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Trusted Remote Patient Monitoring using Blockchain-based Smart Contracts

  • GC University sialkot

Abstract and Figures

With an increase in the development of Internet of Things (IoT), people have started using medical sensors for health monitoring purpose. The huge amount of health data generated by these sensors must be recorded and conveyed in a secure manner in order to take appropriate measures in critical conditions of patients. Additionally , privacy of the personal information of users must be preserved and the health records must be stored in a secure manner. Possession details of IoT devices must be stored electronically for eradication of counterfeited actions. The emerging blockchain is a distributed and transparent technology that provides a trusted and unalterable log of transactions. We have made a healthcare system using blockchain-based smart contracts which supports enrolments of patients and doctors in a health centre thereby increasing user participation in remote patient monitoring. Our system monitors the patients at distant places and generates alerts in case of emergency. We have used smart contracts for authorization of IoT devices and provided a legalised and secure way of using medical sensors. Using the blockchain technology , forgery and privacy hack in healthcare setting is reduced thereby increasing the trust of people in remote monitoring. We have provided graphical comparison of costs that verifies the successful deployment of contracts.
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Trusted Remote Patient Monitoring
Using Blockchain-Based Smart Contracts
Hafiza Syeda Zainab Kazmi1, Faiza Nazeer2, Sahrish Mubarak3,
Seemab Hameed2, Aliza Basharat2, and Nadeem Javaid1(B
1Department of Computer Science,
COMSATS University, Islamabad 44000, Pakistan
2Department of Computer Science,
Government College Women University, Sialkot 51141, Pakistan
3Department of Computer Science, University of Lahore,
Lahore 54590, Pakistan
Abstract. With an increase in the development of the Internet of
Things (IoT), people have started using medical sensors for health mon-
itoring purpose. The huge amount of health data generated by these
sensors must be recorded and conveyed in a secure manner in order to
take appropriate measures in critical conditions of patients. Additionally,
privacy of the personal information of users must be preserved and the
health records must be stored in a secure manner. Possession details of
IoT devices must be stored electronically for eradication of counterfeited
actions. The emerging blockchain is a distributed and transparent tech-
nology that provides a trusted and unalterable log of transactions. We
have made a healthcare system using blockchain-based smart contracts
which support enrollments of patients and doctors in a health center
thereby increasing user participation in remote patient monitoring. Our
system monitors the patients at distant places and generates alerts in
case of emergency. We have used smart contracts for authorization of its
devices and provided a legalized and secure way of using medical sensors.
Using the blockchain technology, forgery and privacy hack in healthcare
settings is reduced, thereby increasing the trust of people in remote mon-
itoring. We have provided a graphical comparison of costs that verifies
the successful deployment of contracts.
Keywords: Remote patient monitoring ·Healthcare ·IoT ·
Blockchain ·Smart contracts ·Privacy
1 Introduction
In recent years, fast growing popularity and extensive development in Inter-
net of Things (IoT) can be witnessed. IoT is being used in smart cities, smart
Springer Nature Switzerland AG 2020
L. Barolli et al. (Eds.): BWCCA 2019, LNNS 97, pp. 765–776, 2020.
766 H. S. Z. Kazmi et al.
cars, wearables, e-business and healthcare. Considerable increase in the num-
ber of medical patients has been observed in various countries. IoT and wear-
able devices have enhanced the patient monitoring quality and a large num-
ber of patients can be monitored remotely. Remote Patient Monitoring (RPM)
allows the monitoring of patients outside the health centre thereby increasing
the patient care and decreasing the appointments time and cost. The core func-
tionality of RPM is the monitoring of patients through wearable devices and
transmission of health readings for diagnosis and treatment. Healthcare devices
are divided into the following types [1]:
Stationary: Devices having physical location e.g., remote chemotherapy
Embedded: Implanted devices in a body e.g., deep brain stimulation
Wearable: Body-worn devices e.g., insulin pump
As RPM is growing world-wide, concerns about secure transmission of Electronic
Health Record (EHR) is increased. The sensitive health data can be accessed
by unauthorized parties, so there is a motivation to secure the medical data
transmission [2]. SCs are used to maintain immutable log of the transactions
being made in RPM. Automatic health notifications using blockchcin increases
trust of patients in wearing medical sensors or devices.
2 Motivation and Problem Statement
The authors of [3] used blockchain for security and privacy preservation of EHR.
The authors used private and consortium blockchains for tackling the privacy
leakage issue of sensitive health data. Private blockchain is used to store the
Protected Health Information (PHI) whereas, consortium blockchain maintains
the indexes of the health record.
The authors of [4] have proposed a model for sharing medical information
exploiting the advantages of blockchain. They have used digital signatures for
protection of medical information against forgery and unauthorized access. Med-
ical information contains record number, date, time, doctor ID, patient name,
patient address, clinical health status, certificate ID and the digital signature
of the record. The authors concluded that blockchain technology is reliable and
provides traceability for medical data sharing.
Researchers are reluctant to share their data due to protection concerns. A
mechanism for stating terms of reuse of digital content is presented in [5]. The
authors used blockchain and SCs for research data rights management. They
maintained the agreements regarding digital content between the authors and
users in order to verify the reuse of data. Externally Owned Accounts (EOA)
for protection of data are used.
The authors of [6] used data masking for data privacy and implemented IPFS
for a secure EHR. The patient data used for data masking consists of name,
age, ID, address and disease. However, they have used data masking instead of
encryption. As the data volume increases, data masking time will also increase.
Trusted Remote Patient Monitoring 767
The use of IoT devices based is increasing day by day thereby enhancing the
comfort and lifestyles. The authors of [7] have suggested the use of blockchain
technology for securing the IoT devices from tampering and unauthorized access.
However, they have used the hyperledger for implementation instead of using
ethereum platform. Hyperledger uses no cyptocurrency and the transactions are
confidential, not transparent. Moreover, they have not considered authorizing
the enterprise who made the device (manufacturer) and device user’s in order to
avoid the counterfeited actions.
Remotely monitoring the patients helps in decreasing the cost thereby
increasing the patient care outside the health centres. The increased number
of IoT devices poses various privacy and security issues in a healthcare setting
where confidentiality of patients’ information must be maintained. The authors
of [2] have used blockchain-based SCs for preserving the health data received
from medical sensors. However, they have not maintained the profiles of patients
and medical professionals that are enrolled in a health centre because of the pri-
vacy leakage issue and people will be unwilling to provide personal data. A forged
or fake device can be risky for a patient and the log of device authorization must
be maintained without involving a third party.
The problems we have identified include: personal information privacy con-
cerns and risky devices of patients.
2.1 Contributions
We have written the following blockchain-based SCs for healthcare system:
Patients and Doctors Enrollments: The personal information of patients and
doctors is sent using EOAs due to privacy concerns.
Patients Health Monitoring: The health data of patient is analyzed and timely
alerts are relayed to the patients, doctors and helath centres. For patients’
health tracking, we have implemented the following modular SCs:
1. Blood Pressure Monitor
2. Temperature Monitor
3. Blood Oxygen Monitor
4. Brain Inflammation Monitor
Enterprise: This SC will be initialized by the enterprise whenever a device is
made and it will facilitate the tracking and maintenance of the device log.
IoT Device Authorization: The log of device’s original and new custodian
records or licences are maintained along with IoT device details in a decen-
tralized manner using SCs eliminating the participation of third party.
The paper is organized as follows: Detailed literature review is given in Sect. 3.
Section 4describes the proposed methodology. The experimental results and
evaluation of the proposed work is given in Sect. 5. Finally, Sect. 6concludes
the paper.
768 H. S. Z. Kazmi et al.
3 Related Work
Authors of [3] tackled the privacy and security issues of EHR sharing using
the immutable blockchain technology. Private and consortium blockchains are
used for PHI sharing thereby increasing the privacy. The data is encrypted with
keyword search. The proposed scheme achieved better data security and control
over data access.
Medical research is increasing with an increase of medical accidents [4].
Healthcare is facing many threats like forgery, unauthorized access and record
tracking. The authors used provided verification of the proposed solution
and concluded that the medical information is reliable and traceable using
blockchain. Their data recovery function helps save the medical information
against alteration.
Electronic Medical Records (EMRs) provide a way to store a huge amount of
sensitive medical data yet it is difficult to share the personal data among health
centres due to privacy concerns [6]. Blockchain provides a secure, trustworthy and
tamper resistent maintenance of health records thereby enhancing data sharing.
It is not feasible to store a huge amount of data on blockchain so, an IPFS storage
is used to store the confidential data after masking. The solution provided data
privacy due to data masking and the blockchain resources are saved using IPFS.
Medical records are an essential element of our lives and a considerable
increase can be witnessed in the medical big data [1]. RPM is based on the
wearable sensors which is helpful in providing healthcare services to patients.
There are many risks involved in the trafer of confidential data that can be
life threatening for patients. The authors have tackled the privacy leakage issue
using blockchain and the data generated by IoT devices is made anonymous.
The authors of [7] have maintained immutable logs of the IoT devices con-
figurations. The history of modifications is stored and made available for the
administrators. The model helps enterprises in tracking the device configuration
changes using the decentralized, secure and trusted blockchain technology.
To avoid security vulnerabilities in RPM, a trackable and unchangeable trans-
actions log must be maintained. The authors in [2] have used private blockchain
to store the health record transactions. The health reading taken using sensors
are evaluated based on threshold values. Health alerts are generated and sent to
the patients and hospitals. The emerging blockchain technology helped greatly
in protecting the EHR of patients.
Protection of medical data is an important factor to be catered for smoothly
executing the medical activities. The two main data protection strategies can be
used; one is access control and other is encryption. Access control mechanisms
can be applied on locally stored data however it can be tampered on local stor-
age. The encryption of data using key has a disadvantage of losing the key in
case of patient’s death. The authors in [8] have used Sibling Intractable Func-
tion Families (SIFF) that provides a shared key. Hyperledger fabric is used for
implementation and better efficiency is achieved.
People will be unwilling to participate in a RPM system due to the privacy
hack issue. The authors in [9] have proposed a conceptual model to manage the
Trusted Remote Patient Monitoring 769
health data using the distributed blockchain technology. In traditional setting,
patients were not allowed to view or manage their own data. The proposed model
guaranteed the data integrity by allowing patients to gather PHI. Blockchain is
a peer-to-peer network that eliminates the third party. The authors of [10]have
worked on IoT-enabled WSNs and achieved efficient routing. The authors of [11
20] have implemented blockchain in various domains like IoTs, healthcare, smart
grids and crowd sensing networks. They have concluded that blockchain is an
effective solution for data trading, remote patient monitoring, energy trading,
malicious node detection, electric vehicles and IoT service provisioning.
4 Proposed Solution
In our scenario, medical sensors are embodied on patient’s body and the health
readings are sent to the specific SC via an master device i.e., a smart phone.
The patient profiles are managed by health centre using SCs. Patient’s health
status is analyzed according to the data being received. Health data is stored on
a decentralized IPFS storage. Patients and doctors are able to register or enrol
themselves using the master device. The health centre is in charge to authorize a
patient for a doctor. Additionally, IoT device possession details are also recorded
in SCs. Whenever an enterprise manufactures a device, SCs are made by both
the enterprise and the patient who takes possession of the device. The main SCs
named patient monitoring, enrolments, enterprise and IoT device authorization
are discussed below in detail.
4.1 Enrollment
Health centre initializes enrolments SC on the blockchain for initiating the doc-
tors and patients’ registrations. The enrolments contract consists of enrolment,
modification and authorization functions. As shown in Fig. 1, health centre entity
generates a public and a private key. Then, it posts the SCs address on the
smart phone for patients and doctors to get registered easily in a secure way.
The patient and doctors register in a health centre using their own EOAs via
SCs address using addpatient() and adddoc() functions. The information taken
from patient and doctors includes id, name, address and age and is made secure
using EOA due to privacy concerns. Personal information is made private so
that patient and medical assistants do not suffer from confidential information
theft. In this way, patients and doctors will not be reluctant to enroll themselves
due to the fear of privacy leakage and participation in the health system will be
increased. The enrolments contract also allows the modification of information
of both patients and doctors using modifypatient() and modifydoc() functions.
Also, only a specific doctor is allowed to check the health status of a patient.
The health centre maintains a list of doctors and can authorize and deautho-
rize a doctor from monitoring a patient’s health using authorize() and deautho-
rize() functions. Patients can view their information and authorized doctors by
means of EOA. The enrolment, modification and patient authorization details
770 H. S. Z. Kazmi et al.
can be seen or retrieved by patientdetails(),doctordetails(),authorizedpatientde-
tails() and deauthorizedpatientdetails() functions in enrolment SC.
4.2 Patient Monitoring
For patients’ monitoring, data received from the smart device is handled by the
main SC named as HealthContractCaller. Then, the main patient monitoring
or HealthContractCaller contract creates a specific contract for every individual
device it is getting data from. The main contract is like a container that orga-
nizes and creates links among all devices and relevant subcontracts for patient
monitoring as shown in Fig. 1. Authorized doctors are allowed to access patients’
information and will be able to change thresholds for monitoring purpose.
For instance, if the smart device receives blood pressure data from a patient’s
body sensor, the data will be sent to HealthContractCaller and subsequently,
BloodPressureMonitor() function will be called for patient monitoring. Minimum
and maximum blood pressure values will be sent by the device to this function
and an object is created by this function. Then, the individual sub contract
Blood Pressure Monitor will pass these values to its analyze() function in order
to evaluate the received data. Response upon the incoming data is generated
by subcontracts instead of regulating it to the main contract. If the analyze()
function returns any other value other than zero (0) or “OK”, then an alert
(e.g. high/low blood pressure) is sent to the patient, doctor and health centre
for treatment. The subcontracts we have used to monitor patient status include:
Heart Rate Monitor, Glucose Monitor, Blood Pressure Monitor, Temperature
Monitor, Blood Oxygen Monitor and Brain Inflammation Monitor. The moti-
vation of modular contracts i.e., Heart Rate Monitor and Blood Sugar Level is
taken from [2]. Whereas, we have proposed the use of other four subcontracts.
The stated subcontracts analyse the real time heart rate, sugar level, fever, oxy-
gen level in blood and brain inflammation measured using the body sensor of
the patient based on specific threshold values. These modular contracts provide
uncomplicated, trouble-free and simple maintenance. These modules will allow a
customized structure where any subcontract for a specific device can be changed
without changing the functionality of others.
4.3 Enterprise and Device Authorization
There are two types of SCs for device authorization, one is of the enterprise and
other is of the device custodian. Here, IoT device refers to the wearable body
sensor of the patient. The patient having that IoT device is referred as custodian
of the device. Device must be registered and the custody must be recognised. The
patient who buys a device must get registered and the device credentials must
be legalised. In traditional systems, the contracts were made by involving a third
party e.g., a bank. However, third parties are run by people that can be deceitful.
We have established device credential management by removing the third party
through SCs. The original custodian or the enterprise who manufactured the
device make a SC named newdevice() after the production of device as shown
Trusted Remote Patient Monitoring 771
PaƟent Monitoring
PaƟent and Docto r
IoT Devic e
Smart Contracts
Health Centres
Health Alert
Body Sensors
Publis h SC Address
Enroll using EOA
Enroll using EOA
Health Readings
Get SC Address
Get SC Address
Details and
Health Alert
Device Deta ils and Transfer
Fig. 1. Blockchain-based healthcare system
in Fig. 1. Whenever a patient buys that medical device, it must make a contract
to get registered as the custodian of device. The device custodian also initiates
a SCs and stores device information like device name and device description. In
this way, device management will be done by the patient. The device custodian
can set access conditions and transfer the device possession to other parties in a
decentralized manner. The transfer of possession function changes the possession
using the current (registered) and new custodian (to be registered) address and
change the credentials of the device. The updated IoT device and custody details
will also be sent to the health centre.
5 Results
The specifications of the system used are: CPU@1.61 GHz, 8 GB RAM, 64 bit
operating system and X64-based processor. We have used ethereum platform
and solidity language for writing our SCs. The contracts are made operational
on the private blockchain using ethereum protocol. We have used open source
web browser environment Remix to test, debug and deploy our SCs. Metamask
browser extension is used for connectivity to distributed web.
Whenever an ethereum transaction takes place on the blockchain, two types
of costs are associated with it; one is the transaction cost and the other is
execution cost. The blockchain network has the potential to increase trust by
reducing the transaction costs because of its decentralized nature with no third
party involved.
772 H. S. Z. Kazmi et al.
Transaction cost: It includes the cost of data being sent, operations being
performed and the storage of contract. Transaction cost is determined by
gasUsed×gasPrice where gasPrice is specified by the user and gasUsed refers
to the total gas used for operations.
Execution cost: This cost refers to the storage of local and global variables as
well as the processing power for calculations.
Figure 2shows the transaction and execution costs of all SCs. SCs are shown
on the x-axis and their gas consumption on y-axis. Enrollment of patients and
doctors shows the costs about 2692790 gas and 1986938 gas in transaction and
execution of the contract. Monitoring and IoT device SCs cost less gas as com-
pared to other contracts because the number of inputs fed to the monitoring
contract are less than the inputs fields given in enrolments. More gas consump-
tion in enrolments depicts a huge internal storage because the more data sent
to the contract, the more cost it takes. Enterprise contract deployment took
1308577 as transaction and 950029 as execution cost. Less costs are recorded in
the deployment of IoT device and monitoring contracts that shows that these
contracts are logically less complex.
Fig. 2. SCs deployment
Figure 3shows the subcontracts being called by the main monitoring contract
on x-aix and the gas consumption on y-axis. The reason behind the deployment of
six subcontracts is to check the amount of gas consumption for patients having
more than 2 body sensors. These modular contracts cost less than the main
contract because breaking the contract up into subcontracts decreases the cost
during interaction. There is a slight difference in all contracts costs because the
modular concept makes the computation simple and the data types used in all
modular contract are almost same. However, the subcontract consuming the
Trusted Remote Patient Monitoring 773
Fig. 3. Patient monitoring modular SCs deployment
Fig. 4. Enrollments functions costs
least transaction and execution gas is due to the reason that instances are using
uint type instead of expensive types. This saves the blockchain from expensive
storage of variables in terms of gas for a transaction.
Figure 4displays the costs of transaction and execution made by all func-
tions of the enrolment SC. Adding the doctors and patient information cost
about 236109 and 235845, respectively which is relatively high as compared to
the costs of transactions in other functions. The execution costs of adding doctor
774 H. S. Z. Kazmi et al.
Fig. 5. IoT device functions costs
and patient are recorded as 209333 and 209069, respectively. The reason behind
high costs is that the larger transactions require a huge amount of fee. Trans-
action costs of authorization, deauthorization, doctor modification and patient
modification are 45832, 15788, 54365 and 54541, respectively. Execution costs of
these four functions are 21744, 6700, 27589 and 27765. These functions consume
less gas because smaller transactions are simpler to validate and consequently,
consume less gas.
Figure 5displays the gas consumption by IoT device contract where the
device contract is created and the possession is transferred from one custodian
to the other. When the possession is transferred, new owner will be allowed to
change the description of the device. The details are updated costing 30021 and
25357 transaction and execution fee. The possession is successfully transferred
consuming 27398 transaction gas whereas the failed transaction ended up con-
suming 23164 transaction cost. When the transfer is successful, the execution
cost is recorded as 5710 and if the same owner registers for the device again, the
transfer is failed consuming 484 execution costs.
6 Conclusion and Future Work
Remote medical care rapidly increasing with an increase in the use of IoT devices.
For improved health services, only the transfer of health status and patients
personal information is not enough rather an immutable record should be main-
tained. We have used blockchain for a secure and permanent log of health and
personal data of patients. The unchangeable nature of blockchain enables us to
keep track of unauthorized alterations to healthcare system. We have written SCs
using ethereum and provided patients and medical professionals with a secure
way of enrolling themselves in a health centre. The health centre maintains the
Trusted Remote Patient Monitoring 775
list of enrolled patients and authorizes them to medical assistants for treatment.
The medical device custody is verified through SCs and enabled the device cus-
todian to transfer the possession of device to other patients. The results show
the costs of all smart contracts and verify the successful deployment of the con-
tracts. For the future work, we aim to implement prescription review system in
which patients will be able to give reviews on doctor’s prescription. This system
will help the hospitals to get an idea of the reputation of the doctors. We will
also give a secure solution for medical data storage because blockchain is not
suitable for a huge amount of storage.
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... Table 7 shows that studies in [42]- [48], focus on BC-based IAM for MIoT devices, while other studies [49]- [65], include IAM in BC-based solutions for different HIoT applications. Studies in, [47], VOLUME 10, 2022 [48], [63], [64], proposed AuthN solutions, while studies in [42], [43], [50], [54], [55], [58], [59], [65] proposed AuthZ solutions. The rest of the studies [44]- [46], [49], [51]- [53], [56], [57], [60]- [62] covered both AuthN and AuthZ solutions. ...
... There are multiple HIoT-based e-Health applications covered in the 24 reviewed studies. In [49], [59], and [60], IAM solutions were proposed for HIoT-based EHRs, while in [50], [55], [56], IAM solutions were proposed for RPMS. In [53], [62], and [64], IAM solutions were proposed for DHS. ...
... Not all BC technologies can satisfy non-financial applications, as cryptocurrency is still the core substance of the majority of BC technologies, except the few as shown in Table8. The results showed that the most used BC technology is Ethereum [42]- [44], [47], [48], [51], [52], [55], [58], [59], [63]- [65], which is a cryptocurrency-based permissionless peer-to-peer network, followed by Hyperleger Fabric [46], [49], [50], [53], [54], [56], [57], [60]- [62], which is a permissioned BC technology. In permissioned BCs, only chosen and known participants can access data, whereas in permissionless BCs, all participants in the network can access data. ...
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... The continuous patient monitoring data were not intended for use in the model Kazmi et al. [125] The licensing of medical personnel and equipment for remote patient monitoring is managed and controlled by smart control When obtaining data from wearable sensors, security and privacy concerns were disregarded ...
... Kazmi et al. [125] created a blockchain-driven remote monitoring platform that used smart contracts to register patients as well as healthcare providers and grant permits for wearable sensors. In addition, the software can provide a genuine notice, encouraging consumers and healthcare professionals to participate in patient surveillance. ...
Existing blockchain approaches exhibit a diverse set of dimensions, and on the other hand, IoT-based health care applications manifest a wide variety of requirements. The state-of-the-art analysis of blockchain concerning existing IoT-based approaches for the healthcare domain has been investigated to a limited extend. The purpose of this survey paper is to analyze current state-of-the-art blockchain work in several IoT disciplines, with a focus on the health sector. This study also attempts to demonstrate the prospective use of blockchain in healthcare, as well as the obstacles and future paths of blockchain development. Furthermore, the fundamentals of blockchain have been thoroughly explained to appeal to a diverse audience. On the contrary, we analyzed state-of-the-art studies from several IoT disciplines for eHealth, and also the study deficit but also the obstacles when considering blockchain to IoT, which are highlighted and explored in the paper with suggested alternatives.
... Kazmi et al. [122] created a remote monitoring system for patients using smart contracts on blockchains to enroll patients and healthcare providers, license wearable sensors, and deliver additional services. It can send out an emergency notice in real-time, encouraging consumers and healthcare professionals to participate in remote patient monitoring. ...
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p>This is a review of research challenges and opportunities for post-quantum blockchains in the IoT. </p
... Kazmi et al. [122] created a remote monitoring system for patients using smart contracts on blockchains to enroll patients and healthcare providers, license wearable sensors, and deliver additional services. It can send out an emergency notice in real-time, encouraging consumers and healthcare professionals to participate in remote patient monitoring. ...
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p>This is a review of research challenges and opportunities for post-quantum blockchains in the IoT. </p
... A legal and secure way can be achieved through sensors that use smart contracts to authorize devices. By using Blockchain technology, people's confidence in remote monitoring can be increased by reducing fraud and privacy violations in healthcare environments (Kazmi et al. 2019). ...
The rapid development of artificial intelligence in recent years has led to an increase in artificial intelligence-based applications in many areas. One of the important application areas of artificial intelligence has been the field of Financial Technology (Fintech) and artificial intelligence has been widely integrated into financial services. Artificial intelligence-based Fintech applications such as workflow automation, fake and fraud detection, algorithm-based asset management (robo advisors), and intelligent consultant provide significant benefits to the finance industry. Fintech applications, which means using technology to improve financial services, may cause financial risks, despite its many benefits. Especially after the 2008 Global Crisis, it is observed that there are significant deficiencies in the regulation and supervision of financial markets. In this context, regulatory technologies (Regtech) are needed in order to eliminate deficiencies and minimize financial risks. In other words, developments in Regtech make secure the improvement of Fintech. The main purpose of Regtech is to find technological solutions that help regulate Fintech without harming their positive potential. Therefore, Regtech allows both an effective financial risk management and provides significant cost saving. In order to fintech and supervision authorities to get maximum efficiency, it is very important that the application processes of Regtech are standardized and technology-oriented. The purpose of this study is to provide an overview of how artificial intelligence will transform the financial system. It is also to discuss how financial technologies (Fintech) and regulatory technologies (Regtech) will be affected by this transformation.
Healthcare is an emerging sector with the integration of emerging technologies aiming to improve Quality of Life of an individual through various medical services. Most of the healthcare services work with sensitive information of patients either collected in real-time using body implanted sensors or through various IoT enabled medical devices during the diagnosis in a centrally controlled model. But, the traditional IoT based medical services suffer from several challenges such as data security, privacy, interoperability, single point of failure, scalability, and data integrity. However, by considering the advantages of Blockchain technology and the disadvantages of IoT systems, the amalgamation of a decentralised, distributed ledger technology with the IoT for various healthcare applications will strengthen the system by resolving the major challenges. Thus, this research article conducts a comprehensive survey on the integration of Blockchain and IoT (BCIoT) for Healthcare services, focusing mainly on existing approaches, possibilities, applications and challenges. First, we present a detailed overview of Blockchain, IoT and the motivation for BCIoT along with the survey on existing healthcare applications. Next we discuss the enabling platforms for BCIoT based healthcare services. For the better understanding, we review the role of BCIoT in Remote patient monitoring, electronic heath record management, Health asset tracing, Covid-19 infected patient contact tracking. Finally challenges and future directions are discussed to improve the Quality of Life of patients through Healthcare applications.
Internet of Things (IoT) reshapes the incumbent industries into smart industries by bringing more opportunities with efficient decision making. The fundamental characteristics of IoT make the system to face various challenges such as poor interoperability, decentralization, heterogeneous data, diversified devices, network complexity, and security related issues. Blockchain technology overcomes the challenges of IoT by maintaining a digital ledger in the distributed systems. The convergence of IoT and blockchain technology synthesizes a novel paradigm that improves production throughput, operation efficiency, and product quality. During the complete procedure, privacy is preserved using blockchain which manages individual data, data sharing among hospitals, insurance companies, and medical centers. Blockchain acts as an interface or repository among IoT devices for the data which is generated by them. The patient's wearing IoT devices can be monitored in their trajectory and the countermeasures could be provided by safeguarding the privacy of patients via blockchain.
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Blokzinciri teknolojisi, aracı bir kuruluş olmadan iki veya daha fazla taraf arasındaki işlemlerin güvenli, şeffaf, değiştirilemez bir şekilde doğrulanması, gerçekleştirilmesi ve depolanmasını sağlayan dağıtık bir defter teknolojisidir. Akıllı sözleşmelerin (smart contracts) gelişimi ile taraflar arasındaki yasal sözleşmelerin aracısız bir şekilde otomatik olarak doğrulanması ve işlerlik kazanması sağlanmış, blokzinciri teknolojisinin gıda, enerji, emlak, inşaat, otomotiv gibi pek çok sektörde kullanılır hale gelmesine yol açmıştır. Sağlık hizmetleri alanında ise blokzinciri teknolojisi sağlık ekosistemini temelden dönüştürme potansiyeli ile önem arz etmektedir. Bu çalışmada, blokzinciri teknolojisinin anlamı, yapısı, işleyişi, çeşitleri, kullanım alanları, akıllı kontratlar ve sağlık hizmetleri alanında blokzinciri teknolojisinin kullanım alanları güncel uygulama örnekleri eşliğinde paylaşılmıştır. Blokzinciri teknolojisinin sağlık hizmetleri alanında kullanımından yola çıkarak oluşan kişisel sağlık verilerinin hastaların izni ile doktorlar, klinik araştırmalar ve hassas tıp çalışmaları ile güvenli paylaşımı, aracısız işlemler sonucu idari süreçlerin optimizasyonu ve maliyetlerde azalma, tedarik zinciri yönetiminde bilgi güvenilirliğinin artışı ve ürünlerin izlenebilirliği sonucu ürün sahteciliğinin önlenmesi gibi pek çok avantajı da ele alınmıştır. Yapısal bir derleme şeklinde kurgulanan bu çalışma, araştırma verileri için ulusal ve uluslararası literatürde “blokzinciri teknolojisi”, “akıllı kontratlar” ve “sağlık hizmetlerinde blokzinciri teknolojisi” ile ilgili çalışmalar taranarak meydana getirilmiştir.
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The Internet of Things aggregates devices able to capture information and interfere in the environment, acting in systems of different domains of application, such as health-care. These systems need a layer of security to guarantee, among other characteristics, the irrefutability, anonymity, and integrity of the manipulated data. In this sense, an integration with a blockchain, through smart contracts, would meet this need. This chapter, therefore, presents current research using IoT, blockchain, and smart contracts in health-care. The details for using these technologies in healthcare, the technical challenges and the consensus protocols involved in the main applications will be discussed. This chapter presents a practice that applies knowledge in the health supply chain, building a decentralized application (DApp) that monitors the temperature of vaccines during their storage. In the end, it offers an informative guide that allows participants to design training in this area, including practical exercises. Resumo A Internet das Coisas (Internet of Things (IoT)) agrega dispositivos capazes de capturar informações e interferir no ambiente, atuando em sistemas de domínios de aplicações diferentes, como por exemplo o da saúde. Estes sistemas precisam de uma camada de segurança para garantir, dentre outras características, a irrefutabilidade, o anonimato e a integridade dos dados manipulados. Neste sentido, a integração com a blockchain, através dos contratos inteligentes, atenderia a esta necessidade. Este capítulo apresenta, portanto, pesquisas recentes que utilizam IoT, blockchain e contratos inteligentes na área da saúde. Serão apresentados os detalhes para se empregar estas tecnologias na área da saúde, os desafios técnicos e os protocolos de consenso envolvidos nas principais aplica-ções. Na sequência, apresenta-se uma prática que aplica os conhecimentos abordados na 1
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Underwater Wireless Sensor Network (UWSN) is quite useful in monitoring different tasks including: from instrument monitoring to the climate recording and from pollution control to the prediction of natural disasters, etc. Recently, different routing protocols have been proposed in UWSN to explore the underwater environment for military and scientific purposes. In this regard, traditional transmission approaches increase the transmission overhead, i.e., packets' collision and congestion, which affect reliable data delivery. In addition, replacement of the sensors' battery in the harsh aquatic environment is also a challenging task. Therefore, to avoid the drastic failure of the network and to prolong the lifespan of the network, efficient routing protocols are needed. However, there are some challenges which affect the performance of the network, i.e., high Energy Consumption (EC), high End to End (E2E) delay, low Packet Delivery Ratio (PDR), minimum network lifetime, high probability of void hole occurrence, limited bandwidth and high bit error rate.~Thus, fast, energy efficient, reliable, collision and interference free routing protocols are required to improve the throughput of a network. Therefore, in this thesis, firstly, two routing protocols are proposed namely: Improved GEogrphic Depth Adjustment Routing (Im-GEDAR) and Co-Improved GEographic Depth Adjustment Routing (Co-Im-GEDAR) to maximize the PDR by minimizing the probability of void hole occurrence (with minimum EC). This enhanced PDR is attained by prohibiting the immutable forwarder nodes selection using three parameters including energy, depth and number of neighbor nodes. Moreover, the probability of void hole occurrence is minimized up to 30\% using fixed nodes deployment at different strategic locations in the network. Secondly, two energy efficient routing protocols namely: Shortest Path-Collision avoidance Based Energy-Efficient Routing (SP-CBE2R) protocol and Improved-Collision avoidance Based Energy-Efficient Routing (Im-CBE2R) protocol are proposed. These routing protocols minimize the probability of void hole occurrence, which minimizes the EC and E2E delay. In addition, both proposed routing protocols enhance the PDR and throughput of the network. In both routing protocols, greedy forwarding is opted to forward the data packets. Moving towards Wireless Sensor Networks (WSNs), during the data transmission, maximum energy is consumed in void hole recovery. In addition, location error and nodes' battery consumption are inevitable. Meanwhile, the loss of data packets and more EC degrade the performance of the network, significantly. Thirdly, three energy conservation routing protocols are implemented. These routing protocols are proposed to maximize the network stability (by avoiding void hole). Fourthly, a Proactive routing Approach with Energy efficient Path Selection (PA-EPS-Case I) is proposed to provide interference free communication. The proposed protocol adaptively changes its communication strategy depending on the type of the network, i.e., dense network, partially dense network and sparse network. Similarly, Bellman-Ford Shortest Path-based Routing (BF-SPR-Three) and Energy-efficient Path-based Void hole and Interference-free Routing (EP-VIR-Three) protocols are proposed for an efficient, reliable, collision and interference free communication. Afterward, the algorithms for the proposed routing protocols are also presented. Feasible regions for proposed routing protocols using linear programming are also computed for optimal EC and maximum network throughput. Moreover, the scalability of the proposed routing protocols is also analyzed by varying the number of nodes. In the end, extensive simulations have been performed to authenticate the performance of the proposed routing protocol. Meanwhile, comparative analysis is performed with state-of-the-art reactive and proactive routing protocols. The comparative analysis clearly shows that proposed routing protocols namely: Im-GEDAR and Co-Im-GEDAR achieved 21\% higher PDR and minimized 7\% EC than GEographic and opportunistic routing with DA based topology control for communication Recovery (GEDAR). The proposed routing protocols outperformed Transmission Adjustment Neighbor-node Approaching Distinct Energy Efficient Mates (TA-NADEEM) and minimized the void hole occurrence up to 30\%. Meanwhile, Im-CBE2R, SP-CBE2R, HA-ECMAE, HA-ECMAE2H and GTBPS-3H outperformed the counterparts. Furthermore, in PA-EPS-Case I, comparative analysis is performed with two cutting edge routing protocols namely: Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR) and Cluster-based WDFAD-DBR (C-DBR). Results demonstrate that proposed protocol achieve 12.64\% higher PDR with 20\% decrease in E2E delay than C-DBR. Furthermore, the proposed routing protocol outperformed C-DBR in terms of packet drop ratio up to 14.29\% with an increase of EC up to 30\%. In the end, comparative analysis of BF-SPR-Three and EP-VIR with benchmarks disclose that the proposed routing protocols outperformed in order to provide efficient path selection and to minimize the void hole occurrence.
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Underwater Wireless Sensor Networks (UWSNs) are promising and emerging frameworks having a wide range of applications. The underwater sensor deployment is beneficial; however, some factors limit the performance of the network, i.e., less reliability, high end to end delay and maximum energy dissipation. The provisioning of the aforementioned factors has become a challenging task for the research community. In UWSNs, battery consumption is inevitable and has a direct impact on the performance of the network. Most of the time energy dissipates due to the creation of void holes and imbalanced network deployment. In this work, two routing protocols are proposed to avoid the void hole and extra energy dissipation problems due to which lifespan of the network will increase. To show the efficacy of the proposed routing schemes, they are compared with the state of the art protocols. Simulation results show that the proposed schemes outperform their counterpart schemes. By keeping in mind the emerging security issues in sensor networks, we have proposed a blockchain based trust model for sensor networks to enrich the security of the network. Additionally, this model provides security along with data immutability. We have used a private blockchain because it has all the security features that are necessary for a private sensor network. Moreover, private blockchain cannot be accessed by using the Internet. In the proposed trust model, the Proof of Authority (PoA) consensus algorithm is used due to its low computational power requirement. In PoA consensus mechanism, a group of the validator is selected for adding and maintaining blocks. Moreover, smart contracts are used to validate and transfer cryptocurrency to service providers. In the end, transaction and execution costs are also calculated for each function to testify the network suitability.
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In a research community, data sharing is an essential step to gain maximum knowledge from the prior work. Existing data sharing platforms depend on trusted third party (TTP). Due to involvement of TTP, such systems lack trust, transparency, security and immutability. To over come these issues, this thesis proposed a blockchain based secure data sharing platform by leveraging the benefits of interplanetary file system (IPFS). A meta data is uploaded to IPFS server by owner and then divided into n secret shares. The proposed scheme achieves security and access control by executing the access roles written in smart contract by owner. Users are first authenticated through RSA signatures and then submit the requested amount as a price of digital content. After the successful delivery of data, a user is encouraged to register reviews about data by announcing customer incentives. In this way, maximum reviews are submitted against every file. In this scenario, decentralized storage, Ethereum blockchain, encryption and decryption schemes and incentive mechanism are combined. To implement the proposed scenario, smart contracts are written in solidity and deployed on local Ethereum test network. The proposed scheme achieves transparency, security, access control, authenticity of owner and quality of data. In simulation results, an analysis is performed on gas consumption and actual cost required in terms of USD, so that a good price estimate can be done while deploying the implemented scenario in real setup. Moreover, computational time for different encryption schemes are plotted to represent the performance of implemented scheme, which is shamir secret sharing (SSS). Results show that SSS shows least computational time as compared to advanced encryption standard (AES) 128 and 256.
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Decision fusion is used to fuse classification results and improve the classification accuracy in order to reduce the consumption of energy and bandwidth demand for data transmission. Decentralized classification fusion problem was the reason to use belief function based decision fusion approach in Wireless Sensor Networks (WSNs). With the consideration of improving the belief function fusion approach, we have proposed four classification techniques namely Enhanced K-Nearest Neighbor (EKNN), Enhanced Extreme Learning Machine (EELM), Enhanced Support Vector Machine (ESVM), and Enhanced Recurrent Extreme Learning Machine (ERELM). In addition, WSNs are fallible to errors and faults because of their different software, hardware failures, and their deployment in diverse fields. These challenges require efficient fault detection methods to be used to detect faults in WSNs in a timely manner. We induced four type of faults: offset fault, gain fault, stuck-at fault, and out of bounds fault and used enhanced classification methods to solve the sensor failure issues. Experimental results show that ERELM has given the first best result for the improvement of belief function fusion approach. The other three proposed techniques ESVM, EELM, and EKNN have provided the second, third, and fourth best results, respectively. Proposed enhanced classifiers are used for fault detection and are evaluated using three performance metrics ,i.e., Detection Accuracy (DA), True Positive Rate (TPR), and Error Rate (ER). In this thesis, the owner of the (Internet of Thing) IoT device can generate revenueby selling IoT device’s data to interested users. However, on the other hand, users do not trust the owner of IoT device for data trading and are not confident about the quality of data. Traditional data trading systems have many limitations, as they involve third party and lack: decentralization, security and reputation mechanisms. Therefore, in this thesis, we have leveraged the IoTs with blockchain technology to provide trustful data trading through automatic review system for monetizing IoT’s data. We have developed blockchain based review system for IoT data monetization using Ethereum smart contracts. Review system encourages the owner to provide authenticated data and solve the issues regarding data integrity, fake reviews and conflict between entities. Data quality is ensured to users through reviews and ratings about the data, stored in blockchain. To maintain the data integrity, we have used Advanced Encryption Standard (AES)-256 encryption technique to encrypt data. All transactions are secure and payments are automated without any human intervention. Arbitrator entity is responsible to resolve problems between data owner and users. Incentive is provided to users and arbitrator in order to maintain the user participation and honesty. Additionally, Ethereum blockchain system requires gas for every transaction. Simulations are performed for the validation of our system. We have examined our model using three parameters: gas consumption, mining time and encryption time. Simulations show that the proposed methods outperform the existing techniques and give better results for belief function and fault detection in datascience WSNs. Additionally, blockchain based data trading in IoT system requires gas for every transaction. We have examined our model using three parameters: gas consumption, mining time and encryption time.
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Wireless Sensor Networks (WSNs) are vulnerable to faults because of their deployment in unpredictable and hazardous environments. This makes WSN prone to failure such as software, hardware, and communication failures. Due to the sensor’s limited resources and diverse deployment fields, fault detection in WSNs has become a daunting task. To solve this problem, Support Vector Machine (SVM), Probabilistic Neural Network (PNN), Stochastic Gradient Descent (SGD), Multilayer Perceptron (MLP), Random Forest (RF), and Convolutional Neural Network (CNN) classifiers are used for classification of gain, offset, spike, data loss, out of bounds, and stuck-at faults at the sensor level. Out of six faults, two of them are induced in the datasets, i.e., spike and data loss faults. Likewise, sensors embedded mobile phones are used for the collection of data for some specific task which can effectively save cost and time in Crowd Sensing Network (CSN). The quality of collected data depends on the participation level from all entities of CSN, i.e., service provider, service consumers and data collectors. In comparison with the centralized traditional incentive and reputation mechanisms, we propose a blockchain based incentive and reputation mechanism for CSNs, which mainly consists of three smart contracts. The incentives are used to stimulate the involvement of data collectors and motivate the participants to join the network. Also, the issue of privacy leakage is tackled by using Advanced Encryption Standard (AES128) technique. In addition to that, a reputation system is implemented to tackle the issues like untrustworthiness, fake reviews, and conflicts among entities. Through registering reviews, the system encourages data utilization by providing correct, consistent and reliable data. Furthermore, the results of first scenario are compared on the basis of their Detection Accuracy (DA), True Positive Rate (TPR), Matthews Correlation Coefficients (MCC), and F1-score. In this thesis, a comparative analysis is performed among the classifiers mentioned previously on real-world datasets and simulations demonstrate that the RF algorithm secures a better rate of fault detection than the rest of the classifiers. Similarly, the second scenario is evaluated through analyzing the gas consumption of all the smart contracts, whereas, the encryption technique is validated through comparing the execution time with base paper technique. Lastly, the reputation system is inspected through analyzing the gas consumption and mining time of input string length.
Conference Paper
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Internet of Things (IoTs) is widely growing domain of the modern era. With the advancement in technologies, the use of IoTs devices also increases. However, security risks regarding service provisioning and data sharing also increases. There are many existing security approaches, although these approaches are not suitable for IoT devices due to their limited storage and limited computation resources. These secure approaches also require a specific hardware. With the invention of blockchain technologies, many security risks are eliminated. With the help of blockchain, data sharing mechanism is also possible. In this paper, we proposed a novel secure service providing mechanism for IoTs by using blockchain. We introduced cloud nodes for maintaining the validity states of edge service providers. The rating and cryptocurrency is given to edge servers. Given rating and incentive is stored in cloud node and updated with respect to time. The smart contract is proposed to check the validity state of the edge server as well as compare and verify the service provided by edge servers. In our proposed system we perform service authentication at cloud layer as well as edge server layer. Moreover, by using Proof of Authority (PoA) consensus mechanism overall performance of our proposed system also enhanced.By experimental analysis it is shown, our proposed model is suitable for resource constrained devices.