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Smart Contracts for Research Lab Sharing Scholars Data Rights Management over the Ethereum Blockchain Network

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The data sharing is the claim of actual scholars datasets to share and reuse in the future from any domain. The rise of blockchain technology has to increase universally and enhancement in share and reuse of scholars datasets. Despite there are numbers of security management frameworks for share data securely. However, those frameworks is a centralize based to make data share digitally. Its has restriction and owned by third party authority. The access and reuse of research datasets have a variety of issues it misinterpretation. In this aspect, the researcher or publisher has not to share data publicly due to reuse and perceive the risk in a data sharing environment. Preparing and storing data is difficult in contents sharing. To overcome the limitation and restriction, we proposed distributed data sharing management based on blockchain network (peer to peer P2P network). To signify on Ethereum framework , we proposed the case study of data sharing on the Ethereum smart contract platform to achieve the access.
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Smart Contracts for Research Lab
Sharing Scholars Data Rights
Management over the Ethereum
Blockchain Network
Abdul Ghaffar, Muhammad Azeem, Zain Abubaker,
Muhammad Usman Gurmani, Tanzeela Sultana, Faisal Shehzad,
and Nadeem Javaid(B
)
COMSATS University Islamabad, Islamabad 44000, Pakistan
abdul7g7@gmail.com, nadeemjavaidqau@gmail.com
Abstract. The data sharing is the claim of actual scholars datasets to
share and reuse in the future from any domain. The rise of blockchain
technology has to increase universally and enhancement in share and
reuse of scholars datasets. Despite there are numbers of security man-
agement frameworks for share data securely. However, those frameworks
is a centralize based to make data share digitally. Its has restriction and
owned by third party authority. The access and reuse of research datasets
have a variety of issues it misinterpretation. In this aspect, the researcher
or publisher has not to share data publicly due to reuse and perceive the
risk in a data sharing environment. Preparing and storing data is diffi-
cult in contents sharing. To overcome the limitation and restriction, we
proposed distributed data sharing management based on blockchain net-
work (peer to peer P2P network). To signify on Ethereum framework, we
proposed the case study of data sharing on the Ethereum smart contract
platform to achieve the access.
Keywords: Repository technologies ·Research data sharing ·Smart
contract ·Digital right management
1 Introduction
Data sharing is an important and vital mainly for public researcher to obtain
their tasks and update there work. Research datasets contain issues to publish.
e.g., reproduced the paper results and simulation that update and proof your
work to republish your task without adding or commitment of their own scheme
in the search cycle. The main difficulties of scholarly communication to main-
tain the preparing and storing the research datasets [1]. Recently, the research
datasets is given autonomy to a requester to update the publish research sharing.
The scholarly communication of research datasets is digitally right managed.
This article proposed the new scheme for the researcher to publish his work
typically its can examine by researchers to view his work on each step to follow
c
Springer Nature Switzerland AG 2020
L. Barolli et al. (Eds.): 3PGCIC 2019, LNNS 96, pp. 70–81, 2020.
https://doi.org/10.1007/978-3-030-33509-0_7
Smart Contracts for Research Lab Sharing Scholars 71
the reuser action that how it can be accessed. Those conditions and policies can
be enforced and follow through the smart contract that follows the conditions
under which the research data is to publish.
The paper aims to evaluate and compare the decentralized architecture with
the existing management scheme for research datasets right management. Using
datasets repository and data sharing solutions for scholarly communication.
Specifically, the research data is evaluated the performance of existing archi-
tecture. In addition, our proposed technique meet design goal of scalability by
measuring the system with a different configuration.
The scholarly datasets communication of researcher domain has more con-
nected parts include numbers of activities for sharing research data. Authors will
post the research datasets by own website [1]. In [2], we facilitate to upload free
services of research contents. From the points of publish research data sharing
and reuse the research contents (reuser/requester) can specify under certain con-
ditions and terms [3]. When supporting research content is publish it follow the
access and reused conditions. So its remain confidential in case of reuser inter-
ference to reuse practically. Usually, reuser takes permission from the author.
1.1 Problem Statement
The most necessary and essential activity of researcher/scholar to share their
scholarly datasets from one part to another mainly due to requirements of
research organization and research labs [1]. In the research cycle to sharing
the scholarly datasets is not necessary because in the survey less then the half
researcher can response on it due to difficulties in storing and data sharing
which is technical issue [2]. In the various activity of knowledge [3], they aware
of the environment that publish research datasets can have the wrong impact
on academic desired aim. In the survey, the main obstacle is fear in misused
and misinterpretation of research publish datasets and fear in lose of publishing
chances.
1.2 Technical Contribution
Smart contract technique is used to solve the digital right management in the
proposed system. We reference to Ethereum blockchain network. To implements
the reuse of scholarly contents/datasets from essential domain to enhance the
knowledge and consideration. The number of scholars can share the contents of
research datasets due to use for further innovation interpretation. To solve the
problem we reach to the best solution using innovation mechanism and tech-
nology called blockchain. This is the new plan to promote the flexibility and
reliability to record each term/condition/policy activities involve in the smart
contract.
The blockchain used to maintain and deploy the records of transactions in
a decentralized distributed public digital ledger. There is no need for the third
party to maintain the transaction. Blockchain maintains each entity to records
separately and subsequently. It also needs to records important information
72 A. Ghaffar et al.
about the publisher and researcher workflow. Moreover, a smart contract for
digital right management represents the solid base for datasets sharing over the
Internet.
Smart contract technology makes interactive between authors scholar
datasets and requester access action. The parameters assigning by authors as
follow:
High qualification degree holder.
Associated with development and research lab to publish the research area
from any domain.
Author account address to store the incentives received from requester.
The remaining paper is structured in the following manner: Sect. 2discusses
the blockchain mechanism. Related work for scholarly datasets communication
of research work and motivation is discussed in Sect. 3. Section 4shows an intro-
duction of our new proposed technique. In Sect. 5concludes the results. More-
over, Sect. 6present the simulation environment. Finally, Sect. 7we conclude our
article and discuss the future limitation/scope of blockchain in data sharing.
2 Blockchain Mechanism
Revolutionized technology used to handle the data. It is the hash-based data
structure. Initially, blockchain develops for the invention of bitcoins. Most peo-
ple think, that this technology used for power the bitcoin. It is actually the
chronological linked list of batches called block. Those blocks are used for store
data which is untampered. The technology of blockchain is an increasing list of
blocks (records) that are related by cryptographically.
2.1 Blockchain Fundamental
In the blockchain, there is a hash function, hash pointer to the previous hash,
and Merkle tree also called a hashed tree. The Merkle tree or hash tree is usually
used to append the data hashes to build a new string of hash. After the resultant,
we get the root hash (the unique hash).
The blockchain used two cryptographically techniques, namely as a digtal sig-
nature and hash function. The digital signature provides the integrity, authen-
tication, and non-repudiation for bitcoin transaction. A hash function is used
to compute the hash value of the previous block and makes blocks as a chain.
Besides, blockchain is basically a decentralized distributed ledger, which is capa-
ble enough to record all transaction information between different agents (sellers
and buyers) in a certified and reliable manner [1,2].
Finally, blockchain technology is completely distributed and public database.
Where any kind of data is to be exchanged. On every transaction, the blockchain
technology creates a new block. The blockchain is formed when all the blocks
are associated sequentially by hash. In addition, the body of every block has all
the necessary transaction data in the preceding phase.
The decentralized blockchain technology in data sharing has many applica-
tions, such as access to data, data trading [6], and data management.
Smart Contracts for Research Lab Sharing Scholars 73
2.2 Blockchain Construction
When a new transaction or any data is to insert in well-known ledger it initially
broadcast to all participant in the particularly given network. The proof-of-
work PoW is actually the solution for authorized access of data inference in the
blockchain. In the bitcoin network, after verification of the transaction. Each
verified transaction is then broadcast to all nodes in the network for record in
public ledger.
For a single transaction, first to be verified for validity before it is recorded
in public ledger. For the tampering data in a blockcain network need the cre-
ation of a new block to store the desired modified data by whom and when.
Because a blockchain is a long time stored mechanism for decades. The most
useful verification techniques as follow:
Proof-of-Work: In PoW to add a block to the chain, miners must compete to
solve difficult mathematical puzzles using their computer processing powers.
In order to add a malicious block for any transaction, you’d to have a com-
puter more powerful to make 51% the network approval [9]. In PoW the first
miner is rewarded to solve the puzzle first.
Proof-of-Stack (PoS): In technique, their is no competition for the block cre-
ator. It is chosen by an algorithm based on the user’s stack. In order to add
a malicious block, you’d have to own 51% of all the cryptocurrency on the
network. There is no reward to the miner on creating the block. But only a
fee transaction is to give to it.
Proof-of-Authority PoA: In PoA transaction and blocks are validated by
approved accounts called validators. Those validators run the software to
put the transactions in the verified blocks. This process is automated and not
need of validators to constantly monitor their computers.
2.3 Blockchain Basic Components
Transaction: Transmitting transaction is actually the information or data
from one participant to another in a particular network. The transaction is
kept on track by a blockchain, since from birth to the desire entity.
Blocks: The blocks are used to collect valid transactions. Each block collect
transaction that has to occur it given period and has the refers to the pre-
ceding block. Therefore, the chain of blocks is built.
Nodes: The nodes are the participants in a particular network. Those nodes
used to store the complete transaction. Nodes are the members. Therefore,
each node is to store the entire blockchain/ledger separate copy instead in a
centralized server/database.
Majority Consensus: It is actually the decision authority. The centralized
authority is to discard. Therefore, the decision is taken by majority node in
the specified network. Participants or nodes modifies the stored transaction
data if the majority in a specified network is approval the status [4].
74 A. Ghaffar et al.
3 Related Work
In this section, we discuss the literature review and motivation to the context of
this article.
The most necessary and essential activity of researcher/scholar to share their
scholarly datasets from one part to another mainly due to the requirements
of research organization and research labs [1]. In the research cycle, to share
the scholarly datasets is not necessary because in the survey less then the half
researcher can respond to it due to difficulties in storing and data sharing which
is a technical issue [2].
In the various acts of knowledge [3], they aware the environment that publish
of research datasets can have the wrong impact on academic desired aim. In the
survey, the main fence or obstacle is fear in misused and misinterpretation of
research publish data and fear in lose of publishing chances.
The scholarly communication of researcher domain has more connected parts
include numbers of activities for sharing research datasets. Authors will post the
research datasets by own website [4,5].
In ZENODO [6] facilitate to upload free services of research contents. From
the point of publishing research datasets sharing and reuse the research contents
(reusers/requesters) can specify under certain conditions and terms [7]. When
supporting research contents is publish it follow the access and reuse conditions.
So its remain confidential in case of reuser interference to reuse practically. Usu-
ally, reusers take permission from author.
The development of mobile communication and networking which is
extremely difficult to manage. Due to proposed in [7] scenario, Artificial Intelli-
gence AI-powered network frameworks. This platform operates a network auto-
matically. To tackle data barriers, we used mutual data sharing frameworks.
With the invention of blockchain technology, most researcher sharing focus
on blockchain mechanism to notice the value of scholarly data sharing. Mostly
include medical data sharing. In a medical scenario, the authors used to take
ownership of saving and manipulate the data. For this, the only solution to the
problem was blockchain technology. For whatever, medical data need only to
verify at the permission from data ownership. This permission is verified through
smart contracts using blockchain technology.
Another problem is to tackle through on aspect of data authority manage-
ment. For tackle such issue, blockchain technology is used for data authority
management. In this scenario, the raw data can’t be controlled by the owner as
long as. In system [7], it includes three levels: user layer, management layer, and
data sharing layer. We also used the storage layer as composed to the cloud-based
storage layer. In [817], authors use of blockchain in wireless sensor networks,
Internet of things, smart grids, vehicle networks, etc.
4 Proposed Scheme Model
In this section, the smart contracts technique is used to solve the digital right
management. We reference to Ethereum blockchain network. To implements the
Smart Contracts for Research Lab Sharing Scholars 75
Layer 1
Authors / Publisher
Domain
Layer 3
Reuser / R equester
Domain
Smart contract
Layer 2
CondiƟons / Terms
Domain
Scholar
Prole
Publisher
Account
Publisher
Data Repository
Publisher
Reuser
Account
Requester
Rework
Data
CommunicaƟon
Data Access
AbstracƟon of
Data
Fig. 1. Smart contracts for Research Data Right Management
reuse of scholarly contents/data from essential domain to enhance the knowledge
and consideration. The number of scholars can share the research contents or
research datasets due to used for further innovation interpretation. To solve the
problem, we reach the best solution using innovation mechanism and technology
called blockchain and smart contracts. This is the new plan to promote the
flexibility and reliability to record and verify each term activity involves in the
smart contracts.
Actually, in the proposed model we have to contribute and divides the given
scenario. The division is made on the functionality of various objects and their
environments. The data repository is storing location where publish datasets is to
maintain. The publisher will access the datasets directly. In datasets repository,
each publisher has its own scholar profiles. Usually, the scholar profiles consists
of various fields of well-known information about scholars. From the scholar
profiles, the required scholar datasets are accessed.
The blockchain used to maintain and deploy the records of transactions in
a decentralized distributed public digital ledger. Their is no need of the third
party to maintain the transaction. Blockchain maintains each entity records sep-
arately and subsequently. It also needs to records important information about
the publishers and researcher workflow. Moreover, smart contracts for digital
right management represent the solid base for data sharing over the Internet.
In Fig. 1smart contracts technology makes interactive between authors
scholar datasets and requester access action. The parameters assigning by
authors is follow:
High qualification degree holder.
Associated with development and research lab to publish the research area
from any domain.
Authors account address to store the incentives receive from requester.
76 A. Ghaffar et al.
Hashing for authors datasets and conditions (used in smart contracts under
which research datasets may access and reuse).
The published work is reuse is to record permanently in a transaction
(Table 1).
Table 1. The gas value occurs during implementing the transaction
Authors
qualification
description
Requester
qualification
description
Authors and
requester output
parameter in gas
Authors
development
research lab
Performance
in gas
Reuser
development
research lab
Performance
in gas
Phd BS 45871 RMIT Lab 45957 RMIT Lab 46023
Phd BS 26328 Comsens
Lab
31406 RMIT Lab 26480
Phd MS 26328 QU Lab 31278 Comsens Lab 31472
MS MS 31064 UOP Lab 26542 Comsens Lab 26672
M-Phil Phd 26264 NUST Lab 31406 QU Lab 31344
BS Phd 26264 USTB Lab 26608 UOP Lab 31216
The performance of transaction evaluation is measured in gas. Ethereum
Virtual Machine (EVM) and the network which used to implement the smart
contracts used to manage the research scholar datasets. In the proposed scenario,
the calculation of each output parameter performance is taken in gas. While the
transaction cost is estimated in ether given in Fig. 2. The execution cost of the
transaction based on ether cryptocurrency.
Table 2. Total evolution of transaction
Transaction sequence in gas Evolution of transaction
Development research lab 99.98
Authors qualification description 99.93
Requester qualification description 99.78
Reuser development research lab 99.78
In the above table, the evaluation of composed parameters is shown. Dur-
ing the transmission of transaction occurs it consume how much gas in ether
(Ethereum coin called ether). The gradually decrement in the transaction of
Ethereum if any parameter occurs (Table 2).
Smart Contracts for Research Lab Sharing Scholars 77
5 Analysis of Results and Discussion
The model is deployed in Ethereum platform, in order to improve the decen-
tralization of scholar datasets sharing using blockchain technology and smart
contracts. The datasets are consumed and encompass on input control and out-
put performance. In this proposed scheme, we consider three layers. Each layer
has own transaction performance. Moreover, the performance evaluation shows
in each plotted graphs.
Fig. 2. Authors development research lab
In Fig. 2shows the output evaluation transaction cost on y-axis based on
input parameters (number of research labs that publish research content or com-
municate scholarly). It is the domain from where the authors will publish the
scholar datasets to maintain the consistency and flexibility of enhancement. Cer-
tainly, lab description allows the desired and needed scholars datasets have to
publish. The datasets published depends on the authors research labs descrip-
tion. The scholars datasets from any desired lab descriptions increments simul-
taneously in data publishing. The output evaluation is computing in transaction
gas period. Definitely, authors, research lab description shows the levels of pub-
lishing materials. Usually, it demonstrates which type of authors from specified
research lab can upload which levels of scholar datasets.
The rapidly decrement in the amount of transaction depends on the through-
put of authors research labs shows in Fig.2. Our proposed technique contribution
has motivated from intelligent vehicle technology [5].
The lab description shows the various labs that are required to publish their
concerned scholar datasets. The numerous well-known scholar data publish from
each lab to take the revolution of participating to make more transaction in the
access of there paper to be published. On y-axis, we evaluate the transaction of
each lab to publish there work done.
78 A. Ghaffar et al.
Fig. 3. Authors qualification description
Fig. 4. Requester qualification description
In Fig. 3shows the authors qualification for publishing the desired and needed
scholar datasets. The data published depends on authors qualification descrip-
tion. The scholar datasets from any desired descriptions is an enhancement in
data publishing. The output evaluation is computing in transaction cost period.
Definitely, authors description shows the levels of publishers. Usually, it demon-
strates which type of authors can upload which level of scholar datasets.
In Fig. 4shows the requester qualification description. On both sides, the
transaction output is taken in gas. The delay is actually shown in gas perfor-
mance. How fast the scholar data is accessed from the publisher, the transaction
almost gradually performed. In general, the result of the experiment shows that
the publish and downloaded gas transaction for each event is acceptable. We also
experiment to measure the relationship between concurrent services requested
and transaction output gas in ether.
In the given scenario, we have three layers, in which the bottom layer is for
reuser of the scholar datasets. In Fig. 5, the reuser or the requester needs to
access the published datasets from the blockchain technology. On each access of
the desired paper, the incentives can share to the publisher. Reuser can access
Smart Contracts for Research Lab Sharing Scholars 79
Fig. 5. Reuser development research lab
publish materials from any well-known labs for future. The access of required
papers can be made from the authorized lab because of their reuse must be
working on policies.
6 Semulation Environment
In the simulation scenarios, we consider the experiment employs on the laptop
which actually indicates the user’s devices. Here laptop plays the role of miners
due to relative compute and storage capability as follow:
Laptop with 8.00 GB RAM.
64-bit window 10 (Operating System).
Laptop processor is Intel Core m3-7Y30 CPU @ 1.00 GHz 1.61 GHz.
The smart contracts actually make runtime contract between the datasets pol-
isher and reuser for sharing datasets.
Remix is an integrated development environment (IDE). Which is web
browser-based IDE for programming in solidity (to write the smart contracts
that digitally facilitate the parties on both sides to trust on given rules). The
Ethereum platform used ether. Which shows how much ether has been done on
a specific task. How much gas is consumed to indicate actually the total cost for
a specific task. For more a complex task, we need more cost to be consume.
Ganache is a personal blockchain to create a smart contract. It’s available for
a desktop application which is a command line tool for windows. It works and
used on Ethereum development. It provides the functionality of the deployment
of smart contracts. We used as a desktop application to deploy the contract
between data scholars publisher and reuser. Ganache allows you to create a
private Ethereum blockchain for you to run for test and execute commands.
MetaMask is a bridge that allows you to visit the distributed web to run
Ethereum desktop application on your browser. It is usually a wallet to store,
send, and receive the ethers. It allows you to control the funds.
80 A. Ghaffar et al.
7 Conclusion and Limitation
The results of experiment shows the gas value occurs during implementing the
transaction in EVM of smart contracts for the right research datasets man-
agements. While the transaction cost defines the actual workflow to be done
in blockchain network transaction based on the limited number of computing
resources. The publish of scholar datasets similarly estimates in ethers incentive
tokens to stay the terms.
The above plots shows the throughput parameters of publishing total transac-
tion, lab description, and authors qualification. Each plot defines the transaction
cost and estimated gas value which is calculated in either token due to EVM. We
carried out a brief description of each newly added parameter in research right
managements datasets to reuse by various requesters to enhance the domain. On
each plot, the datasets are taken randomly to define the conclusion for mainte-
nance. The proposed system is accordingly working as resultants of experiments.
Each author has much scholarly information to publish in any fields but in some
checks such as qualification and developed research lab mandatory.
The total sequence gas generated due to researcher publish the datasets to
response the reusers request. In enhanced publishing, data storing is increasing
with probability. The authors must attach to a development lab to access the
published work to enhance and develop his own research work.
Moreover, for future limitation, the scheme can be extended to enforce the
policies and terms conditions to establish the research data. It can also increase
in economic perspectives. We should also examine for research interest in inte-
grating the access to identical fields data.
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Thesis
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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.
Thesis
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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.
Thesis
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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.
Thesis
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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.
Conference Paper
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The emergence of smart homes appliances has generated a high volume of data on smart meters belonging to different customers which, however, can not share their data in deregulated smart grids due to privacy concern. Although, these data are important for the service provider in order to provide an efficient service. To encourage customers participation, this paper proposes an access control mechanism by fairly compensating customers for their participation in data sharing via blockchain and the concept of differential privacy. We addressed the computational issues of existing ethereum blockchain by proposing a proof of authority consensus protocol through the Pagerank mechanism in order to derive the reputation scores. Experimental results show the efficiency of the proposed model to minimize privacy risk, maximize aggregator profit. In addition, gas consumption, as well as the cost of the computational resources, is reduced. Index Terms-Blockchain, consensus mechanism, proof of authority, privacy preserving and smart grid. I. INTRODUCTION Presently, because of the rapid growth of the world population and the technological innovations, a lot of energy is needed in a short period of time and during peak hours, and its effect increases the cost of production. Customers can, therefore, optimize their utilization based on the current energy demand and supply. As a result, demand response and dynamic pricing proposal are subject to privacy issues. In a smart grid, customers will share their hourly information load profile with a service provider only to allow a certain level of privacy to be maintained, which is a major barrier for customer participation. In order to efficiently aggregate customer data, while preserving their privacy, Liu et al. [1] propose a privacy-preserving mechanism for data aggregation. The proposed solution minimizes the cost of communication and computational overhead. However, a trusted environment is not considered. To achieve a trusted environment, several studies in [2]-[8] used blockchain as privacy-preserving mechanism for data aggregation; privacy protection and energy storage; secure classification of multiple data; incentive announcement network for smart vehicle; crowdsensing applications; dynamic tariff decision and payment mechanism for vehicle-to-grid. A survey concerning privacy protection using blockchain is discussed in [9]. The survey highlights all the existing