability and incorruptibility of its data registration, or through more refined automation tools called Smart Contracts.

Selwan Abdullah, Steven Rothenberg, Eliot L. Siegel, Woojin Kim

No abstract is available for this record.

Jingqiu Gong, Shaofu Lin, Jingwen Li

Data provenance technology and right confirmation technology have received great attention in recent years, because data exposure and abuse have been a serious problem with the rapid development of smart device and hospital. Based on the traceability and unchangeable properties of blockchain, we propose a model of personal health-related application data provenance and use smart contract to ensure right confirmation. We find that the user condition and use-right of personal health data can be effectively confirmed by using data provenance. In addition, the possible future extensions to personal health data on provenance are discussed.

Peng Zhang, Maged N. Kamel Boulos

No abstract is available for this record.

Chayakrit Krittanawong, Albert J. Rogers, Mehmet Aydar, Edward Choi · 7 authors

No abstract is available for this record.

Ketan Paranjape, Mitchell Parker, David Houlding, Josip Car

Objective: This article aims to provide a primer on blockchain technology and implementation considerations for blockchain at healthcare institutions.  Results: After research and interviews, we developed a primer and a high-level implementation guide for healthcare systems exploring the use of blockchain technology.  Conclusions: The use of blockchain technology in health care is at a promising stage in development but blockchain-based applications are yet to be demonstrated as a viable platform for exchanging and reviewing information. Healthcare systems should be cautiously optimistic regarding the potential of blockchain and do a thorough business and technical diligence that is driven by targeted use cases to be successful. 

Francesco Verde, Arnaldo Stanzione, Valeria Romeo, Renato Cuocolo · 6 authors

No abstract is available for this record.

Talha Burki

No abstract is available for this record.

Qiuzi Huang, Shuyu Chen, Hui Zhao, Junhao Wen

With the rapid development of medical information services, the construction of intelligent hospitals is opening up a new mode of medical treatment in the health care industry. Medical data is gradually becoming more and more important, while it also faces some challenges, among which the most urgent problem to be solved is data security and privacy protection. In the construction of intelligent hospitals, the safety issues among the basic information of patients, the protection of medical information and inter-institutional information sharing have become the focus at this stage. Blockchain technology, with highly security, reliable architecture and algorithm design have operated stably in the financial industry for more than seven years. The related innovative technologies such as distributed ledgers, smart contracts, symmetric encryptions and consensus mechanisms are used widely in many fields. This paper will take the demonstration construction of Chongqing Intelligent Hospital as an example, which tries to combine the blockchain, homomorphic encryption and zero-knowledge proof technology to carry out the research on the security construction and data privacy protection of intelligent hospitals.

Eko Yunianto, Yudi Prayudi, Bambang Sugiantoro

Digital evidence handling and preservation are one stage of digital forensic process. This part is very crucial because digital evidence is the basis of digital forensic process. The credibility of digital evidence must be maintaned for law and court process. Process of preservation of digital evidence known as chain of custody (CoC). CoC is a document that used to ensure that digital evidence remains and does not change. Both during the investigation process until the completion of the forensic process. Electronic evidence documentation is different from digital evidence documentatation. The different are character and the metadata. Some adjustments need to be accomodated on system for digital evidence. Digital evidence is easy to change as well as its CoC document. It needs to be protected. A new technology is needed that can ensure integrity of digital evidence and CoC Document like the blockchain. In this study, digital evidence management will be built on the CoC concept with blockchain technology. More precisely, this design combines the framework of the Digital Evidence Bag (DEC) with blockchain technology. This prototype is known as the Blockchain Digital Evidence Bag (B-DEC). B-DEC utilizes the data storage integrity to accommodate digital evidence management that refers to DEC. In this case, the prototype will build on a smart contract based on Ethereum. The development of the DEC framework also will be adjusted to accommodate DEC applications in the blockchain.

StanislawPeter Stawicki, SagarC Galwankar, Sebastian Clarke, Iain Craig · 11 authors

Technological progress is reshaping multiple domains of human activity, from financial transactions to medical care.[1] This paradigm shift represents a global movement that will transform our lives for generations to come.[2] The democratization of decision-making capacity, including consensus-based mechanisms for transaction verification, will enable global implementation of projects that were previously not feasible because of the requirement for centralized control.[34] Blockchain represents a decentralized ledger technology that operates by consensus and serves to democratize decision-making processes and to disintermediate traditionally understood intermediaries.[1] According to Deutsche Bank forecasts, by mid-2020's, approximately 10% of the worldwide gross domestic product could be regulated by blockchain-based solutions.[5] It is estimated that more than $400 billion will be invested in this technology in 2019 to advance its capabilities.[6] Within this broader context, it is important to understand that cryptocurrencies and financial transactions constitute only one small aspect of the blockchain concept, which also incorporates areas like verification, transparency, encryption, and maintenance of data integrity.[378] Blockchain technology appears to be following a fairly typical pattern of adoption, with multiple early entrants into the increasingly crowded and competitive cryptocurrency space and the fast-growing sphere of blockchain-based applications.[91011] It is the latter that will help truly define, and be responsible for the societal impact of, “the era of distributed ledgers” that is under way.[1112] The primary goal of the strategic global partnership between Litecoin Cash Foundation (LCCF, https://litecoinca.sh/) and OPUS 12 Foundation, Inc. (O12FI, http://www.opus12.org/), is to leverage our collective resources to establish early leadership in the development and implementation of practical, real-life, blockchain-based solutions in academic and clinical medicine.[11314] The practicality of the dual blockchain utilization, featuring both currency and application layers, becomes apparent with the realization that the need for ongoing data processing relies on constant verification and encryption activity throughout the entire network of blockchain nodes.[113] Thus, the approach selected by the LCCF-O12FI consortium creates significantly more synergy than a single-track approach based on subcomponent strategy. Within this context, the technology provides not only a “digital wallet” functionality for currency exchange, but also different blockchain-based use cases incorporating academic and medical information. In one example, cell phones are ubiquitous in low- and middle-income countries (LMIC) whereas electronic health records are not. Older, less costly cell phone technology would suffice as only SMS capability is needed to utilize blockchain or cryptocurrency, enabling broad access to the populations of LMICs. Blockchain can support information exchange across disparate data types, while providing digital payments on a global scale and across borders. The functional dimension of introducing the primary currency feature of Litecoin Cash (LCC) cryptocurrency has the potential to bring tremendous benefits to the areas of the world where banking services (and infrastructure) are severely underdeveloped, yet basic components for the successful adoption of cryptocurrencies clearly exist (e.g., limited internet access and mobile devices capable of supporting blockchain transactions). Much like entire regions of the world that essentially “bypassed” landline-based telephony following the introduction of cellular networks, many localities stand to “bypass and leapfrog” traditional banking, and progress directly to distributed ledger technologies.[151617181920] There is growing recognition of the role of microeconomies and the critical need for efficient, dependable, accessible, safe, and scalable financial transactions and infrastructures, especially in low-resource regions, a topic that was recently recognized with a Nobel Prize in Economics.[2122] Of note, this does not necessarily preclude traditional banking firms from participation; however, they will need to adapt to new competitive pressures across economic realities for which high-resource environment models are not optimized. Ability to appropriately scale current blockchain capabilities will be critical to such implementations.[32324] Blockchain-based mechanisms also allow for crossover of monetary value from various loyalty cards and rewards programs, similar to currency exchange between different nations. Such reward points (mileage, car rental, and hotel stay) can then become an alternative subsidy for healthcare services. This can, for example, help establish a modernized barter system where a patient could use their “frequent flyer miles” to pay for medical costs, exchanging their reward points for “health care coins” through an intermediary exchange market. Institutions, such as nongovernmental organizations, could turn “flyer miles” used to shuttle staff between locations into vaccine and medical equipment purchases. Further, direct and real-time transparent payment for services in healthcare could lead to a reduction of both “intermediary” insurance companies and inefficiencies in the system. This streamlining would result in substantial healthcare savings, translating to lower costs, more access for patients, and decreased overhead with increased revenue for clinics, hospitals, and providers. Security of the blockchain (including various “side chains” and “layers”) is of paramount importance to ensuring trust and wider mainstream adoption of this technology.[252627] The inherent risk in the concept of distributed ledger “democratization” is the possibility of emerging inequality due to maldistribution of infrastructure responsible for the maintenance and ongoing operations of the blockchain.[2829] Within this broader topic area, our group previously described the risk of ill-intended, third-party actors to project massive bursts of “hashing power” and effectively take over the blockchain for a limited duration of time.[1] This, in turn, allows such destructive actors to “double spend” cryptocurrency output to the detriment of the broader populace.[114] To effectively prevent the risk of the blockchain being “hijacked,” the LCCF Developer Team devised an innovative paradigm of agent-based mining (e.g., the creation of new cryptocurrency) that helps ensure democratization of the LCC generation/transaction process while providing sustainable, long-term security of the distributed ledger.[14] Another significant advantage of this prototype mining technique is that it is not based on technologies that are becoming increasingly energy and resource inefficient, thus not requiring ever greater amounts of energy to generate diminishing amounts of block rewards (e.g., “coins”). The synergy between secure mining processes and the need for the highest possible levels of distributed ledger security creates a unique environment for the development of blockchain-based educational and medical applications. Our joint implementation framework of blockchain-based application layer includes clearly stated and reasonably achievable milestones, each defined within the broader contexts of adoption readiness and resource availability. Parallel to these developments will be the phased introduction of LCC as a voluntary medium of exchange for various international medical programs (IMPs) collaborating within our global network of institutions, providers, and clinical sites.[30] The initial step in the strategic LCCF-O12FI collaboration will be the development of a cryptography-based “Secure ID” (SID) that will serve as the foundation for the future developments. This SID will contain each user's unique identifying information, accessible only to the end-user (incorporating various best practices in cyber security such as 2-factor or multisource verification), and shareable for viewing and information verification only with end-user's designees. The SID will also serve as a “Secure Key” to access other, downstream blockchain-based applications including “Academic Activity Logger” (AAL) and “Credentialing Document Repository” (CDR). We will now discuss the development and implementation of AAL and CDR. The AAL will be the first step toward the integration of blockchain technology into real-life academic international medicine (AIM) applications. Powered by the global LCC network, the AAL will help record and track activities by faculty members, facilitating the categorization and quantification of academic efforts into the following subtypes: (a) teaching, (b) clinical medicine, (c) community/government interactions, (d) research, and (e) other/miscellaneous. Each entry will include the activity date/time/duration as well as basic description, with a number of generic entries available through a drop-down menu. Activities entered by academic faculty will then be analyzed periodically and will serve as a basis for resource mobilization and allocation. Access to the AAL will only be possible using the SID, thus making the AAL a logical extension and a springboard for subsequent LCC blockchain-based implementations. On this foundation, the CDR and ultimately a “basic electronic medical record” (BEMR, see below) will be constructed. Although the task of constructing a high-fidelity, immutable, and accurate ledger of academic activities will not be easy, certain steps can be taken to minimize the likelihood of “false claims.” Much like the blockchain-based cryptocurrency paradigm, a secure mechanism for consensus building and data verification can be constructed. Such a “network of trust” (NOT) is technically workable and analogous to how “pretty good privacy” keys were distributed at signing parties attended by people known to each other, and also similar to the way “secure socket layer” certificate authorities work.[3132] For example, if Party A's certificate is signed by some Party B who is trusted by Party C, Party C can trust Party A's certificate, etc. The next developmental step in our strategic plan will be the implementation of the CDR, where provider credentials will be securely uploaded and stored in decentralized fashion. These documents will follow predefined credentialing requirements by most institutions globally such as record of college education/graduation, professional school record/diploma, professional licensing/verification/certification, and any additional elements deemed important to the safe conduct of AIM efforts globally. Uploading of credentialing information will be voluntary, and access to this information will only be possible with the permission of the record owner, utilizing his or her unique SID. Optimally, this important credentialing instrument will help providers verify their identity, education, and qualifications, and ensure that appropriate standards are followed by all stakeholders. The end-result will be the provision of safe and efficient care to the patients worldwide. Similar to the academic activity verification process, there will be important challenges to consider before successfully implementing the global CDR. In principle, there will need to exist some form of “data onboarding” authority. This should be performed by a “verification agent” (e.g., independent organization/group) with equivalent authority to that which it takes to set up a legitimate record of specific type (e.g., a medical school diploma and medical board specialty certification). In terms of identity verification, for example, the level of diligence required is similar to that already present in “know your customer” legislation. The case for verifying professional credentials would be similar, including the process of independent data validation and certification. Again, this is technically possible with a NOT arrangement as mentioned above; however, there will be obvious limitations inherent to the workability of credential verification similar to traditional efforts already in place. If a practitioner is claiming to possess credentials from some credentialing provider, only that particular provider really has (and only should have) the authority to confirm that. At the same time, there must also be a mechanism to revoke trust and to hardwire time-defined recertification processes based on the expiry of records currently on file. The final step in the strategic LCCF-O12FI collaboration will be the development of a super secure, BEMR that could be deployed in low-resource environments, utilizing rudimentary portable device technology, and containing fundamental health information for each end-user. Much like the SID, information stored on the BEMR would be owned by the end-user and could be shared with healthcare providers only with the end-user's consent, requiring SID as the “Secure Key” to unlock information. We recognize the substantial challenges in the global implementation of this concept, especially with regards to the enormity of healthcare-related data (often from multiple systems and sources), the need for privacy, timely and accurate access, and verification of data. Other potential shortcomings, at this time, include the need for further development of the technology, limited availability of expert knowledge, significant gaps in public awareness, along with growth-related issues of scalability, security, and user adoption.[6] Nonetheless, it is our hope that the lessons learned from other blockchain application layers will serve as the foundation for successful development, evolution, and adoption of BEMR.[1] There are many other considerations related to blockchain technology implementations in healthcare. Although full discussion of such a broad topic is beyond the scope of this manuscript, certain key ramifications must be discussed in the context of the proposed O12FI-LCCF initiatives. Blockchain technology may be an important tool for increasing transparency of how charities collect and allocate funds, propelling a much leaner system that will benefit intended recipients to a much greater degree.[1] This application of the blockchain technology will help verify the integrity of an organization's operations such as the transparency regarding the proportion of contributions distributed to medical and educational causes versus the overhead. In turn, the public, philanthropic donors, and potential collaborators will be able to make more informed choices regarding where their contributions can be allocated most efficiently. Pharmaceutical companies may utilize blockchain to keep track of medications manufacturing and shipment, supply, expiration, and possible points of contamination.[33] By extension, similar technological approaches could be useful for tracking opiates in this age of epidemic prescription drug abuse.[34] In such cases, blockchain would make it easier to investigate and determine the source of access as the supply chain would become much more transparent. Various built-in data verification and safety features could also be used to prevent duplication of medications from different providers and other hazards that occur with polypharmacy. Furthermore, the same tracking approaches could be used to secure food supply chains and safeguard against disease outbreaks.[35] Contaminated food products could be quickly and more efficiently traced to specific farms, processing or packaging plants for immediate identification, and removal from circulation. When combined with potential applications for AIM and global health equity, blockchain-based applications could help catalyze further innovation. First, they can enable universal access to financial resources by removing third-party intermediaries and offering transparent, secure, and accountable means for AIM financing.[36] Next, they could help facilitate multilateral financing mechanisms dedicated to health system development and strengthening.[136] In addition, they could reduce fraud and corruption through the use of immutable, tamper-proof transaction ledgers.[136] Finally, entire new capital markets for healthcare data could be created, providing better access (and opportunities) to patients, institutions, governments, researchers, and other key stakeholders.[136] Additional benefit offered by any token with fixed or “capped” supply as a medium of international exchange – subject to harmonization with region-specific laws and regulations – is the noninflationary character of such cryptocurrency. This, in turn, may help provide end-users with a protective mechanism against inflation and loss of monetary value – a phenomenon experienced across many LMICs.[3738] In conclusion, the global partnership between OPUS 12 Foundation (including its allied partners and subsidiaries) and LCCF provides a unique platform for the parallel development of both global currency support framework and medical/educational application layer for the academic international medical community.

Rong Wang, Wei‐Tek Tsai, Juan He, Can Liu · 6 authors

In recent years, artificial intelligence (AI) has played an increasingly important role in the medical field. AI based on big data analysis and deep learning algorithms has become the core driving force for the future development of the medical industry, but the biggest obstacle to its development is incompleteness and inaccuracy of medical data. The main reason is that medical big data is difficult to achieve sharing. This paper studies and analyzes the problems of medical big data sharing, proposes a medical data sharing platform based on permissioned blockchains (BCs), which uses dual-BCs architecture (Account BC and transaction BC), Concurrent Byzantine Fault Tolerance (CBFT) consensus mechanism, encryption technology and smart contract technology. Account BC (ABC) is used to store user data hash after encryption and transaction BC (TBC) is used to process computing tasks. The use of encryption technology ensures that users have full autonomy in their own medical data. Smart contract technology is used to enable users to set up different access permissions of medical data. A TBC can be used by multiple ABCs and TBC does not save users' medical data, but only obtains users' medical data from ABCs when needs computation. When the computing task is completed, the TBC deletes all users' medical data and packages the operation record to save into ABCs, thereby it realizes data sharing while protecting users' privacy. In addition, this paper compares the functions with other medical data systems, analyzes and compares their advantages and disadvantages. Finally, the conclusions and future works of the medical data sharing platform based on BC technology are prospected.

Tsung-Ting Kuo, Rodney A. Gabriel, Lucila Ohno‐Machado

OBJECTIVE: Decentralized privacy-preserving predictive modeling enables multiple institutions to learn a more generalizable model on healthcare or genomic data by sharing the partially trained models instead of patient-level data, while avoiding risks such as single point of control. State-of-the-art blockchain-based methods remove the "server" role but can be less accurate than models that rely on a server. Therefore, we aim at developing a general model sharing framework to preserve predictive correctness, mitigate the risks of a centralized architecture, and compute the models in a fair way. MATERIALS AND METHODS: We propose a framework that includes both server and "client" roles to preserve correctness. We adopt a blockchain network to obtain the benefits of decentralization, by alternating the roles for each site to ensure computational fairness. Also, we developed GloreChain (Grid Binary LOgistic REgression on Permissioned BlockChain) as a concrete example, and compared it to a centralized algorithm on 3 healthcare or genomic datasets to evaluate predictive correctness, number of learning iterations and execution time. RESULTS: GloreChain performs exactly the same as the centralized method in terms of correctness and number of iterations. It inherits the advantages of blockchain, at the cost of increased time to reach a consensus model. DISCUSSION: Our framework is general or flexible and can also address intrinsic challenges of blockchain networks. Further investigations will focus on higher-dimensional datasets, additional use cases, privacy-preserving quality concerns, and ethical, legal, and social implications. CONCLUSIONS: Our framework provides a promising potential for institutions to learn a predictive model based on healthcare or genomic data in a privacy-preserving and decentralized way.

Peter Williams

New technologies and the knowledge economy are destabilising graduate professions, with artificial intelligence and the analysis of ‘big data’ making significant impacts on formerly secure jobs. Blockchain technology, offering automated secure credentialling of undergraduate students’ activities and achievements, may significantly erode existing systems of assessment. The challenge for universities will be not only to maintain the relevance of their curricula but also to manage erosion of their current near-monopoly in awarding degrees. This paper envisions a landscape in which universities must outsource parts of their course delivery and assessment in order to remain competitive. It examines a potentially sustainable mission strategy: to move away from narrow academic disciplines towards an authentic learning curriculum focusing on the development of students as whole persons with rounded educations. This paper examines implications for the academy of the convergence of artificial intelligence, data analytics and blockchain technology.

Tsigab Angosom Gebremedhin

Fear of stigmatization and discrimination from colleagues, friends and family drives patients with various type of mental health problems away from a traditional face-to-face therapy and enforces them to look for an alternative treatment methods. Internet-based mental health therapy helps patients to get their needed therapies and support from healthcare professional and peers, or as a part of automated online form of therapy. Conducting Internet based therapy anonymously is vital for the patient privacy. However, lack of trust, access permission, ownership control and traceability undermines patient safety and security. Blockchain technology is an innovative technology initially designed for a cryptocurrency. However, with the introduction of programming blockchain and smart contracts, the technology has extended its importance to other areas for developing decentralized application (DApp), such as mental health related information management, which is the primary focus of this thesis. Privacy and security are very crucial for patient safety and to preserve patient’s medical history from adversaries. Sharing of private medical information online between the patient and their respective provider contains sensitive information that can easily be compromised if a proper security measure is not put in place. Blockchain is consensus-based peer-to-peer distributed ledger technology that stores and maintains an updated copy of all transactions within the network. It makes trust more transparent and traceable by keeping auditable-logs of all transactions in the form of blocks. In this thesis, Blockchain and its underlying technology are studied, and a prototype has been developed to explore the potential of the blockchain technology. Furthermore, we explore alternative distributed ledger technologies and their respective security models such as consensus protocols, cryptographic techniques, privacy and scalability. The prototype was proposed based on Ethereum blockchain.

Manish Chand, Navin Ramachandran, Danail Stoyanov, Laurence Lovat

No abstract is available for this record.