SlideShare a Scribd company logo
BOHR International Journal of Smart Computing
and Information Technology
2023, Vol. 4, No. 1, pp. 50–54
DOI: 10.54646/bijscit.2023.36
www.bohrpub.com
METHODS
An improvement in the safety of big data using blockchain
technology
Archana1* and Gaurav Aggarwal2*
1Department of Computer Science, Govt. PG College for Women, Rohtak, India
2Department of Computer Science, Jagannath University, Jhajjar, India
*Correspondence:
Archana,
archana300030@gmail.com
Gaurav Aggarwal,
gauravaggarw@gmail.com
Received: 25 July 2023; Accepted: 12 August 2023; Published: 24 August 2023
The development of big data in the information technology sector has made data management and analysis far
more challenging. It is necessary to take into account everything, including volume, variety, speed, value, and
complexity. Clustering makes the processing of vast volumes of data simpler. This is especially helpful when
working with unstructured data. By the usage of cloud computing, which makes use of the internet as its delivery
channel, it is possible to provide a variety of computer services, including servers, storage, databases, and
networking, in addition to analytics and intelligence, at a lower cost. The main problem is the security of such
big amounts of data. One way to enforce strong security is blockchain technology which is also the backbone of
cryptocurrency. The distributed, incontrovertible, and publicly verifiable record of every transaction activity that may
be provided by blockchain technology has the potential to revolutionize security in a big way for different industries.
Keywords: big data, security, block chain, clustering, inconsistency
Introduction
Big data is a reference to the ever-increasing amount
of data that cannot be processed by traditional database
techniques. Due to its huge size, unstructured as well as
structured data, and complexity, standard data management
technologies are unable to effectively store or process
the information. Some examples of big data include the
following: New York Stock Exchange, which generates
around one terabyte worth of fresh trading data every single
day. The estimates provided by Facebook indicate that more
than 500 gigabytes of fresh data are being uploaded to the
site’s databases on a daily basis. The key ways in which these
data are collected include users uploading photographs and
videos, engaging in discussions with one another, posting
comments, and so on.
Characteristics of big data
Big data can be described by the following characteristics:
a) Volume: The phrase “big data” refers to an extremely
large quantity of data. When you have access to
a vast amount of information, it is essential to
make the most of its potential applications. The
quantity of information that is required to categorize
anything is one major aspect that determines
whether or not it is considered “big data.” The
volume of data is particularly high in banking
and other financial institutions, social media, and
entertainment industries.
b) Variety: The second facet of big data that has to
be taken into consideration is its level of diversity.
The concepts of structured and unstructured data are
both included under the umbrella word “variety.” In
50
10.54646/bijscit.2023.36 51
the past, the majority of applications did little more
than save data in spreadsheets and databases and then
retrieve it when necessary. At the moment, analytical
applications make use of a broad variety of data
sources with structured, semi-structured, as well as
unstructured data; some examples of which include
emails, photographs, videos, documents in PDF
format, monitoring devices, and audio recordings.
Data storage, data mining, and data analysis are
all made more challenging by the presence of
unstructured data.
c) Velocity: In the context of big data, the word “velocity”
refers to the pace at which new data are generated. The
speed at which new data are generated and processed
will influence how much of the data’s potential can
be realized. What is known as “Big Data Velocity”
is a concept that was developed as a result of the
contributions made by business processes, log files,
networks, social media, sensors, and mobile devices.
There is a rapid flow of information that involves
a significant volume of data. The velocity of data
is particularly high for the banking, healthcare, and
manufacturing sectors.
d) Inconsistency: It may be difficult to efficiently manage
and analyze the data due to the variability that may
arise in the data. This makes it a potential challenge.
Advantages of big data processing
There are several reasons why big data processing is
beneficial:
1. Businesses have the option of incorporating outside
information into decision-making. Due to the
availability of social data gleaned from search engines
and sites such as Facebook and Twitter, organizations
are able to fine-tune their business plans according to
user sentiment and changes in choices.
2. Improved customer service: Conventional means of
gathering input from customers are being phased
out in favor of big data technology. With these new
platforms, the responses received from customers are
studied and assessed with the use of big data and
natural language processing technologies.
3. An early evaluation of any possible risks that may
be associated with the product or service will lead to
preventive actions for the risks.
4. The big data environment allows for the pre-
processing of larger data sets before they are
transferred to the warehouse, which improves the
operational efficiency of the business. The combination
of big data and data warehouses also assists businesses
in offloading data that are needed less often.
Cluster
In a computer cluster, two or more individual computers, also
known as nodes, collaborate with one another to carry out a
specific task. Because of this, it is feasible to distribute huge
tasks that can be done in parallel throughout the nodes that
make up the cluster. Performance is boosted as a result of the
fact that the combined memory and processing capabilities
of each machine may benefit a variety of operations. Since
each individual node in a computer cluster has to be able
to interact with the other nodes in the cluster, the building
of a computer cluster requires the use of an internodes
network. In order to construct a cluster, the nodes must
first be connected via the use of cluster software. A storage
device that is shared across the nodes and/or a storage device
that is local to each node are both potential solutions. It
is common practice to designate at least one of the nodes
as a leader node, which then operates as the entry point
for the cluster. This node could be in charge of delegating
responsibilities to the subordinates and, if that is required,
gathering the results before relaying them to an external
party. Also, the communication between nodes in a cluster
has to be optimized so that latency may be reduced and
bottlenecks can be avoided.
Blockchain technology
Blockchain technology is the term that describes the technical
basis upon which Bitcoin currency is built. Because of this
technology, it is possible to carry out any transaction in
a way that is not governed by any central authority. The
participation of a middleman or broker is not required in
order for it to take place. As it creates records of transactions
that are decentralized, unchangeable, and publicly verifiable,
Blockchain technology has the potential to revolutionize a
wide variety of industries.
Blockchains store the data differently from standard
databases, which store the data in rows and columns that
are hash-linked together, while blockchains store the data in
blocks that are cryptographically connected together. Each
new piece of information that is received results in the
creation of a new block in the database. After a block has
been filled with information, the data included inside it are
connected to one another in the order that chronological
events occurred.
While a blockchain may be used to store a wide range of
data types, the use that has proven to be the most successful
to this point is that of a ledger for the recording of financial
transactions. There is not a single person or group in control
of Bitcoin’s use of the blockchain; rather, all users collectively
hold the reins. Blockchain is used to record transactions
related to Bitcoin transactions. With the use of blockchains,
digital information may be saved and distributed, but it
cannot be changed once it has been recorded. Because of this,
52 Archana and Aggarwal
a blockchain may be used as the foundation for immutable
ledgers, which are essentially recordings of transactions
that are incorruptible in any way. Blockchains are often
referred to as “distributed ledger technology” as a direct
consequence of this fact.
Features of blockchain technology
The key points depicting features of blockchain technology
are cited ahead:
a) Immutability is the state of being incapable of
undergoing any kind of change or transformation. This
is an essential component of blockchain that assures
the long-term survival of the technology as it is a
network that cannot be altered and is permanent.
b) Decentralized: As the network is decentralized, there is
not a single person who is in charge of supervising the
infrastructure. This means that security and privacy
are not compromised. Decentralization of the network
is ensured through the use of a dispersed collection
of nodes that are responsible for its management. It
is able to store anything of value, including Bitcoins,
important documents, contracts, and other valuable
digital assets. After then, with the assistance of the
blockchain, you will be able to have direct control
over them by making use of your private key. As a
consequence of this, the general public regains both
control and ownership of the assets as a result of the
decentralized structure.
c) Improved security: In the blockchain, every piece of
data is encrypted and hashed using a new method each
time. This provides an additional layer of protection
against unauthorized access. To put it another way,
the information provided by the network hides the
fundamental characteristics of the data. Mathematical
techniques may be used to any data as an input to
generate various values, but the length of the output
always stays the same. A one-of-a-kind identification is
assigned to each individual piece of data. In the ledger,
each new block is given its own one-of-a-kind hash and
also includes the hash of the block that came before it.
A fresh set of hash IDs will be generated in the event
that the data are altered in any way. And even that is
a bit of a stretch, to say the least. The user is going to
need both a private key and a public key in order to get
access to the data.
d) Hashing cannot be undone in any case. Hashing is
a very complicated process, and it is not feasible to
modify or undo it in any way. Nobody will ever be able
to take a public key and turn it into a private key.
e) Distributed ledger: With a public ledger, this
information is often accessible to anybody who is
a member of the general public. There is nowhere
to run since everything is out in the open. There
is, however, an exception to this general rule for
blockchains that are either private or federated.
In spite of this, a significant number of users are
able to see the ledger at any one time under these
circumstances. As a consequence of this, the ledger
that represents the network is continually updated by
everyone else who is using the system. This distributed
the processing power among the several machines in
order to get a more favorable outcome.
f) Consensus: The techniques used to reach consensus
are essential to the operation of any blockchain. The
intelligent design of this architecture is based on
consensus algorithms, which serve as its foundation.
Every blockchain has to have a consensus in order
to function properly. The network’s ability to reach a
consensus is directly responsible for the credibility of
the network. The nodes that make up a network may
not have much confidence in one another, but they
could have faith in the algorithms that drive it. As a
consequence of this, the blockchain is improved by
every decision that is taken on the network. Using the
blockchain provides this as one of its many benefits.
g) Quicker settlement: The processing of transactions
via traditional banking systems may often take
a very lengthy period. But, with the assistance
of blockchains and other contemporary systems,
monetary transactions may be completed in a shorter
amount of time, saving the user important time.
Role of blockchain in big data
The fact that everything that takes place on a blockchain is
encrypted makes it capable of providing the greatest possible
degree of security. In a similar fashion, the data that are saved
on the blockchain cannot be changed. To be on the safe side,
the file signatures of all of the nodes in the network may be
checked across all of the ledgers in the network to make sure
that they have not been altered. If the record is modified in
any way, the signature will no longer be valid.
The applications of big data and blockchain are mutually
beneficial. Big data technologies can handle any data,
regardless of its variety, velocity, or volume. Blockchain
applications simplify operations in any industry. The
traditional information processing architecture and business
transaction processing have been rendered obsolete as big
data and blockchain technologies have grown over the last
several years. This has made it possible to abandon these
processes. It is necessary for big data to have processing
power that is capable of handling big data’s processing
capacity; conversely, big data requires processing power that
is capable of handling the complexity of blockchain and
its fast growth.
10.54646/bijscit.2023.36 53
FIGURE 1 | Research methodology.
This sheds light on several implementations of blockchain
technology in big data among various industries:
1. Accelerating the financial services sector, the
combination of blockchain technology and large
amounts of data held by financial institutions will
make it possible to estimate risk and spot suspicious
trends in real time. Making use of blockchain
technology as a way of conducting transactions would
assist to safeguard banks and their clients from fraud,
speed up the process of transactions, and minimize
the cost of transferring money between accounts. For
instance, in the most recent few years, in order to
streamline the process of moving money from one
bank account to another using technology known as
blockchain, an association consisting of 47 Japanese
banks joined a blockchain business known as Ripple.
The goal here is to carry out real-time transfers while
minimizing associated costs. The cost of conventional
real-time transactions is high because of the possibility
of risk factors such as double spending, which may be
avoided with blockchain technology.
2. Security in businesses other than banking: Businesses
in healthcare, public administration, and other
areas have begun adopting blockchain technology
to manage data and thwart hacking attempts and
avoid data breaches.
3. Monitoring of the supply chain: A blockchain is
employed to maintain tabs on the commodities that
make up the supply chain, and a mobile app is utilized
to monitor the locations of these commodities as they
move. Walmart is a wonderful example of this as it uses
the technology of blockchains to enhance food safety
by allowing for more accurate monitoring of items
from the farm to the shop shelf. Users have the ability
to get credible information on the provenance of their
food while using this strategy (Figure 1).
Conclusion
The proposed research is supposed to be capable to resolve
the security issue in big data using blockchain. This research
would provide a solution to confirm the impact of blockchain
on big data security. The goal of the proposed work is to
make use of big data with blockchain applicable in real-
life scenario. The proposed work offers a broad range of
options and flexibility. Improved precision and efficiency are
expected as a result of this investigation. The proposed work
provides a wide range of possibilities and adaptability.
References
1. Mechkaroska D, Popovska-mitrovikj A, Dimitrova V. Secure big data
and IoT with implementation of blockchain technology. Int Sci J Secur
Fut. (2018) 185:183–5.
2. Tariq N, Asim M, Al-Obeidat F, Zubair Farooqi M, Baker T,
Hammoudeh M, et al. The security of big data in fog-enabled IoT
applications including blockchain: a survey. Sensors (2019) 19:1788. doi:
10.3390/s19081788
3. Ferrag MA, Maglaras L, Janicke H. Blockchain and its role in the internet
of things. In: Kavoura A, Kefallonitis E, Giovanis A editors. Strategic
innovative marketing and tourism. Berlin: Springer (2019). p. 1029–38.
doi: 10.1007/978-3-030-12453-3_119
54 Archana and Aggarwal
4. Dujak D, Sajter D. Blockchain applications in supply. Berlin: Springer
International Publishing (2019). doi: 10.1007/978-3-319-91668-2_2
5. Valdeolmillos D, Mezquita Y, González-Briones A, Prieto J, Corchado
JM. Blockchain technology: a review of the current challenges
of cryptocurrency. Proceedings of the blockchain and applications
international congress. Berlin: Springer (2020). p. 153–60. doi: 10.1007/
978-3-030-23813-1_19
6. Bertino E, Ferrari E. Big data security and privacy. In: Flesca S, Greco
S, Masciari E, Saccà D editors. A comprehensive guide through the
Italian database research over the last 25 years. Cham: Springer (2018).
p. 425–39. doi: 10.1007/978-3-319-61893-7_25
7. Babar M, Arif F. Real-time data processing scheme using big data
analytics in internet of things based smart transportation environment.
J Ambient Intell Human Comput. (2018) 10:4167–77. doi: 10.1007/
s12652-018-0820-5
8. Dasgupta D, Shrein JM, Datta K. A survey of blockchain from security
perspective. J Bank Financ Technol. (2018) 3:1–17. doi: 10.1007/s42786-
018-00002-6
9. Kumar A, Abhishek K, Nerurkar P, Khosravi MR, Rukunuddin M,
Shankar A. Big data analytics to identify illegal activities on bitcoin
blockchain for IoMT. Pers Ubiquit Comput. (2021) 1–12. doi: 10.1007/
s00779-021-01562-z
10. Meng Y, Nazir S. A decision support system for the uses of lightweight
blockchain designs for P2P computing. Peer Peer Netw Appl. (2021)
14:2708–18. doi: 10.1007/s12083-021-01083-9
11. Niranjanamurthy M, Nithya BN, Jagannatha S. Analysis of blockchain
technology: pros, cons and SWOT. Cluster Comput. (2018) 22. doi:
10.1007/s10586-018-2387-5
12. Singh SP, Nayyar A, Kumar R, Sharma A. Fog computing: from
architecture to edge computing and big data processing. J Supercomput.
(2019) 75:2070–105. doi: 10.1007/s11227-018-2701-2
13. Zhang P, Lu Q, Hu X, Gu S, Yang L, Min M, et al. Latest progress of
the Chinese meteorological satellite program and core data processing
technologies. Adv Atmos Sci. (2019) 36:1027–45. doi: 10.1007/s00376-
019-8215-x
14. Azmoodeh A, Dehghantanha A, Choo KR. Big data and internet
of things security and forensics: challenges and opportunities.
In: Dehghantanha A, Choo KK editors. Handbook of big data and
IoT security. Cham: Springer (2019). p. 10–3. doi: 10.1007/978-3-030-
10543-3
15. Ahmadvand H, Goudarzi M, Foroutan F. Gapprox: using Gallup
approach for approximation in big data processing. J. Big Data (2019)
6:20. doi: 10.1186/s40537-019-0185-4
16. Silva BN, Diyan M, Han K. Big data analytics. Berlin: Springer (2019).
doi: 10.1007/978-981-13-3459-7_2
17. Rathee G, Sharma A. A hybrid framework for multimedia data
processing in IoT-healthcare using blockchain technology. Multimed
Tools Appl. (2019) 79:9711–33. doi: 10.1007/s11042-019-07835-3
18. Calvaresi D, Leis M, Dubovitskaya A, Schegg R, Schumacher M. Trust
in tourism via blockchain technology: results from a systematic review.
Berlin: Springer International Publishing (2019).
19. Czachorowski K, Solesvik M, Kondratenko Y. The application of
blockchain technology in the maritime industry. Berlin: Springer
International Publishing (2019). doi: 10.1007/978-3-030-00253-4_24
20. Khan MM, Ikram M. Use of blockchain in education: a systematic
literature review. In: Nguyen NT, Gaol FL, Hong T-P, Trawński B editors.
Intelligent information and database systems. Cham: Springer (2019).
p. 191–202. doi: 10.1007/978-3-030-14802-7_17
21. Xu M, Chen X, Kou G. A systematic review of blockchain. Financ Innov.
(2019) 5:27. doi: 10.1186/s40854-019-0147-z
22. Firdaus A, Faizal M, Razak A, Feizollah A. The rise of “blockchain”:
bibliometric analysis of blockchain study. Scientometrics (2019)
120:1289–331. doi: 10.1007/s11192-019-03170-4
23. Chen J, Lv Z, Song H. Design of personnel big data management system
based on blockchain. Fut .Gener Comput Syst. (2019) 101:1122–9. doi:
10.1016/j.future.2019.07.037
24. Nandan S, Ramya KC, Sheeba Rani S, Gupta D, Shankar K,
Lakshmanaprabu SK, et al. An efficient lightweight integrated
blockchain (ELIB) model for IoT security and privacy. Fut Gener
Comput Syst. (2020) 102:1027–37. doi: 10.1016/j.future.2019.09.050
25. Deepa N, Pham VQ, Nguyen DC, Bhattacharya S, Prabadevi B,
Gadekallu TR, et al. A survey on blockchain for big data: approaches,
opportunities, and future directions. Fut Gener Comput Syst. (2022) 131.
doi: 10.1016/j.future.2022.01.017

More Related Content

Similar to An improvement in the safety of big data using blockchain technology

Design of access control framework for big data as a service platform
Design of access control framework for big data as a service platformDesign of access control framework for big data as a service platform
Design of access control framework for big data as a service platform
International Journal of Reconfigurable and Embedded Systems
 
Blockchain and AI
Blockchain and AIBlockchain and AI
Blockchain and AI
Ahmed Banafa
 
An interactive Study on secure data sharing in the IOT through Blockchain
An interactive Study on secure data sharing in the IOT through BlockchainAn interactive Study on secure data sharing in the IOT through Blockchain
An interactive Study on secure data sharing in the IOT through Blockchain
IRJET Journal
 
A survey on security and policy aspects of blockchain technology
A survey on security and policy aspects of blockchain technologyA survey on security and policy aspects of blockchain technology
A survey on security and policy aspects of blockchain technology
TELKOMNIKA JOURNAL
 
IRJET- Blockchain for Large-Scale Internet of Things Data Storage and Protection
IRJET- Blockchain for Large-Scale Internet of Things Data Storage and ProtectionIRJET- Blockchain for Large-Scale Internet of Things Data Storage and Protection
IRJET- Blockchain for Large-Scale Internet of Things Data Storage and Protection
IRJET Journal
 
"Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech...
"Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech..."Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech...
"Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech...
IRJET Journal
 
jayesh_Blockchain.pptx
jayesh_Blockchain.pptxjayesh_Blockchain.pptx
jayesh_Blockchain.pptx
JackTheMan1
 
IRJET -Securing Data in Distributed System using Blockchain and AI
IRJET -Securing Data in Distributed System using Blockchain and AIIRJET -Securing Data in Distributed System using Blockchain and AI
IRJET -Securing Data in Distributed System using Blockchain and AI
IRJET Journal
 
A decentralized consensus application using blockchain ecosystem
A decentralized consensus application using blockchain ecosystem  A decentralized consensus application using blockchain ecosystem
A decentralized consensus application using blockchain ecosystem
IJECEIAES
 
IRJET- Blockchain Technology in Cloud Computing : A Systematic Review
IRJET-  	  Blockchain Technology in Cloud Computing : A Systematic ReviewIRJET-  	  Blockchain Technology in Cloud Computing : A Systematic Review
IRJET- Blockchain Technology in Cloud Computing : A Systematic Review
IRJET Journal
 
HEALTHCHAIN: A Patient Centric Blockchain Based Web Application For Maintaini...
HEALTHCHAIN: A Patient Centric Blockchain Based Web Application For Maintaini...HEALTHCHAIN: A Patient Centric Blockchain Based Web Application For Maintaini...
HEALTHCHAIN: A Patient Centric Blockchain Based Web Application For Maintaini...
IRJET Journal
 
HDI - Blockchain White Paper
HDI - Blockchain White PaperHDI - Blockchain White Paper
HDI - Blockchain White Paper
David MANSET
 
IRJET-Block Chain based Cyber Security System for Data Transfer
IRJET-Block Chain based Cyber Security System for Data TransferIRJET-Block Chain based Cyber Security System for Data Transfer
IRJET-Block Chain based Cyber Security System for Data Transfer
IRJET Journal
 
Electronic Health Records (EHR) storage using blockchain
Electronic Health Records (EHR) storage using blockchainElectronic Health Records (EHR) storage using blockchain
Electronic Health Records (EHR) storage using blockchain
IRJET Journal
 
IMPLEMENTING BLOCKCHAIN ASSISTED PUBLIC KEY ENCRYPTION TECHNIQUE IN CLOUD COM...
IMPLEMENTING BLOCKCHAIN ASSISTED PUBLIC KEY ENCRYPTION TECHNIQUE IN CLOUD COM...IMPLEMENTING BLOCKCHAIN ASSISTED PUBLIC KEY ENCRYPTION TECHNIQUE IN CLOUD COM...
IMPLEMENTING BLOCKCHAIN ASSISTED PUBLIC KEY ENCRYPTION TECHNIQUE IN CLOUD COM...
IRJET Journal
 
Distributed ledger technical research in central bank of brazil
Distributed ledger technical research in central bank of brazilDistributed ledger technical research in central bank of brazil
Distributed ledger technical research in central bank of brazil
mustafa sarac
 
Blockchain Technology and Its Application in Artificial Intelligence and Mach...
Blockchain Technology and Its Application in Artificial Intelligence and Mach...Blockchain Technology and Its Application in Artificial Intelligence and Mach...
Blockchain Technology and Its Application in Artificial Intelligence and Mach...
Dr. Kotrappa Sirbi
 
Blockchain for AI: Review and Open. Research Challenges K. SALAH, M. H. REHMA...
Blockchain for AI: Review and Open. Research Challenges K. SALAH, M. H. REHMA...Blockchain for AI: Review and Open. Research Challenges K. SALAH, M. H. REHMA...
Blockchain for AI: Review and Open. Research Challenges K. SALAH, M. H. REHMA...
eraser Juan José Calderón
 
Information governance and blockchain
Information governance and blockchainInformation governance and blockchain
Information governance and blockchain
Metataxis
 
How Blockchain Development Can Revolutionize Your Digital Strategy.pdf
How Blockchain Development Can Revolutionize Your Digital Strategy.pdfHow Blockchain Development Can Revolutionize Your Digital Strategy.pdf
How Blockchain Development Can Revolutionize Your Digital Strategy.pdf
Pixel Softwares
 

Similar to An improvement in the safety of big data using blockchain technology (20)

Design of access control framework for big data as a service platform
Design of access control framework for big data as a service platformDesign of access control framework for big data as a service platform
Design of access control framework for big data as a service platform
 
Blockchain and AI
Blockchain and AIBlockchain and AI
Blockchain and AI
 
An interactive Study on secure data sharing in the IOT through Blockchain
An interactive Study on secure data sharing in the IOT through BlockchainAn interactive Study on secure data sharing in the IOT through Blockchain
An interactive Study on secure data sharing in the IOT through Blockchain
 
A survey on security and policy aspects of blockchain technology
A survey on security and policy aspects of blockchain technologyA survey on security and policy aspects of blockchain technology
A survey on security and policy aspects of blockchain technology
 
IRJET- Blockchain for Large-Scale Internet of Things Data Storage and Protection
IRJET- Blockchain for Large-Scale Internet of Things Data Storage and ProtectionIRJET- Blockchain for Large-Scale Internet of Things Data Storage and Protection
IRJET- Blockchain for Large-Scale Internet of Things Data Storage and Protection
 
"Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech...
"Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech..."Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech...
"Unravelling the Challenges: A Deep Dive into the Problems of Blockchain Tech...
 
jayesh_Blockchain.pptx
jayesh_Blockchain.pptxjayesh_Blockchain.pptx
jayesh_Blockchain.pptx
 
IRJET -Securing Data in Distributed System using Blockchain and AI
IRJET -Securing Data in Distributed System using Blockchain and AIIRJET -Securing Data in Distributed System using Blockchain and AI
IRJET -Securing Data in Distributed System using Blockchain and AI
 
A decentralized consensus application using blockchain ecosystem
A decentralized consensus application using blockchain ecosystem  A decentralized consensus application using blockchain ecosystem
A decentralized consensus application using blockchain ecosystem
 
IRJET- Blockchain Technology in Cloud Computing : A Systematic Review
IRJET-  	  Blockchain Technology in Cloud Computing : A Systematic ReviewIRJET-  	  Blockchain Technology in Cloud Computing : A Systematic Review
IRJET- Blockchain Technology in Cloud Computing : A Systematic Review
 
HEALTHCHAIN: A Patient Centric Blockchain Based Web Application For Maintaini...
HEALTHCHAIN: A Patient Centric Blockchain Based Web Application For Maintaini...HEALTHCHAIN: A Patient Centric Blockchain Based Web Application For Maintaini...
HEALTHCHAIN: A Patient Centric Blockchain Based Web Application For Maintaini...
 
HDI - Blockchain White Paper
HDI - Blockchain White PaperHDI - Blockchain White Paper
HDI - Blockchain White Paper
 
IRJET-Block Chain based Cyber Security System for Data Transfer
IRJET-Block Chain based Cyber Security System for Data TransferIRJET-Block Chain based Cyber Security System for Data Transfer
IRJET-Block Chain based Cyber Security System for Data Transfer
 
Electronic Health Records (EHR) storage using blockchain
Electronic Health Records (EHR) storage using blockchainElectronic Health Records (EHR) storage using blockchain
Electronic Health Records (EHR) storage using blockchain
 
IMPLEMENTING BLOCKCHAIN ASSISTED PUBLIC KEY ENCRYPTION TECHNIQUE IN CLOUD COM...
IMPLEMENTING BLOCKCHAIN ASSISTED PUBLIC KEY ENCRYPTION TECHNIQUE IN CLOUD COM...IMPLEMENTING BLOCKCHAIN ASSISTED PUBLIC KEY ENCRYPTION TECHNIQUE IN CLOUD COM...
IMPLEMENTING BLOCKCHAIN ASSISTED PUBLIC KEY ENCRYPTION TECHNIQUE IN CLOUD COM...
 
Distributed ledger technical research in central bank of brazil
Distributed ledger technical research in central bank of brazilDistributed ledger technical research in central bank of brazil
Distributed ledger technical research in central bank of brazil
 
Blockchain Technology and Its Application in Artificial Intelligence and Mach...
Blockchain Technology and Its Application in Artificial Intelligence and Mach...Blockchain Technology and Its Application in Artificial Intelligence and Mach...
Blockchain Technology and Its Application in Artificial Intelligence and Mach...
 
Blockchain for AI: Review and Open. Research Challenges K. SALAH, M. H. REHMA...
Blockchain for AI: Review and Open. Research Challenges K. SALAH, M. H. REHMA...Blockchain for AI: Review and Open. Research Challenges K. SALAH, M. H. REHMA...
Blockchain for AI: Review and Open. Research Challenges K. SALAH, M. H. REHMA...
 
Information governance and blockchain
Information governance and blockchainInformation governance and blockchain
Information governance and blockchain
 
How Blockchain Development Can Revolutionize Your Digital Strategy.pdf
How Blockchain Development Can Revolutionize Your Digital Strategy.pdfHow Blockchain Development Can Revolutionize Your Digital Strategy.pdf
How Blockchain Development Can Revolutionize Your Digital Strategy.pdf
 

More from BOHRInternationalJou1

Data mining approach to predict academic performance of students
Data mining approach to predict academic performance of studentsData mining approach to predict academic performance of students
Data mining approach to predict academic performance of students
BOHRInternationalJou1
 
Synthetic feature generation to improve accuracy in prediction of credit limits
Synthetic feature generation to improve accuracy in prediction of credit limitsSynthetic feature generation to improve accuracy in prediction of credit limits
Synthetic feature generation to improve accuracy in prediction of credit limits
BOHRInternationalJou1
 
Object detection and ship classification using YOLOv5
Object detection and ship classification using YOLOv5Object detection and ship classification using YOLOv5
Object detection and ship classification using YOLOv5
BOHRInternationalJou1
 
Dynamic Hough transform for robust lane detection and navigation in real time
Dynamic Hough transform for robust lane detection and navigation in real timeDynamic Hough transform for robust lane detection and navigation in real time
Dynamic Hough transform for robust lane detection and navigation in real time
BOHRInternationalJou1
 
Detection of abnormal human behavior using deep learning
Detection of abnormal human behavior using deep learningDetection of abnormal human behavior using deep learning
Detection of abnormal human behavior using deep learning
BOHRInternationalJou1
 
A study on disruptive technologies toward smart cities governance
A study on disruptive technologies toward smart cities governanceA study on disruptive technologies toward smart cities governance
A study on disruptive technologies toward smart cities governance
BOHRInternationalJou1
 
CNN-based plastic waste detection system
CNN-based plastic waste detection systemCNN-based plastic waste detection system
CNN-based plastic waste detection system
BOHRInternationalJou1
 
Fuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dust
Fuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dustFuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dust
Fuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dust
BOHRInternationalJou1
 
A case study: Grid services for satellite image processing
A case study: Grid services for satellite image processingA case study: Grid services for satellite image processing
A case study: Grid services for satellite image processing
BOHRInternationalJou1
 
Detecting paraphrases in the Marathi language
Detecting paraphrases in the Marathi languageDetecting paraphrases in the Marathi language
Detecting paraphrases in the Marathi language
BOHRInternationalJou1
 

More from BOHRInternationalJou1 (10)

Data mining approach to predict academic performance of students
Data mining approach to predict academic performance of studentsData mining approach to predict academic performance of students
Data mining approach to predict academic performance of students
 
Synthetic feature generation to improve accuracy in prediction of credit limits
Synthetic feature generation to improve accuracy in prediction of credit limitsSynthetic feature generation to improve accuracy in prediction of credit limits
Synthetic feature generation to improve accuracy in prediction of credit limits
 
Object detection and ship classification using YOLOv5
Object detection and ship classification using YOLOv5Object detection and ship classification using YOLOv5
Object detection and ship classification using YOLOv5
 
Dynamic Hough transform for robust lane detection and navigation in real time
Dynamic Hough transform for robust lane detection and navigation in real timeDynamic Hough transform for robust lane detection and navigation in real time
Dynamic Hough transform for robust lane detection and navigation in real time
 
Detection of abnormal human behavior using deep learning
Detection of abnormal human behavior using deep learningDetection of abnormal human behavior using deep learning
Detection of abnormal human behavior using deep learning
 
A study on disruptive technologies toward smart cities governance
A study on disruptive technologies toward smart cities governanceA study on disruptive technologies toward smart cities governance
A study on disruptive technologies toward smart cities governance
 
CNN-based plastic waste detection system
CNN-based plastic waste detection systemCNN-based plastic waste detection system
CNN-based plastic waste detection system
 
Fuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dust
Fuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dustFuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dust
Fuzzy clustering and energy resourceful routing protocol (FCER2P) for smart dust
 
A case study: Grid services for satellite image processing
A case study: Grid services for satellite image processingA case study: Grid services for satellite image processing
A case study: Grid services for satellite image processing
 
Detecting paraphrases in the Marathi language
Detecting paraphrases in the Marathi languageDetecting paraphrases in the Marathi language
Detecting paraphrases in the Marathi language
 

Recently uploaded

1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf
1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf
1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf
MadhavJungKarki
 
Transformers design and coooling methods
Transformers design and coooling methodsTransformers design and coooling methods
Transformers design and coooling methods
Roger Rozario
 
EV BMS WITH CHARGE MONITOR AND FIRE DETECTION.pptx
EV BMS WITH CHARGE MONITOR AND FIRE DETECTION.pptxEV BMS WITH CHARGE MONITOR AND FIRE DETECTION.pptx
EV BMS WITH CHARGE MONITOR AND FIRE DETECTION.pptx
nikshimanasa
 
Object Oriented Analysis and Design - OOAD
Object Oriented Analysis and Design - OOADObject Oriented Analysis and Design - OOAD
Object Oriented Analysis and Design - OOAD
PreethaV16
 
Call For Paper -3rd International Conference on Artificial Intelligence Advan...
Call For Paper -3rd International Conference on Artificial Intelligence Advan...Call For Paper -3rd International Conference on Artificial Intelligence Advan...
Call For Paper -3rd International Conference on Artificial Intelligence Advan...
ijseajournal
 
一比一原版(uofo毕业证书)美国俄勒冈大学毕业证如何办理
一比一原版(uofo毕业证书)美国俄勒冈大学毕业证如何办理一比一原版(uofo毕业证书)美国俄勒冈大学毕业证如何办理
一比一原版(uofo毕业证书)美国俄勒冈大学毕业证如何办理
upoux
 
AI in customer support Use cases solutions development and implementation.pdf
AI in customer support Use cases solutions development and implementation.pdfAI in customer support Use cases solutions development and implementation.pdf
AI in customer support Use cases solutions development and implementation.pdf
mahaffeycheryld
 
Determination of Equivalent Circuit parameters and performance characteristic...
Determination of Equivalent Circuit parameters and performance characteristic...Determination of Equivalent Circuit parameters and performance characteristic...
Determination of Equivalent Circuit parameters and performance characteristic...
pvpriya2
 
Null Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAMNull Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAM
Divyanshu
 
SENTIMENT ANALYSIS ON PPT AND Project template_.pptx
SENTIMENT ANALYSIS ON PPT AND Project template_.pptxSENTIMENT ANALYSIS ON PPT AND Project template_.pptx
SENTIMENT ANALYSIS ON PPT AND Project template_.pptx
b0754201
 
Open Channel Flow: fluid flow with a free surface
Open Channel Flow: fluid flow with a free surfaceOpen Channel Flow: fluid flow with a free surface
Open Channel Flow: fluid flow with a free surface
Indrajeet sahu
 
Asymmetrical Repulsion Magnet Motor Ratio 6-7.pdf
Asymmetrical Repulsion Magnet Motor Ratio 6-7.pdfAsymmetrical Repulsion Magnet Motor Ratio 6-7.pdf
Asymmetrical Repulsion Magnet Motor Ratio 6-7.pdf
felixwold
 
AN INTRODUCTION OF AI & SEARCHING TECHIQUES
AN INTRODUCTION OF AI & SEARCHING TECHIQUESAN INTRODUCTION OF AI & SEARCHING TECHIQUES
AN INTRODUCTION OF AI & SEARCHING TECHIQUES
drshikhapandey2022
 
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering on AAI Summer Training Report-003.pdfMechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering on AAI Summer Training Report-003.pdf
21UME003TUSHARDEB
 
Sri Guru Hargobind Ji - Bandi Chor Guru.pdf
Sri Guru Hargobind Ji - Bandi Chor Guru.pdfSri Guru Hargobind Ji - Bandi Chor Guru.pdf
Sri Guru Hargobind Ji - Bandi Chor Guru.pdf
Balvir Singh
 
This study Examines the Effectiveness of Talent Procurement through the Imple...
This study Examines the Effectiveness of Talent Procurement through the Imple...This study Examines the Effectiveness of Talent Procurement through the Imple...
This study Examines the Effectiveness of Talent Procurement through the Imple...
DharmaBanothu
 
Supermarket Management System Project Report.pdf
Supermarket Management System Project Report.pdfSupermarket Management System Project Report.pdf
Supermarket Management System Project Report.pdf
Kamal Acharya
 
Beckhoff Programmable Logic Control Overview Presentation
Beckhoff Programmable Logic Control Overview PresentationBeckhoff Programmable Logic Control Overview Presentation
Beckhoff Programmable Logic Control Overview Presentation
VanTuDuong1
 
Digital Image Processing Unit -2 Notes complete
Digital Image Processing Unit -2 Notes completeDigital Image Processing Unit -2 Notes complete
Digital Image Processing Unit -2 Notes complete
shubhamsaraswat8740
 
Applications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdfApplications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdf
Atif Razi
 

Recently uploaded (20)

1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf
1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf
1FIDIC-CONSTRUCTION-CONTRACT-2ND-ED-2017-RED-BOOK.pdf
 
Transformers design and coooling methods
Transformers design and coooling methodsTransformers design and coooling methods
Transformers design and coooling methods
 
EV BMS WITH CHARGE MONITOR AND FIRE DETECTION.pptx
EV BMS WITH CHARGE MONITOR AND FIRE DETECTION.pptxEV BMS WITH CHARGE MONITOR AND FIRE DETECTION.pptx
EV BMS WITH CHARGE MONITOR AND FIRE DETECTION.pptx
 
Object Oriented Analysis and Design - OOAD
Object Oriented Analysis and Design - OOADObject Oriented Analysis and Design - OOAD
Object Oriented Analysis and Design - OOAD
 
Call For Paper -3rd International Conference on Artificial Intelligence Advan...
Call For Paper -3rd International Conference on Artificial Intelligence Advan...Call For Paper -3rd International Conference on Artificial Intelligence Advan...
Call For Paper -3rd International Conference on Artificial Intelligence Advan...
 
一比一原版(uofo毕业证书)美国俄勒冈大学毕业证如何办理
一比一原版(uofo毕业证书)美国俄勒冈大学毕业证如何办理一比一原版(uofo毕业证书)美国俄勒冈大学毕业证如何办理
一比一原版(uofo毕业证书)美国俄勒冈大学毕业证如何办理
 
AI in customer support Use cases solutions development and implementation.pdf
AI in customer support Use cases solutions development and implementation.pdfAI in customer support Use cases solutions development and implementation.pdf
AI in customer support Use cases solutions development and implementation.pdf
 
Determination of Equivalent Circuit parameters and performance characteristic...
Determination of Equivalent Circuit parameters and performance characteristic...Determination of Equivalent Circuit parameters and performance characteristic...
Determination of Equivalent Circuit parameters and performance characteristic...
 
Null Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAMNull Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAM
 
SENTIMENT ANALYSIS ON PPT AND Project template_.pptx
SENTIMENT ANALYSIS ON PPT AND Project template_.pptxSENTIMENT ANALYSIS ON PPT AND Project template_.pptx
SENTIMENT ANALYSIS ON PPT AND Project template_.pptx
 
Open Channel Flow: fluid flow with a free surface
Open Channel Flow: fluid flow with a free surfaceOpen Channel Flow: fluid flow with a free surface
Open Channel Flow: fluid flow with a free surface
 
Asymmetrical Repulsion Magnet Motor Ratio 6-7.pdf
Asymmetrical Repulsion Magnet Motor Ratio 6-7.pdfAsymmetrical Repulsion Magnet Motor Ratio 6-7.pdf
Asymmetrical Repulsion Magnet Motor Ratio 6-7.pdf
 
AN INTRODUCTION OF AI & SEARCHING TECHIQUES
AN INTRODUCTION OF AI & SEARCHING TECHIQUESAN INTRODUCTION OF AI & SEARCHING TECHIQUES
AN INTRODUCTION OF AI & SEARCHING TECHIQUES
 
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering on AAI Summer Training Report-003.pdfMechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering on AAI Summer Training Report-003.pdf
 
Sri Guru Hargobind Ji - Bandi Chor Guru.pdf
Sri Guru Hargobind Ji - Bandi Chor Guru.pdfSri Guru Hargobind Ji - Bandi Chor Guru.pdf
Sri Guru Hargobind Ji - Bandi Chor Guru.pdf
 
This study Examines the Effectiveness of Talent Procurement through the Imple...
This study Examines the Effectiveness of Talent Procurement through the Imple...This study Examines the Effectiveness of Talent Procurement through the Imple...
This study Examines the Effectiveness of Talent Procurement through the Imple...
 
Supermarket Management System Project Report.pdf
Supermarket Management System Project Report.pdfSupermarket Management System Project Report.pdf
Supermarket Management System Project Report.pdf
 
Beckhoff Programmable Logic Control Overview Presentation
Beckhoff Programmable Logic Control Overview PresentationBeckhoff Programmable Logic Control Overview Presentation
Beckhoff Programmable Logic Control Overview Presentation
 
Digital Image Processing Unit -2 Notes complete
Digital Image Processing Unit -2 Notes completeDigital Image Processing Unit -2 Notes complete
Digital Image Processing Unit -2 Notes complete
 
Applications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdfApplications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdf
 

An improvement in the safety of big data using blockchain technology

  • 1. BOHR International Journal of Smart Computing and Information Technology 2023, Vol. 4, No. 1, pp. 50–54 DOI: 10.54646/bijscit.2023.36 www.bohrpub.com METHODS An improvement in the safety of big data using blockchain technology Archana1* and Gaurav Aggarwal2* 1Department of Computer Science, Govt. PG College for Women, Rohtak, India 2Department of Computer Science, Jagannath University, Jhajjar, India *Correspondence: Archana, archana300030@gmail.com Gaurav Aggarwal, gauravaggarw@gmail.com Received: 25 July 2023; Accepted: 12 August 2023; Published: 24 August 2023 The development of big data in the information technology sector has made data management and analysis far more challenging. It is necessary to take into account everything, including volume, variety, speed, value, and complexity. Clustering makes the processing of vast volumes of data simpler. This is especially helpful when working with unstructured data. By the usage of cloud computing, which makes use of the internet as its delivery channel, it is possible to provide a variety of computer services, including servers, storage, databases, and networking, in addition to analytics and intelligence, at a lower cost. The main problem is the security of such big amounts of data. One way to enforce strong security is blockchain technology which is also the backbone of cryptocurrency. The distributed, incontrovertible, and publicly verifiable record of every transaction activity that may be provided by blockchain technology has the potential to revolutionize security in a big way for different industries. Keywords: big data, security, block chain, clustering, inconsistency Introduction Big data is a reference to the ever-increasing amount of data that cannot be processed by traditional database techniques. Due to its huge size, unstructured as well as structured data, and complexity, standard data management technologies are unable to effectively store or process the information. Some examples of big data include the following: New York Stock Exchange, which generates around one terabyte worth of fresh trading data every single day. The estimates provided by Facebook indicate that more than 500 gigabytes of fresh data are being uploaded to the site’s databases on a daily basis. The key ways in which these data are collected include users uploading photographs and videos, engaging in discussions with one another, posting comments, and so on. Characteristics of big data Big data can be described by the following characteristics: a) Volume: The phrase “big data” refers to an extremely large quantity of data. When you have access to a vast amount of information, it is essential to make the most of its potential applications. The quantity of information that is required to categorize anything is one major aspect that determines whether or not it is considered “big data.” The volume of data is particularly high in banking and other financial institutions, social media, and entertainment industries. b) Variety: The second facet of big data that has to be taken into consideration is its level of diversity. The concepts of structured and unstructured data are both included under the umbrella word “variety.” In 50
  • 2. 10.54646/bijscit.2023.36 51 the past, the majority of applications did little more than save data in spreadsheets and databases and then retrieve it when necessary. At the moment, analytical applications make use of a broad variety of data sources with structured, semi-structured, as well as unstructured data; some examples of which include emails, photographs, videos, documents in PDF format, monitoring devices, and audio recordings. Data storage, data mining, and data analysis are all made more challenging by the presence of unstructured data. c) Velocity: In the context of big data, the word “velocity” refers to the pace at which new data are generated. The speed at which new data are generated and processed will influence how much of the data’s potential can be realized. What is known as “Big Data Velocity” is a concept that was developed as a result of the contributions made by business processes, log files, networks, social media, sensors, and mobile devices. There is a rapid flow of information that involves a significant volume of data. The velocity of data is particularly high for the banking, healthcare, and manufacturing sectors. d) Inconsistency: It may be difficult to efficiently manage and analyze the data due to the variability that may arise in the data. This makes it a potential challenge. Advantages of big data processing There are several reasons why big data processing is beneficial: 1. Businesses have the option of incorporating outside information into decision-making. Due to the availability of social data gleaned from search engines and sites such as Facebook and Twitter, organizations are able to fine-tune their business plans according to user sentiment and changes in choices. 2. Improved customer service: Conventional means of gathering input from customers are being phased out in favor of big data technology. With these new platforms, the responses received from customers are studied and assessed with the use of big data and natural language processing technologies. 3. An early evaluation of any possible risks that may be associated with the product or service will lead to preventive actions for the risks. 4. The big data environment allows for the pre- processing of larger data sets before they are transferred to the warehouse, which improves the operational efficiency of the business. The combination of big data and data warehouses also assists businesses in offloading data that are needed less often. Cluster In a computer cluster, two or more individual computers, also known as nodes, collaborate with one another to carry out a specific task. Because of this, it is feasible to distribute huge tasks that can be done in parallel throughout the nodes that make up the cluster. Performance is boosted as a result of the fact that the combined memory and processing capabilities of each machine may benefit a variety of operations. Since each individual node in a computer cluster has to be able to interact with the other nodes in the cluster, the building of a computer cluster requires the use of an internodes network. In order to construct a cluster, the nodes must first be connected via the use of cluster software. A storage device that is shared across the nodes and/or a storage device that is local to each node are both potential solutions. It is common practice to designate at least one of the nodes as a leader node, which then operates as the entry point for the cluster. This node could be in charge of delegating responsibilities to the subordinates and, if that is required, gathering the results before relaying them to an external party. Also, the communication between nodes in a cluster has to be optimized so that latency may be reduced and bottlenecks can be avoided. Blockchain technology Blockchain technology is the term that describes the technical basis upon which Bitcoin currency is built. Because of this technology, it is possible to carry out any transaction in a way that is not governed by any central authority. The participation of a middleman or broker is not required in order for it to take place. As it creates records of transactions that are decentralized, unchangeable, and publicly verifiable, Blockchain technology has the potential to revolutionize a wide variety of industries. Blockchains store the data differently from standard databases, which store the data in rows and columns that are hash-linked together, while blockchains store the data in blocks that are cryptographically connected together. Each new piece of information that is received results in the creation of a new block in the database. After a block has been filled with information, the data included inside it are connected to one another in the order that chronological events occurred. While a blockchain may be used to store a wide range of data types, the use that has proven to be the most successful to this point is that of a ledger for the recording of financial transactions. There is not a single person or group in control of Bitcoin’s use of the blockchain; rather, all users collectively hold the reins. Blockchain is used to record transactions related to Bitcoin transactions. With the use of blockchains, digital information may be saved and distributed, but it cannot be changed once it has been recorded. Because of this,
  • 3. 52 Archana and Aggarwal a blockchain may be used as the foundation for immutable ledgers, which are essentially recordings of transactions that are incorruptible in any way. Blockchains are often referred to as “distributed ledger technology” as a direct consequence of this fact. Features of blockchain technology The key points depicting features of blockchain technology are cited ahead: a) Immutability is the state of being incapable of undergoing any kind of change or transformation. This is an essential component of blockchain that assures the long-term survival of the technology as it is a network that cannot be altered and is permanent. b) Decentralized: As the network is decentralized, there is not a single person who is in charge of supervising the infrastructure. This means that security and privacy are not compromised. Decentralization of the network is ensured through the use of a dispersed collection of nodes that are responsible for its management. It is able to store anything of value, including Bitcoins, important documents, contracts, and other valuable digital assets. After then, with the assistance of the blockchain, you will be able to have direct control over them by making use of your private key. As a consequence of this, the general public regains both control and ownership of the assets as a result of the decentralized structure. c) Improved security: In the blockchain, every piece of data is encrypted and hashed using a new method each time. This provides an additional layer of protection against unauthorized access. To put it another way, the information provided by the network hides the fundamental characteristics of the data. Mathematical techniques may be used to any data as an input to generate various values, but the length of the output always stays the same. A one-of-a-kind identification is assigned to each individual piece of data. In the ledger, each new block is given its own one-of-a-kind hash and also includes the hash of the block that came before it. A fresh set of hash IDs will be generated in the event that the data are altered in any way. And even that is a bit of a stretch, to say the least. The user is going to need both a private key and a public key in order to get access to the data. d) Hashing cannot be undone in any case. Hashing is a very complicated process, and it is not feasible to modify or undo it in any way. Nobody will ever be able to take a public key and turn it into a private key. e) Distributed ledger: With a public ledger, this information is often accessible to anybody who is a member of the general public. There is nowhere to run since everything is out in the open. There is, however, an exception to this general rule for blockchains that are either private or federated. In spite of this, a significant number of users are able to see the ledger at any one time under these circumstances. As a consequence of this, the ledger that represents the network is continually updated by everyone else who is using the system. This distributed the processing power among the several machines in order to get a more favorable outcome. f) Consensus: The techniques used to reach consensus are essential to the operation of any blockchain. The intelligent design of this architecture is based on consensus algorithms, which serve as its foundation. Every blockchain has to have a consensus in order to function properly. The network’s ability to reach a consensus is directly responsible for the credibility of the network. The nodes that make up a network may not have much confidence in one another, but they could have faith in the algorithms that drive it. As a consequence of this, the blockchain is improved by every decision that is taken on the network. Using the blockchain provides this as one of its many benefits. g) Quicker settlement: The processing of transactions via traditional banking systems may often take a very lengthy period. But, with the assistance of blockchains and other contemporary systems, monetary transactions may be completed in a shorter amount of time, saving the user important time. Role of blockchain in big data The fact that everything that takes place on a blockchain is encrypted makes it capable of providing the greatest possible degree of security. In a similar fashion, the data that are saved on the blockchain cannot be changed. To be on the safe side, the file signatures of all of the nodes in the network may be checked across all of the ledgers in the network to make sure that they have not been altered. If the record is modified in any way, the signature will no longer be valid. The applications of big data and blockchain are mutually beneficial. Big data technologies can handle any data, regardless of its variety, velocity, or volume. Blockchain applications simplify operations in any industry. The traditional information processing architecture and business transaction processing have been rendered obsolete as big data and blockchain technologies have grown over the last several years. This has made it possible to abandon these processes. It is necessary for big data to have processing power that is capable of handling big data’s processing capacity; conversely, big data requires processing power that is capable of handling the complexity of blockchain and its fast growth.
  • 4. 10.54646/bijscit.2023.36 53 FIGURE 1 | Research methodology. This sheds light on several implementations of blockchain technology in big data among various industries: 1. Accelerating the financial services sector, the combination of blockchain technology and large amounts of data held by financial institutions will make it possible to estimate risk and spot suspicious trends in real time. Making use of blockchain technology as a way of conducting transactions would assist to safeguard banks and their clients from fraud, speed up the process of transactions, and minimize the cost of transferring money between accounts. For instance, in the most recent few years, in order to streamline the process of moving money from one bank account to another using technology known as blockchain, an association consisting of 47 Japanese banks joined a blockchain business known as Ripple. The goal here is to carry out real-time transfers while minimizing associated costs. The cost of conventional real-time transactions is high because of the possibility of risk factors such as double spending, which may be avoided with blockchain technology. 2. Security in businesses other than banking: Businesses in healthcare, public administration, and other areas have begun adopting blockchain technology to manage data and thwart hacking attempts and avoid data breaches. 3. Monitoring of the supply chain: A blockchain is employed to maintain tabs on the commodities that make up the supply chain, and a mobile app is utilized to monitor the locations of these commodities as they move. Walmart is a wonderful example of this as it uses the technology of blockchains to enhance food safety by allowing for more accurate monitoring of items from the farm to the shop shelf. Users have the ability to get credible information on the provenance of their food while using this strategy (Figure 1). Conclusion The proposed research is supposed to be capable to resolve the security issue in big data using blockchain. This research would provide a solution to confirm the impact of blockchain on big data security. The goal of the proposed work is to make use of big data with blockchain applicable in real- life scenario. The proposed work offers a broad range of options and flexibility. Improved precision and efficiency are expected as a result of this investigation. The proposed work provides a wide range of possibilities and adaptability. References 1. Mechkaroska D, Popovska-mitrovikj A, Dimitrova V. Secure big data and IoT with implementation of blockchain technology. Int Sci J Secur Fut. (2018) 185:183–5. 2. Tariq N, Asim M, Al-Obeidat F, Zubair Farooqi M, Baker T, Hammoudeh M, et al. The security of big data in fog-enabled IoT applications including blockchain: a survey. Sensors (2019) 19:1788. doi: 10.3390/s19081788 3. Ferrag MA, Maglaras L, Janicke H. Blockchain and its role in the internet of things. In: Kavoura A, Kefallonitis E, Giovanis A editors. Strategic innovative marketing and tourism. Berlin: Springer (2019). p. 1029–38. doi: 10.1007/978-3-030-12453-3_119
  • 5. 54 Archana and Aggarwal 4. Dujak D, Sajter D. Blockchain applications in supply. Berlin: Springer International Publishing (2019). doi: 10.1007/978-3-319-91668-2_2 5. Valdeolmillos D, Mezquita Y, González-Briones A, Prieto J, Corchado JM. Blockchain technology: a review of the current challenges of cryptocurrency. Proceedings of the blockchain and applications international congress. Berlin: Springer (2020). p. 153–60. doi: 10.1007/ 978-3-030-23813-1_19 6. Bertino E, Ferrari E. Big data security and privacy. In: Flesca S, Greco S, Masciari E, Saccà D editors. A comprehensive guide through the Italian database research over the last 25 years. Cham: Springer (2018). p. 425–39. doi: 10.1007/978-3-319-61893-7_25 7. Babar M, Arif F. Real-time data processing scheme using big data analytics in internet of things based smart transportation environment. J Ambient Intell Human Comput. (2018) 10:4167–77. doi: 10.1007/ s12652-018-0820-5 8. Dasgupta D, Shrein JM, Datta K. A survey of blockchain from security perspective. J Bank Financ Technol. (2018) 3:1–17. doi: 10.1007/s42786- 018-00002-6 9. Kumar A, Abhishek K, Nerurkar P, Khosravi MR, Rukunuddin M, Shankar A. Big data analytics to identify illegal activities on bitcoin blockchain for IoMT. Pers Ubiquit Comput. (2021) 1–12. doi: 10.1007/ s00779-021-01562-z 10. Meng Y, Nazir S. A decision support system for the uses of lightweight blockchain designs for P2P computing. Peer Peer Netw Appl. (2021) 14:2708–18. doi: 10.1007/s12083-021-01083-9 11. Niranjanamurthy M, Nithya BN, Jagannatha S. Analysis of blockchain technology: pros, cons and SWOT. Cluster Comput. (2018) 22. doi: 10.1007/s10586-018-2387-5 12. Singh SP, Nayyar A, Kumar R, Sharma A. Fog computing: from architecture to edge computing and big data processing. J Supercomput. (2019) 75:2070–105. doi: 10.1007/s11227-018-2701-2 13. Zhang P, Lu Q, Hu X, Gu S, Yang L, Min M, et al. Latest progress of the Chinese meteorological satellite program and core data processing technologies. Adv Atmos Sci. (2019) 36:1027–45. doi: 10.1007/s00376- 019-8215-x 14. Azmoodeh A, Dehghantanha A, Choo KR. Big data and internet of things security and forensics: challenges and opportunities. In: Dehghantanha A, Choo KK editors. Handbook of big data and IoT security. Cham: Springer (2019). p. 10–3. doi: 10.1007/978-3-030- 10543-3 15. Ahmadvand H, Goudarzi M, Foroutan F. Gapprox: using Gallup approach for approximation in big data processing. J. Big Data (2019) 6:20. doi: 10.1186/s40537-019-0185-4 16. Silva BN, Diyan M, Han K. Big data analytics. Berlin: Springer (2019). doi: 10.1007/978-981-13-3459-7_2 17. Rathee G, Sharma A. A hybrid framework for multimedia data processing in IoT-healthcare using blockchain technology. Multimed Tools Appl. (2019) 79:9711–33. doi: 10.1007/s11042-019-07835-3 18. Calvaresi D, Leis M, Dubovitskaya A, Schegg R, Schumacher M. Trust in tourism via blockchain technology: results from a systematic review. Berlin: Springer International Publishing (2019). 19. Czachorowski K, Solesvik M, Kondratenko Y. The application of blockchain technology in the maritime industry. Berlin: Springer International Publishing (2019). doi: 10.1007/978-3-030-00253-4_24 20. Khan MM, Ikram M. Use of blockchain in education: a systematic literature review. In: Nguyen NT, Gaol FL, Hong T-P, Trawński B editors. Intelligent information and database systems. Cham: Springer (2019). p. 191–202. doi: 10.1007/978-3-030-14802-7_17 21. Xu M, Chen X, Kou G. A systematic review of blockchain. Financ Innov. (2019) 5:27. doi: 10.1186/s40854-019-0147-z 22. Firdaus A, Faizal M, Razak A, Feizollah A. The rise of “blockchain”: bibliometric analysis of blockchain study. Scientometrics (2019) 120:1289–331. doi: 10.1007/s11192-019-03170-4 23. Chen J, Lv Z, Song H. Design of personnel big data management system based on blockchain. Fut .Gener Comput Syst. (2019) 101:1122–9. doi: 10.1016/j.future.2019.07.037 24. Nandan S, Ramya KC, Sheeba Rani S, Gupta D, Shankar K, Lakshmanaprabu SK, et al. An efficient lightweight integrated blockchain (ELIB) model for IoT security and privacy. Fut Gener Comput Syst. (2020) 102:1027–37. doi: 10.1016/j.future.2019.09.050 25. Deepa N, Pham VQ, Nguyen DC, Bhattacharya S, Prabadevi B, Gadekallu TR, et al. A survey on blockchain for big data: approaches, opportunities, and future directions. Fut Gener Comput Syst. (2022) 131. doi: 10.1016/j.future.2022.01.017