Reputation System for IoT Data
Monetization Using Blockchain
Atia Javaid, Maheen Zahid, Ishtiaq Ali, Raja Jalees Ul Hussen Khan,
Zainib Noshad, and Nadeem Javaid(B
COMSATS University, Islamabad 44000, Pakistan
Abstract. Internet of Things (IoT) is growing exponentially and bring-
ing revolution in today’s modern society. IoT based smart devices are
source of convenience to human life and producing huge amount of data
on daily basis. This data is useful for consumers like industries, mar-
ketplaces, and researchers to extract valuable and functional data from
raw data generated by these devices. This data is used by industries
and developers to provide more eﬃcient devices and services to users.
Owner of the IoT device can generate revenue by selling IoT device
data to interested consumers. However, on the other hand consumers
do not trust the owner of IoT device for data trading and are not con-
ﬁdent about the quality of data. Traditional systems for data trading
have many limitations, such as they are centralized, lack reputation sys-
tem, security and involve third party. Therefore in this paper, we have
leveraged the IoT with blockchain technology to provide a trustful trad-
ing through automatic review system for monetizing IoT data. We have
developed blockchain based review system for IoT data monetization
using Ethereum smart contracts. All transactions are secure and pay-
ments are automated without any human intervention. Data quality is
ensured to consumer through reviews and ratings about the data. Addi-
tionally, Ethereum blockchain system requires gas for every transaction.
We have used 2 parameters: gas consumption, string input length and in
terms of time and cost, and examined our model.
Keywords: Message querring telemetry transport ·Blockchain ·IoT ·
Review system ·Metadata
The Internet of Things (IoT) is a world wide network where humans, devices
and objects are connected with unique addresses. These devices have the capabil-
ity to communicate, share and transfer data through centralized servers. IoT is
growing exponentially year by year and gaining more attraction for all academic
ﬁelds and industries. More than 8.5 billion devices are connected to the IoT and
will increase up to 20.4 billion connected devices in 2020. The applications of
Springer Nature Switzerland AG 2020
L. Barolli et al. (Eds.): BWCCA 2019, LNNS 97, pp. 173–184, 2020.
174 A. Javaid et al.
IoT in daily life makes its importance more evident. These devices produce data
of diﬀerent types depending on the type of network. This data is used by pub-
lic users, industries and many other technologies like smart home automation,
health care, data trading market places, etc. This data is used to make human
life more convenient and advance. Using IoT devices for the purpose of sensing
as a service, huge amount of revenue could be generated.
As number of connecting devices are increasing, there is huge threat to net-
work security and data integrity. Traditional centralized systems because of secu-
rity, automation, scalability and third party issues are not feasible for IoT devices
to share or trade data and assets over the network. Centralized systems are costly,
involve hacking and trust issues along with the threat of single point of failures
. Improving security and privacy regarding IoT is challenging because IoT
devices are energy, memory and resource constrained . The available amount
of energy is utilized to perform needed application functions, because of which
security and other important features are compromised. Many researchers con-
tributed to handle such security issues like transmission ﬁeld security , cloud
storage ﬁeld , digital signature and permission identiﬁcation [5,6]. In the ﬁeld
of IoT and healthcare, researchers have worked on the IoT to collect data ubiq-
uitously , to provide processed data in time for eﬃcient healthcare purposes.
The resource based IoT access methods are used to collect heterogenous data
ubiquitously from cloud and mobile computing platforms. On the other hand,
these devices are generating huge amount of data. Scalable data storage solution
is necessary to handle large amount of data eﬃciently.
Researchers have worked on such data storage issues to produce eﬃcient
solutions for the structured and unstructured data . Blockchain is new emerg-
ing technology with a lot of advantages of security, trust and immutability. It
is a decentralized ledger, previously only used for money transactions however,
it is now widely applied to diverse ﬁelds like smart grids, IoT , smart cities
, vehicle management  and many more. Once the transactions between
sender and receiver are recorded in the open and distributed ledger, then this
data cannot be tampered. In the mining process of blockchain, miner records
the transaction in the block and broadcast this block in the network, so that all
nodes have the same copy of transaction.
2 Related Work
Many studies have been done to leverage the advantages of blockchain in IoT.
Blockchain and IoT integration have achieved automation in industries and in
daily human life. Secure, scalable and adaptive industrial IoT platforms are
needed by the industries to achieve their goals. Existing industrial IoT platforms
are centralized systems having problems of single point failure. These systems
also face the problems like accessibility, conﬁdentiality and integrity. Semantic
rules engine  and health based IoT systems  are facing the issue of sin-
gle point failure. In  authors have presented the industrial IoT system for
the smart factories to address the above mentioned problems. Directed Acyclic
Reputation System for IoT Data Monetization Using Blockchain 175
Graph (DAG) structured blockchain is used with eﬃcient POW mechanism,
making DAG structured blockchains more eﬃcient for industrial IoT systems.
Privacy and conﬁdentiality are ensured through data authority management sys-
tem. However, they do not tackle the storage and data quality issues related to
sensor data. There is a major threat to traditional storage systems because of
Traditional storage systems are vulnerable to single point of failures, and are
costly due to involvement of third party. In  a blockchain based storage sys-
tem named Sapphire is presented for analyses of data. For this storage system
smart contracts are created based on object storage device approach for interac-
tion of IoT devices with blockchain. Application speciﬁc operations are executed
only and results are provided to users instead of all the data which decreases
the storage and computational overhead of data analyses in IoT. However, this
system is not matured enough to deal with scalability and security issues. IoT
devices are used along with other electronic devices and protocols to perform
diﬀerent tasks and operations without the human involvement. These electronic
and IoT devices and other network participants have to communicate with each
other to complete desired tasks. These devices must be authenticated before
entering the network and sharing data and resources with the other authenti-
cated entities. Authentication is essential, otherwise network will become target
for malicious users.
Conventional centralized authentication systems for IoT are not eﬃcient. In
 authors have presented a decentralized system for authentication of devices.
Blockchain system provides security features and virtual zones provides trust-
ful environment where devices can authenticate each other. However, virtual
zones introduce the computational overhead and delay for the authentication
purpose. Diﬀerent authors have used blockchain to tackle the several problems
such as: data trading, energy trading, node recovery, eﬃcient energy routing,
edge servers participation, data rights management, healthcare issues, securing
data, fair sharing of data and under water routing problems. In [17–27] authors,
have provided solutions for the above mentioned problems using blockchain.
In , authors used review system for ensuring data quality and integrity of
data being traded through data marketplaces. Reviews are maintained by the
blockchain based system for the new users to analyze the reviews before using
2.2 Problem Statement
Earning revenue through the data produced by the IoT devices considering secu-
rity, cost eﬃciency, automatic monetization and centralized governance are the
challenging problems handled by the authors in .
176 A. Javaid et al.
•Security: Previously, generating revenue from IoT does not consider the rules
and regulations provided from the owner of the IoT devices. Usage terms
about the data are not well deﬁned.
•Cost Eﬃciency: Automatic monetization of IoT data is costly due to the
involvement of third parties to exchange data and money.
•Centralized Governance: Number of devices connected to the centralized plat-
form will create a bottleneck, and if centralized system is attacked or failed,
whole system will suﬀer the consequences.
Authors have implemented a blockchain using smart contracts to provide secure,
cost eﬀective and decentralized solution for IoT data trading. However, they
did not consider the trustworthiness of data owner and quality of data. Data
consumers will purchase the data only if they have trust on the data owner.
Previous IoT and blockchain systems do not provide a review system for IoT
data to be traded. Review system is needed which holds the reviews from users
who have used the data, so that other data users can trust the data they are
3 Proposed System Model
In this section, we present an Ethereum blockchain based solution to provide
an automated review system for monetization of IoT data using smart con-
tracts by taking motivation from  and . Ethereum blockchain platform
is used because it is open source, and public users can access it easily. It is a
distributed virtual machine with crypto-currency payments and developers are
free to execute their smart contracts. Smart contracts eliminate the third party
risk associated with exchange of payments in IoT monetization. Proposed system
comprises of seven main entities interacting with each other. Main entities of the
system include: device owner having an IoT device, MQTT broker , review
system, smart contracts, arbitrator, users and blockchain database. The process
starts with creating a smart contract using solidity language where owner of the
IoT device deﬁnes set of rules for the sale of IoT device data. Previous customers
who had accessed the data, had provided reviews about the data used, which are
stored in the blockchain. New customers who want to use this data can interact
with the smart contract to get the reviews and ratings along with exchange of
payments. Review system is available for the users to analyze the quality of data
they want to use.
Metadata, reviews and ratings are stored in the blockchain however, because
of the security and storage purposes data is stored in MQTT broker. Owner
sends data to MQTT broker and making use of review system , when any
user request the data, reviews and ratings, smart contract is triggered and unique
token is provided to the user. Smart contract also provide the customer unique
token to the MQTT broker for authentication.
Reputation System for IoT Data Monetization Using Blockchain 177
3.1 System Model Components
The main components of the system model are discussed below. All main
components contain Ethereum addresses for identiﬁcation of their accounts in
Ethereum blockchain. The interaction between the smart contracts and main
components is as follows:
•Owner: At ﬁrst, IoT device contract is created by the owner of the device.
Owner also speciﬁes the rate for each topic in the contract depending on the
topic information and length. Owner of device data encrypts the data which
is to be stored in MQTT broker and sends private key to the smart contracts.
Customers must have to deposit money to smart contracts before making
transaction. Rates for the topics are decided in agreement with MQTT broker,
because broker has to store them. Successful data access triggers the deposit
function and payment is transferred to the ether wallet of the owner.
•IoT Device Contract: All the logic and code of the system is written in the
•MQTT Broker: MQTT broker holds the data and provides this data to user
on demand. Smart contract provides the customer token to broker so that
broker can authenticate the user.
the HTML code. Application binary interface (ABI) and bytecode values of
gramming interface is the communication medium between smart contracts
contract functions to execute the transactions. When user interact with the
input. Output is displayed when block is mined successfully. When user on
the web page calls the function, transaction occurs and added to the block
through mining. We have used geth interface to run the mining server. Remote
procedure call (RPC) protocol is used by the geth interface.
Web page and web browser are connected using Node.js and web page is
created using HTML and CSS. User will open the web browser and then con-
nected web page will also open. When a contract is deployed, user will choose
the account address and write the review. User who wants to check the exist-
smart contract functions.
•User: Users will interact with the smart contracts, broker and review system
and will pay for the data they want to use. User is allowed to subscribe,
review, access data, add review, modify review. User is provided with the
decryption key to decrypt and use data.
•Arbitrator: Arbitrator is a trusted entity selected by the owner and system
administration. Arbitrator will get incentive, to act honestly and perform the
two speciﬁed tasks from the owner. Owner will provide some privileges to
arbitrator to download the data and provide reviews to handle dispute and
fake reviews (Fig. 1).
178 A. Javaid et al.
4 Smart Contract: Review System for IoT Data
The proposed blockchain system focusses on keeping and managing reviews,
ratings, and metadata about the data stored in MQTT broker. These reviews
and ratings are stored in blockchain as a result of the user interactions. After
using data, user writes review and rating before leaving the system depending
upon his experience. In this Section, discussion about the functions and smart
contract is provided. Smart contract code is written, using solidity language.
•Add Topic: Firstly, IoTContract is created by the device owner using the con-
structor of the contract. Owner then identiﬁes the default topics and MQTT
broker’s address. Smart contract registers the MQTT broker and topic is
added using the Add Topic function.
•Deposit: Interested customers who want to access this data will deposit ethers
using the Deposit function to the contract.
•Subscribe: Before, accessing the topic customer has to subscribe the topic
which they want to access.
•Is Review Exist: User triggers this function to check whether reviews exist
for the data he/she subscribed.
Review System for IoT Data Monezaon
MQTT Connecon MQTT Connecon
Request and Submit
JS Services Request Data
Owner deﬁnes rules
Fig. 1. Blockchain based patient driven interoperability.
Reputation System for IoT Data Monetization Using Blockchain 179
•Get Reviews: Customer will make request to smart contract for the reviews of
the subscribed topic. Then this function returns the existing review for sub-
scribed data. Data structure which saves the reviews consists “dt −contents”
which is string value.
•Get Ratings: Customer will make request to smart contract for the rating of
the subscribed topic. Then this function returns the existing rating for sub-
scribed data. Data structure which saves the reviews consists “dt −ratings”
which is a rating value for the string.
•Acces s : After, analyzing the review and ratings about data, if user is satis-
ﬁed he/she can access the topic by calling access function. Smart contract
then authenticates, if user has subscription and deposited money. Smart con-
tract will grant access usage time, and unique token to user. The message is
broadcasted and broker also have user unique token for user authentication.
Every user will have a unique token because contract hashes the concatena-
tion of several variables which include: owner and customer address, topic id,
and total number of accesses. User access time for the data depends on the
amount of money in his account. When account ethers are utilized, user is
not able to access data further.
•Get Data Content: If user want to get a copy of data to be downloaded on
his system. User will invoke this function and get the data oﬀchain. Smart
contract will send decryption key to user, after user has invoked this function.
User using this decryption key will decrypt the data. To download data, user
must have enough balance in his account.
•Update Subscription: When user disconnects or account balance is used, bro-
ker will call this function and customer balance is updated according to the
usage time or downloaded data. Smart contract then sends the money to the
•Ref und : In case, if there are ethers left in the user’s account and user discon-
nects, then these ethers will be refunded to the user. This function will also
be triggered, when arbitrator ﬁnds problem in the user downloaded ﬁle.
•Set Reviews: User and arbitrator will provide reviews after using and analyz-
ing data and is provided with incentive through incentive mechanism.
5 Results and Discussion
In Ethereum blockchain gas is of fundamental importance because it reﬂects
the computational complexity of the transactions having number of diﬀerent
operations. As a result of any request when transaction occurs, smart contracts
are executed. In the network at every node instructions are executed and there is
a cost for every operation which is expressed as number of gas units. Transaction
is the operation which adds something to the blockchain or modiﬁes its state.
Transaction cost or gas cost for a transaction depends on the size and complexity
of the smart contract. Transaction cost is the cost of sending data to blockchain
and is concerned with the transaction’s base cost and contract deployment cost
180 A. Javaid et al.
Access Get Data Set Revie w s Ref u n d
Ex ec u t ion Ga s
Tra ns act ion Ga s
Fig. 2. Gas consumption for smart contract functions
Get Rat i ngs Up da t e Get De posi t Rev i e w Exi s t
Ex ec u t ion Ga s
Tra ns act ion Ga s
Fig. 3. Gas consumption for smart contract functions
which are 21000 and 32000 in our case. We can calculate transaction cost of any
transaction, if we know the gas cost using Eq.1.
gwei =GasUsed ×GasCost (1)
In Eq. 1gas used, is the amount of gas used by smart contract or any single
operation of smart contract. Gas cost represents the unit price of gas with cryp-
tocurrency unit of gwei.
In smart contract cost test we have set the default gas price as 10gwei. Dif-
ferent operations of the smart contract uses diﬀerent gas amount. Some smart
contract function costs are given in Table 1. The data trading contract and data
review contract are created once and their costs are $989099 and $90898 respec-
tively. At ﬁrst, the owner of the IoT device adds the topic to MQTT broker
and cost of this transaction is $0.15103. Then customer will perform initial
ether deposit and subscribe the topic. The cost for these two operations is
$0.03880732 and $0.21558128 respectively. Then customer can access to data
and make request for reviews about the data. These two operations have the
Reputation System for IoT Data Monetization Using Blockchain 181
String Length as Trx Input Value
43 820 37
Fig. 4. Gas consumption for string input length
Fig. 5. Mining time for string input length
Table 1. Cost of functions in Ether and USD.
(Functions) Gas used Cost (Ethers) Cost (USD)
Topic added 92091 0.00092091 0.15103
Deposit 23663 0.00023663 0.03880732
Subscribe 131452 0.00131452 0.21558128
Access 70,000 0.0007 0.1148
Get reviews 24476 0.00024476 0.04014064
Get data content 23115 0.00023115 0.0379086
Refund 18352 0.00018352 0.03009728
Set reviews 59362 0.00059362 0.0973537
cost $0.1148 and $0.04014064 respectively. If user is satisﬁed about the data
he/she will invoke the get data content to download the data and this operation
have the cost of $0.0379086. If user did not want to download data money will be
refunded to that user when he invokes the refund function. This operation has
the cost of $0.03009728. At the end user will set reviews and this operation has
total consumption of 59362 gas and actual cost in ethers is $0.00059362 ether,
and USD (0.09735368).
182 A. Javaid et al.
Figure 2shows the result for access, get data content, refund and set review
functions. Access function has gained the highest execution and transaction costs
as compared to other smart contract functions. The user when invokes the access
function smart contracts check whether user has the subscription and provides
a unique token to the user. When this user makes other transactions this token
is used for authentication of that speciﬁc user. Because of these authentications
involved with these functions, they have more cost and gas consumption. Figure3
shows the result for get deposit, get ratings, is review exist and update subscrip-
tion time functions. Ethereum yellow paper is referred  for more informa-
tion regarding to transaction and execution gas. Figure 4shows the relationship
between review string length and gas used to submit that review. Amount of gas
used is increased when string contains more characters. 3200 gas is consumed
when review string length is 32 because gas consumption and review length are
directly proportional to each other. Figure 5shows the mining time for string
input length. Graph shows that there is no relationship between review length
and mining time. At smaller review string length mining time is greater and for
larger review string length mining time is smaller. We can conclude from the
results that mining time is not related to review string length, it depends on
the network conditions and miner’s choice. Customer who has given a detailed
review about the data, cost of the transaction gas will be increased, however
mining time depends upon the network conditions.
IoT devices are becoming everyday part of human life and data produced by
these devices is used to improve the modern civilization. In this paper, we have
presented blockchain based review system for trading data of IoT devices. This
system provides conﬁdence to users, that quality of the data is satisfactory.
Trustful automated payments are done using smart contracts by eliminating
third party risk. In order to consider data integrity and security at ﬁrst only
metadata is provided and reviews cannot be modiﬁed because it is a blockchain
based system. All transactions are done through Ethereum smart contracts and
there is log of every transaction in the blockchain. The security and immutability
of the system is ensured using blockchain based system. The smart contracts are
implemented in solidity language and the system is designed using Visual studio
code. User interface is developed using HTML and CSS.
1. Perera, C., Zaslavsky, A., Christen, P., Georgakopoulos, D.: Sensing as a service
model for smart cities supported by internet of things. Trans. Emerg. Telecommun.
Technol. 25(1), 81–93 (2014)
2. Xie, R., He, C., Xie, D., Gao, C., Zhang, X.: A secure ciphertext retrieval scheme
against insider kgas for mobile devices in cloud storage. Secur. Commun. Netw.
Reputation System for IoT Data Monetization Using Blockchain 183
3. Fan, L., Lei, X., Yang, N., Duong, T.Q., Karagiannidis, G.K.: Secure multiple
amplify-and-forward relaying with cochannel interference. IEEE J. Sel. Top. Signal
Process. 10(8), 1494–1505 (2016)
4. Shen, J., Gui, Z., Ji, S., Shen, J., Tan, H., Tang, Y.: Cloud-aided lightweight certiﬁ-
cateless authentication protocol with anonymity for wireless body area networks.
J. Netw. Comput. Appl. 106, 117–123 (2018)
5. Tao, M., Ota, K., Dong, M., Qian, Z.: AccessAuth: capacity-aware security access
authentication in federated-IoT-enabled V2G networks. J. Parallel Distrib. Com-
put. 118, 107–117 (2018)
6. Chen, J., He, K., Yuan, Q., Xue, G., Du, R., Wang, L.: Batch identiﬁcation game
model for invalid signatures in wireless mobile networks. IEEE Trans. Mob. Com-
put. 16(6), 1530–1543 (2016)
7. Xu, B., Da Xu, L., Cai, H., Xie, C., Hu, J., Bu, F.: Ubiquitous data accessing
method in IoT-based information system for emergency medical services. IEEE
Trans. Ind. Inform. 10(2), 1578–1586 (2014)
8. Jiang, L., Da Xu, L., Cai, H., Jiang, Z., Bu, F., Xu, B.: An IoT-oriented data
storage framework in cloud computing platform. IEEE Trans. Ind. Inform. 10(2),
9. Yu, B., Wright, J., Nepal, S., Zhu, L., Liu, J., Ranjan, R.: IoTChain: establishing
trust in the internet of things ecosystem using blockchain. IEEE Cloud Comput.
5(4), 12–23 (2018)
10. Sharma, P.K., Park, J.H.: Blockchain based hybrid network architecture for the
smart city. Future Gener. Comput. Syst. 86, 650–655 (2018)
11. Jiang, T., Fang, H., Wang, H.: Blockchain-based Internet of vehicles: distributed
network architecture and performance analysis. IEEE Internet Things J. 6, 4640–
12. El Kaed, C., Khan, I., Van Den Berg, A., Hossayni, H., Saint-Marcel, C.: SRE:
semantic rules engine for the industrial Internet-of-Things gateways. IEEE Trans.
Ind. Inform. 14(2), 715–724 (2017)
13. Hossain, M.S., Muhammad, G.: Cloud-assisted industrial internet of things (IIoT)-
enabled framework for health monitoring. Comput. Netw. 101, 192–202 (2016)
14. Huang, J., Kong, L., Chen, G., Wu, M.Y., Liu, X., Zeng, P.: Towards secure indus-
trial IoT: blockchain system with credit-based consensus mechanism. IEEE Trans.
Ind. Inform. 15, 3680–3689 (2019)
15. Xu, Q., Aung, K.M.M., Zhu, Y., Yong, K.L.: A blockchain-based storage system
for data analytics in the internet of things. In: New Advances in the Internet of
Things, pp. 119–138. Springer, Cham (2018)
16. Hammi, M.T., Hammi, B., Bellot, P., Serhrouchni, A.: Bubbles of trust: a decentral-
ized blockchain-based authentication system for IoT. Comput. Secur. 78, 126–142
17. Mateen, A., Javaid, N., Iqbal, S.: Towards energy eﬃcient routing in blockchain
based underwater WSNs via recovering the void holes, MS thesis, COMSATS Uni-
versity Islamabad (CUI), Islamabad, Pakistan, July 2019
18. Naz, N., Javaid,N., Iqbal, S.: Research based data rights management using
blockchain over ethereum network, MS thesis, COMSATS University Islamabad
(CUI), Islamabad, Pakistan, July 2019
19. Javaid, A., Javaid, N., Imran, M.: Ensuring analyzing and monetization of data
using data science and blockchain in loT Devices, MS thesis, COMSATS University
Islamabad (CUI), Islamabad, Pakistan, July 2019
184 A. Javaid et al.
20. Zainab Kazmi, H.S., Javaid, N., Imran, M.: Towards energy eﬃciency and trustful-
ness in complex networks using data science techniques and blockchain, MS thesis,
COMSATS University Islamabad (CUI), Islamabad, Pakistan, July 2019
21. Zahid, M., Javaid, N., Babar Rasheed, M.: Balancing electricity demand and sup-
ply in smart grids using blockchain, MS Thesis, COMSATS University Islamabad
(CUI), Islamabad, Pakistan, July 2019
22. Noshad, Z., Javaid, N., Imran, M.: Analyzing and securing data using data science
and blockchain in smart networks, MS thesis, COMSATS University Islamabad
(CUI), Islamabad, Pakistan, July 2019
23. Ali, I., Javaid, J., Iqbal, S.: An incentive mechanism for secure service provision-
ing for lightweight clients based on blockchain, MS thesis, COMSATS University
Islamabad (CUI), Islamabad, Pakistan, July 2019
24. Khan, J.H., Javaid, N., Iqbal, S.: Blockchain based node recovery scheme for wire-
less sensor networks. MS thesis, COMSATS University Islamabad (CUI), Islam-
abad, Pakistan, July 2019
25. Samuel, O., Javaid, N., Awais, M., Ahmed, Z., Imran, M., Guizani, M.: A
blockchain model for fair data sharing in deregulated smart grids. In: IEEE Global
Communications Conference (GLOBCOM), July 2019
26. Rehman, M., Javaid, N., Awais, M., Imran, M., Naseer, N.: Cloud based Secure
Service Providing for IoTs using Blockchain. In: IEEE Global Communications
Conference (GLOBCOM) (2019)
27. Awais, M., Javaid, M., Imran, M.: Energy eﬃcient routing with void hole allevi-
ation in underwater wireless sensor networks, MS thesis, COMSATS University
Islamabad (CUI), Islamabad, Pakistan, July 2019
28. Suliman, A., Husain, Z., Abououf, M., Alblooshi, M., Salah, K.: Monetization of
IoT data using smart contracts. IET Netw. 8, 32–37 (2018)
29. Park, J.S., Youn, T.Y., Kim, H.B., Rhee, K.H., Shin, S.U.: Smart contract-based
review system for an IoT data marketplace. Sensors 18(10), 3577 (2018)
30. Wood, G.: Ethereum: a secure decentralised generalised transaction ledger.
Ethereum Proj. Yellow Pap. 151, 1–32 (2014)