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Blockchain transaction analysis is a powerful tool to gain insights into the actions and conduct of participants within blockchain networks. This article aims to extensively examine the applications, tasks, and methods associated with blockchain transaction analysis. We look at various uses of trans...
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The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2023
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System research and information technologies| _version_ | 1867334434769862656 |
|---|---|
| author | Dorogyy, Yaroslaw Kolisnichenko, Vadym |
| author_facet | Dorogyy, Yaroslaw Kolisnichenko, Vadym |
| author_institution_txt_mv | [
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"author": "Yaroslaw Dorogyy",
"institution": "National Technical University of Ukraine \"Igor Sikorsky Kyiv Polytechnic Institute\", Kyiv"
},
{
"author": "Vadym Kolisnichenko",
"institution": "National Technical University of Ukraine \"Igor Sikorsky Kyiv Polytechnic Institute\", Kyiv"
}
] |
| author_sort | Dorogyy, Yaroslaw |
| baseUrl_str | http://journal.iasa.kpi.ua/oai |
| collection | OJS |
| datestamp_date | 2024-02-01T21:03:07Z |
| description | Blockchain transaction analysis is a powerful tool to gain insights into the actions and conduct of participants within blockchain networks. This article aims to extensively examine the applications, tasks, and methods associated with blockchain transaction analysis. We look at various uses of transaction analysis, ranging from its instrumental role in blockchain development to its pivotal significance in the field of criminal investigations. By leveraging common techniques and technologies employed in conducting such an analysis, we unlock hidden insights and uncover information that is not visible at first look. This article offers a wide-ranging perspective on the profound significance of blockchain transaction analysis while shedding light on its key role within the cryptocurrency industry and its wide-ranging applications beyond. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2023.4.03 |
| first_indexed | 2025-07-17T10:28:10Z |
| format | Article |
| fulltext |
Ya. Dorogyy, V. Kolisnichenko, 2023
Системні дослідження та інформаційні технології, 2023, № 4 37
UDC 004.4 + 004.9
DOI: 10.20535/SRIT.2308-8893.2023.4.03
BLOCKCHAIN TRANSACTION ANALYSIS:
A COMPREHENSIVE REVIEW OF APPLICATIONS,
TASKS AND METHODS
Ya. DOROGYY, V. KOLISNICHENKO
Abstract. Blockchain transaction analysis is a powerful tool to gain insights into the
actions and conduct of participants within blockchain networks. This article aims to
extensively examine the applications, tasks, and methods associated with blockchain
transaction analysis. We look at various uses of transaction analysis, ranging from
its instrumental role in blockchain development to its pivotal significance in the field
of criminal investigations. By leveraging common techniques and technologies em-
ployed in conducting such an analysis, we unlock hidden insights and uncover in-
formation that is not visible at first look. This article offers a wide-ranging perspec-
tive on the profound significance of blockchain transaction analysis while shedding
light on its key role within the cryptocurrency industry and its wide-ranging applica-
tions beyond.
Keywords: blockchain transactions, transaction analysis, transaction tracing, flow
analysis, blockchain forensics.
INTRODUCTION
Blockchain technology has revolutionized the way financial transactions are con-
ducted and recorded, creating a public decentralized network that eliminates the
need for intermediaries and enables secure and transparent transactions. With the
growing popularity of cryptocurrencies and blockchain-based systems, the need
for effective blockchain transaction analysis has become increasingly important.
Blockchain transaction analysis refers to the process of examining and interpret-
ing blockchain data to gain insights into the flow of transactions, identify patterns,
and detect anomalies.
This paper provides a review of the applications of analysis in various do-
mains, the methods and techniques used to analyze blockchain data. The paper is
organized as follows. First, we provide an overview of blockchain technology and
its key concepts including the types of data available on the blockchain. Then, we
delve into the applications of blockchain transaction analysis, including crypto-
currency investigations. We provide real-world examples of how blockchain
transaction analysis has been used in different domains and discuss the benefits
and limitations of the approaches.
Next, we discuss blockchain transaction analysis, the challenges of analyzing
blockchain data, and the methods and techniques used to perform blockchain
transaction analysis.
Finally, we conclude the paper with a discussion of the future of blockchain
transaction analysis, including the challenges and opportunities that lie ahead. We
argue that blockchain transaction analysis has the potential to transform many
industries by providing greater transparency, security, and efficiency. However,
Ya. Dorogyy, V. Kolisnichenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 4 38
the field is still in its early stages, and much research is needed to develop more
effective methods and tools for analyzing blockchain data.
Overall, this paper aims to provide a comprehensive overview of blockchain
transaction analysis, covering both the methods and applications of the field. By
doing so, we hope to contribute to the growing field of research on blockchain
technology and its potential impact on various industries.
BLOCKCHAIN TRANSACTIONS
Blockchain transaction, in simple terms, can be defined as a record of the transfer
of digital assets or the storage of information on a blockchain network that is
permanently recorded on a distributed ledger.
One of the most notable features of blockchains is that everything stored is
visible to everyone, meaning anyone can see who makes transactions to whom.
While it may sound easy at first, it appears much more complex.
Mechanisms of asymmetric cryptography are used to define the sender or re-
ceiver of a transaction – addresses are formed from public keys, and private keys
are used to sign transactions (to prove that the actual owner of the funds created
the transaction).
Another concept blockchain networks are using is hierarchical deterministic
(HD) wallets. In HD wallets a master seed is used to generate an unlimited num-
ber of public-private key pairs, allowing for the creation of multiple addresses and
sub-wallets that can be easily managed from a single mnemonic phrase or seed.
This enables users to receive and send funds with new addresses each time, there-
fore increasing the privacy of the end-user.
In terms of record-keeping, there are two common models: unspent transac-
tion output (UTXO) model and account model. In the UTXO model (Fig. 1), each
transaction creates a list of outputs that will be spent in future transactions (used
as inputs). The outputs are assigned to the addresses that should be able to use
(spend) them. The total balance of the address is the sum of all unspent outputs to
this address at the current moment.
The account model, on the other hand, is much simpler to understand.
A blockchain maintains balance for each account and keeps a record of all
transactions that have affected that balance.
Fig. 1. Simplified UTXO model
Blockchain transaction analysis: a comprehensive review of applications, tasks and methods
Системні дослідження та інформаційні технології, 2023, № 4 39
In order to have the ability of multi-user ownership of funds, or more gener-
ally, to set up conditions and rules for spending funds (rules of ownership), block-
chain networks were built with additional complexity. In fact, Bitcoin transactions
do not have sender or receiver fields. Instead, Bitcoin uses lock (scriptPubKey)
and unlock (scriptSig) scripts to create a concept of a puzzle, solvable by meeting
specified conditions (e.g., to spend a transaction the one should specify a signa-
ture in the unlock script, whose public key is set in the lock script).
Bitcoin scripts are extremely limited and do not allow creating complex
logic. To face this, Ethereum network uses a concept of smart contract [1], which
enables creating complex programs using JavaScript-like language called Solidity,
storing them on the blockchain and executing thorough Ethereum Virtual Machine.
Scripting and programming features give extensive possibilities to build ap-
plications with various levels of complexity providing end-users with secure de-
centralized financial (DeFi) services and developers with tools for further optimi-
zation (e.g., layer 2 networks) and development [2].
If we talk about what information is stored in the blockchain, then it is usu-
ally logical information. By logical information here we mean information related
to blocks, transactions, accounts, etc. In other words, data to support the business
logic of a blockchain.
There is much information that is not part of blockchain and, usually, it is
more technical and does not influence the business logic directly. Let us consider
a simplified process of including transactions into the blockchain (which is simi-
lar among different networks). A user creates a transaction and signs it, providing
proof of address ownership and transaction integrity. After a transaction is signed,
the user broadcasts it by using one’s own node or through the JSON-RPC inter-
face of a chosen public node. Traveling through a bunch of nodes, the transaction
finally reaches miners who include it to the block and mine it. After the block is
mined, it gets broadcast to the rest of the nodes. When the rest of the nodes accept
it, it is considered as a part of the blockchain. No networking information (IP of
the sender and nodes that broadcasted the transaction, etc.) in this process is in-
cluded into the blockchain, however, intermediate hosts may store it in their own
databases.
Taking into consideration all the mentioned specifics, it is not easy to ana-
lyze transactions and data stored in the blockchain – who owns the funds, how
much, who was the actual sender, what logic the transaction performs, etc. In the
next chapter we will go into why such analysis is important and where it is applied.
APPLICATION OF ANALYSIS
Blockchain transaction analysis is a powerful tool that allows us to better under-
stand the behavior of users and events on blockchain networks. As blockchain and
decentralized finance (DeFi) technologies continue to grow, there are an increas-
ing number of use cases for transaction analysis. This chapter will explore the key
applications of blockchain transaction analysis, including cryptocurrency investi-
gations, risk management, tax compliance, and many others. By leveraging the
insights gained through transaction analysis, stakeholders can seize the big picture
and make informed decisions.
While some categories may overlap, we think the following distinguishment
reflects the unique specifics in the best way.
Ya. Dorogyy, V. Kolisnichenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 4 40
Crime Investigation
Cryptocurrencies possess unique properties such as decentralization, independ-
ence from banks, security, ubiquity, and anonymity. As is the case with other
types of assets, these distinct characteristics determine the specific applications of
cryptocurrencies. However, these same properties have also made cryptocurren-
cies an appealing tool for illicit activities such as money laundering, fraud, scam,
and sanctions evasion, among others [3; 4].
The Africrypt incident is one of the biggest that has happened with the in-
volvement of cryptocurrencies. Two founders of Africrypt alleged that their firm
was hacked resulting in the theft of all its assets. After the statement, the founders
vanished. Approximately $3.6 billion in Bitcoin has disappeared in total [5]. As of
now, not much added information has been found regarding this case. Law en-
forcement authorities are reportedly continuing their search for the founders [6].
This incident, among many others [7; 8], is similar to traditional finance scams,
where founders (whose names are often known) collect money and disappear.
While blockchain technologies provide a certain level of privacy it cannot be
considered as fully anonymous [9], and in many cases a careful analysis may an-
swer the question “where the money goes” [10]. Let us examine some prominent
cases where transaction analysis was helpful for the investigation.
Cryptocurrencies are often used as a means of payment in cyber extortion
and ransomware attacks. Hackers who carry out these attacks demand payment in
cryptocurrency in exchange for returning control of the victim’s computer system
or stolen data. One of such cases is NetWalker malware, which is built as Ran-
somware as a Service (RaaS) model [11], where affiliates rent malware from op-
erators to launch attacks. One of the affiliates was arrested, and a blockchain
transaction analysis solution was used to help to track down addresses associated
with the affiliate [12].
Hacking of the DeFi projects is quite widespread [13; 14]. Compared to
other domains, in the blockchain domain a hacker directly operates the valuable
assets such as coins or tokens. It is worth mentioning that the biggest amounts of
assets are concentrated in cross-chain bridges and centralized crypto exchanges
(CEX) which make them attractive targets [15]. Transaction analysis is usually
applied to get an understanding of the attack and to track the ones who were in-
volved.
An attack analysis is an essential measure to be taken after the incident has
occurred. This process involves identifying how the system was compromised,
assessing the extent of the damage caused, determining strategies for minimizing
the damage, and addressing any vulnerabilities that were exploited. To identify
how the blockchain system was hacked, attackers’ transactions together with in-
volved smart contracts are analyzed. Such analysis is often performed by the own-
ing company, investigating company or blockchain community [16; 17] with
various levels of details.
Hackers who steal funds from blockchains often seek to launder the stolen
cryptocurrencies to conceal their identities and make it difficult for law enforce-
ment agencies to trace the illicit funds [18]. They can do this by using mixers,
tumblers, or other obfuscation techniques to obscure the trail of transactions and
make it hard to trace the stolen funds. Additionally, hackers can use decentralized
exchanges to convert stolen cryptocurrencies to other assets, such as privacy coins
Blockchain transaction analysis: a comprehensive review of applications, tasks and methods
Системні дослідження та інформаційні технології, 2023, № 4 41
or stablecoins, to further obfuscate the trail of transactions. These assets can then
be moved through multiple wallets to further distance the funds from the original
theft. The final step may involve converting the stolen cryptocurrencies to fiat
currency through a regulated exchange or other means to cash out the illicit funds.
One of the successful investigations of laundering is the Bitfinex case. Ac-
cording to Elliptic [19], after the hack stolen funds were slowly being laundered
using different techniques. AlphaBay is one of the services that was used as a
mixer to hide the trails. However, later it was seized by law enforcement, and this
likely allowed them to get trails to the hackers.
Another, less successful investigation case, is a hack of Zaif exchange in
September 2018. Crystal Blockchain Analytics engineering team performed an
analysis of bitcoin movements [20] and could find addresses involved in the hack.
Although the owners of the addresses are unknown, the addresses are being moni-
tored in case of further transactions.
One notable type of blockchain assets that got much attention is Non-
Fungible Token (NFT). NFTs are assets that represent ownership of unique items
such as music, videos, art or other on a blockchain network. They are not divid-
able and interchangeable with one another. Each NFT is unique and cannot be
replicated. Although it can be implicated in criminal activities similar to other
digital assets, one distinctive aspect worth mentioning is copyright infringement.
Blockchain technology can guarantee the uniqueness of the token but cannot
guarantee the uniqueness of the represented asset, which can be copied. Transac-
tion analysis can be used to assist with NFT copyrighting. By analyzing the NFT
transactions it may be possible to verify its authenticity and identify the original
creator or owner of the work. This information could also be used as evidence to
support copyright claims. One notable project that tries to detect copyright in-
fringement by scanning blockchains and marketplaces is DeviantArt [21]. They
use different techniques including machine learning to spot the copy.
We can observe that blockchain transaction analysis is used as a valuable
tool in crime investigations, enabling law enforcement agencies to track the flow
of funds in the blockchain network and identify any suspicious activity associated
with illegal activities such as money laundering, dark web transactions, cyber-
crime, and fraud. Transaction analysis also helps trace the flow of funds associ-
ated with cyberattacks, ransomware payments, and other malicious activities. It
provides insights into transaction behavior and patterns that can be used to iden-
tify potential criminal activity and take appropriate action.
Compliance and Regulation
Cryptocurrency regulations are laws or rules established by governments or regu-
latory bodies to govern the use, trading, and custody of cryptocurrencies. These
regulations aim to protect investors, prevent illicit activities such as money laun-
dering and terrorist financing, and promote the stability and integrity of the finan-
cial system. Cryptocurrency regulations can cover a wide range of topics, depend-
ing on the jurisdiction and the specific concerns of regulators [22]. While these
regulations are mostly related to cryptocurrencies rather than technology itself,
some countries may try to enforce regulations on the tech side too (e.g., on min-
ing) [23].
Transaction analysis is a useful tool for enforcing cryptocurrency regulations
and ensuring compliance with regulatory requirements [24; 25]. Regulators can
Ya. Dorogyy, V. Kolisnichenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 4 42
use transaction analysis to monitor and detect potential money laundering activi-
ties, enforce KYC (know your customer) and tax compliance, prevent fraud, and
protect consumers in the cryptocurrency market [26].
By analyzing transaction patterns and identifying any unusual or suspicious
activity, regulators can take appropriate action to prevent money laundering and
other financial crimes. They can also use transaction analysis to monitor compli-
ance with know-your-customer requirements and tax laws and regulations. Addi-
tionally, transaction analysis can help prevent cryptocurrency fraud by identifying
any fraudulent activity and taking appropriate action.
While in the previous section transaction analysis is applied after an event
happened (for the investigation), in case of regulations, transaction analysis is
mostly used continuously (for the detection and prevention).
Trade and investment
In traditional finance, financial transactions are mostly opaque, and investors of-
ten rely on intermediaries [27] to provide information about the assets they are
investing in. Investors and traders use methods such as technical analysis to ana-
lyze financial markets and securities based on statistical trends and patterns in
historical price and volume data. Trading in blockchain offers new opportunities
and challenges with its unique characteristics of transparency, security, and de-
centralization [28].
Having access to transaction data changes the rules of the game. However,
without a proper processing of massive amounts of raw data transparency does
not give you advantages. Therefore, it is important to produce new methods and
tools that can provide insights into the behavior of market participants and the
underlying fundamentals of digital assets. Moreover, these methods and tools
should be the same or better than in your potential opponents, as they also have
access to the same raw data.
Here transaction analysis can be helpful in several ways. It can provide vol-
ume and velocity of transactions for a particular cryptocurrency [29]. Blockchain
transaction analysis can give information on the distribution of digital assets
among market participants and provide valuable insights into their behavior. This
information can help traders and investors identify potential price levels for a par-
ticular cryptocurrency based on the level of demand from buyers and sellers. By
analyzing this information traders and investors can gain insights into partici-
pants’ trading strategies and use this information to adjust their own trading deci-
sions.
Besides that, it can be used for analyzing the flow of assets within a block-
chain to identify large transactions and movements of funds that may be indica-
tive of market manipulation or other illicit activities. Transaction flow analysis
can help traders avoid entering into positions that may be vulnerable to sudden
price movements.
Risk Management
Organizations that try to adopt blockchain and DeFi technologies for their busi-
nesses should be aware of numerous additional risks [30–32].
Cryptocurrencies are still growing and one of the primary risks is unclear
regulations, specifically, legal, and regulatory compliance. Blockchain-based
Blockchain transaction analysis: a comprehensive review of applications, tasks and methods
Системні дослідження та інформаційні технології, 2023, № 4 43
businesses may face challenges in complying with current regulations or in pre-
dicting future regulations, which can result in legal and financial penalties or re-
putational damage. The risk of unclear regulations in blockchain risk management
is significant because blockchain technology operates in a regulatory gray area in
many countries.
Another set of risks comes from the technical side. Bugs, vulnerabilities,
network scalability difficulties can lead to various negative outcomes such as loss
or theft of funds [33], network downtime [34], reputational damage and others.
Volatility and liquidity are another two significant risks associated with
blockchain and cryptocurrencies [35]. These risks can affect both investors and
businesses that use cryptocurrencies for transactions or other purposes. Volatility
can lead to significant losses for investors who have invested in cryptocurrencies,
as the value of their investments can decrease rapidly. Additionally, businesses
that use cryptocurrencies for transactions can be negatively affected by volatility
as the value of their transactions can also fluctuate rapidly. Cryptocurrency mar-
kets can be relatively illiquid, particularly for less popular cryptocurrencies or
during periods of market instability. This illiquidity can make it difficult for in-
vestors to sell their cryptocurrencies when they need to, leading to losses. Addi-
tionally, illiquidity can create challenges for businesses that use cryptocurrencies
for transactions, as it can be difficult to find a buyer or seller for the desired
cryptocurrency at a fair market price.
Transaction analysis is a useful tool for risk management in blockchain. It
can provide businesses with insights into transaction behavior and patterns, which
can be used to identify potential risks and vulnerabilities. Transaction analysis can
be used to detect fraudulent activity, such as money laundering or other financial
crimes, by analyzing transaction patterns and identifying any unusual or suspi-
cious activity. It can also help businesses monitor compliance with regulations
and industry standards by detecting any potential compliance issues. Businesses
can determine the level of risk associated with a particular transaction or customer
and take appropriate action to manage that risk. Moreover, transaction analysis
can help investors and businesses assess the liquidity of cryptocurrencies by ana-
lyzing transaction volumes.
Supply Chain Management
Supply chain management in blockchain refers to the use of blockchain technol-
ogy to track and manage the movement of goods and services through a supply
chain. Blockchain technologies provide a transparent and secure platform for
tracking and verifying transactions in real-time [36]. Each asset is represented
through a unique token. When a party performs transfer of the asset, it also cre-
ates and signs a transaction to transfer the token (that represents actual asset) on
that blockchain. Transactions are then recorded on the blockchain, and the entire
process is transparent for the shareholders. This can help businesses to optimize
their supply chain operations, reduce costs, and ensure compliance with relevant
regulations and industry standards.
In the supply chain process, blockchain transaction analysis is a core tool,
which allows stakeholders to follow the entire process. It allows extracting and
analyzing transaction patterns, businesses can gain valuable insights into the
movement of goods and services through the supply chain [37–39].
Ya. Dorogyy, V. Kolisnichenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 4 44
Blockchain Development
Analysis of transactions is also important for blockchain development and its op-
timization. At different stages of development transactions are analyzed to debug
errors [40] and monitor the network health. It is used to get understanding about
users’ behavior inside the network, to identify their needs and troubles [41]. By
analyzing transaction patterns, developers can identify bottlenecks in the block-
chain network, such as congested nodes [42] or high transaction fees. The infor-
mation gained can be used to develop new solutions to optimize the blockchain
platform. Such optimization may apply to its performance [43; 44] or security
[45]. Additionally, transaction analysis allows developers to detect suspicious ac-
tivity or DoS attacks and take steps to mitigate the risks [46].
Blockchain Attacks Detection and Prevention
Real-time analysis of transactions is employed for monitoring smart contracts to
detect possible attacks and prevent them. The analysis of transaction data in real-
time enables the detection of any suspicious activity, allowing for timely interven-
tion to prevent or minimize the impact of an attack.
There are no strict criteria defining what to consider as an attack, therefore
various heuristics (detect maximum value transfer, ownership change, contract
upgrades) and machine learning algorithms for flow analysis may be used. When
a potential attack happens and the algorithm detects it, the stakeholders get noti-
fied so they can perform further actions. In situations where immediate response
is required, it is possible to configure automated actions, such as temporarily halt-
ing the core functionality of a contract.
One such widely used solution is Forta [47]. It gets advantage of transaction
analysis to detect and mitigate security threats in decentralized applications and
smart contracts. Forta technology is designed to analyze blockchain transactions
and data to identify and prevent hacks, exploitations, and other malicious activi-
ties. It is stated [48] that the utilization of the system could have prevented nu-
merous attacks and financial losses.
TASKS AND METHODS
Given the applications of the analysis described in the previous sections, we have
identified and selected the most frequent and critical tasks to be addressed
through blockchain transaction analysis, which can be broadly categorized into
three big groups. In this section, we will examine these tasks and the techniques
employed to address them.
Linking addresses with identities
A common task in transaction analysis is to identify the owner of the address. By
owning an address, we mean that the person holds a private key (or
seed/mnemonic phrase) and a corresponding public key, from which the address
is created. Because addresses are created using solely cryptographic mechanisms
and even before interacting with the chain, it can be impossible to get the real
identity of the owner. Fortunately, we do not need to solve the problem where
users just create their addresses, but where users actually use them. Similar to this
task, there is an opposite one – to find addresses belonging to a certain entity.
Blockchain transaction analysis: a comprehensive review of applications, tasks and methods
Системні дослідження та інформаційні технології, 2023, № 4 45
One of the most straightforward methods for linking addresses to identities is
to require users to disclose their identities when they purchase or sell cryptocur-
rency with fiat money. This is a prevalent regulatory approach, and most crypto-
currency exchanges now must follow Know Your Customer (KYC) procedures
that include several steps to identify the user. KYC procedure typically involves
several steps, such as providing identification documents and verifying the user’s
personal information, in order to confirm the user’s identity. Once a user has been
successfully identified through this process, their cryptocurrency transactions on
the exchange can be linked to their real-world identity, making it easier to track
any suspicious activity or money laundering attempts.
When a signed transaction or block is transmitted to other nodes, or a JSON-
RPC call is made on a public network, information about the sender, such as their
IP address, can be recorded by the nodes and intermediary network devices. This
can provide a means of identifying the user in the future. In general, transmitting
any information related to a blockchain address to a third-party server, such as
making a purchase on a website, searching for a transaction, or checking a bal-
ance on a blockchain explorer [49], or using a wallet application that utilizes ana-
lytics, can potentially establish a connection between the user and the address.
Another method for mapping entities to addresses is to maintain a record of
information related to the blockchain addresses that has been published by the
entity or utilize openly accessible databases. One example of such a database is a
list of malicious actors [50] or a database of sanctioned addresses, which can be
employed during analysis. Social networks scraping may also be helpful, as users
often publish addresses of their wallets. The main downside of this approach is
you need to set up complex infrastructure and collect a lot of data beforehand, and
the identity you are interested in may not be even in this data.
Flow Comprehension
By blockchain transaction flow we refer to sequences of transactions that occur
on a blockchain network. These sequences can vary from small to large and have
complex structures containing branches and joins. Complex structures may con-
tain valuable information that is not visible at first look and therefore different
methods should be applied to extract it.
Occasionally, these sequences can intentionally have intricate structures.
Criminal actors often obscure traffic, expecting that investigators will lose track.
However, by utilizing the right approaches and tools, it is possible to gain signifi-
cant insights into the flow and uncover details that may have otherwise remained
hidden. In the following sections, we will explore common approaches to analyz-
ing blockchain transaction flows.
One can manually retrieve data from the blockchain using blockchain ex-
plorers or similar tools that enable communication with blockchain nodes. Usu-
ally, they are web-based tools [51] that enable users to access and navigate the
contents of a blockchain. They have a graphical interface to examine and analyze
blockchain data, such as transaction records, account addresses, and balances. The
primary function of a blockchain explorer is to facilitate the search of specific
transactions, verify wallet balances, and examine network metrics. Although
blockchain explorers are useful for basic cases, they are not suitable for handling
complex cases involving long chains of transactions.
Ya. Dorogyy, V. Kolisnichenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 4 46
Graph visualization is used to handle the complexity of sequences of transac-
tions. Different kinds of graphs and representations can be used to fit certain
needs [52–54]. However, in the majority of cases, it is desirable to present the
flow as a graph, in which addresses are represented as nodes and transactions as
directed edges (Fig. 2). This format gives an ability to follow the asset transfer in
the most natural way. It can still be challenging to comprehend, and as such, it is
beneficial to group, filter, highlight, and conceal distinct elements, to extract or
segregate valuable information from irrelevant data.
For various reasons, users may want to transfer their assets from one net-
work into another or want to exchange one type of assent into another. They use
exchange platforms and cross-chain bridges for these purposes. Bad actors who
want to obfuscate their traffic can also take advantage of these methods. Addi-
tionally, they can use tools such as mixers [56; 57] which can significantly com-
plicate the task of investigators attempting to comprehend the transactional flow.
We can define these instruments as conversion protocols. Transactions tracing
tools should be aware of different conversion protocols and be robust enough to
perform address linking (in cases where theoretically possible). In many cases
conversion protocols, such as cross-chain bridges [58], are well-documented and
when they are not specifically designed for hiding traffic it can be an easy task to
find what is the address of the user in the other network. In cases where no docu-
mentation is available or where it is claimed that the system provides absolute
anonymity, it may be necessary to perform a manual analysis of the system. A
thorough manual analysis of the system can provide valuable insights into its
functionality. It helps in understanding the meaning of user transactions and iden-
tifying any potential flaws that could be exploited. Additionally, this type of
analysis can reveal possibilities of developing new methods to obtain additional
information about the transactions or the users [59].
In order to simplify flow analysis, various algorithms can be utilized to dis-
cover connections, patterns, and anomalies [60]. They can be used to simplify the
view or bring the most important data to the front. These algorithms can be a clas-
sic one [61] or machine learning algorithms [62].
Fig. 2. Graph visualization in Crystal Explorer [55]
Blockchain transaction analysis: a comprehensive review of applications, tasks and methods
Системні дослідження та інформаційні технології, 2023, № 4 47
There are commercial tools available on the market, such as Chainalysis Re-
actor, MistTrack and others [63], that provide convenient instruments for flow
analysis, including graph visualizations and various other features discussed in
this section.
Smart Contract Brakedown
In contrast to the regular banking transactions, blockchain transactions became
more than just funds transferring. Smart contracts let writing very complex condi-
tions for transferring funds, and as a result – building additional abstraction layers
and protocols. This allowed the creation of a new financial paradigm – DeFi.
With increased complexity, transaction analysis became harder and more
time consuming to perform. Calling a certain function on a smart contract and
transferring funds can mean different things and therefore prior contract under-
standing is needed. A call to a smart contract may create a chain of calls with dif-
ferent arguments, including calls to other contracts. A list of methods has been
developed to approach the smart contract breakdown.
Manual source code review provides a comprehensive insight into the be-
havior of a smart contract. This process involves a thorough examination of the
code, line by line, to gain understanding of both the overarching concept and the
finer points. However, this type of analysis requires extensive knowledge of pro-
gramming languages, cryptography, and blockchain technology, and can be a
time-consuming process. Reading documentation of a product may be helpful and
can clarify reasons behind some programming decisions or explain unfamiliar
concepts. However, it is not always available.
During a source code review, the availability of the source code is another
important aspect to consider. It is common for smart contract source code to be
published and, in many cases, it can be found on GitHub. However, having a
source code of the contract does not mean the exact same contract is published on
the blockchain, therefore a contract verification is needed [64] – to match source
code to on-chain bytecode.
In some cases, developers may choose not to make the source code of the
contracts publicly available. As a result, alternative techniques are necessary to
gain insight into the behavior of the contract through analyzing its bytecode. Gen-
erally, the process is called reverse engineering. It is similar to the code review
but more complex and requires more effort. The reason for this is that a compiled
smart contract contains significantly less information compared to the original
code. In cases of optimizations the resulting bytecode gets even more compli-
cated, as human written code is converted into more efficient code patterns. To
simplify the reverse engineering process disassemblers (convert bytecode to EVM
opcodes) and decompilers are used [65; 66]. Decompilers convert a bytecode to
high-level representation. However, due to the loss of information during compi-
lation, the code does not look like the original code.
If we want to look at the actual execution of the smart contract on the chain,
block explorers may be helpful for simple cases. Some of them have transaction
decoders and can provide execution traces. There are tools developed specifically
for transaction decoding, such as Transaction Tracer [67] or similar [68], which
provide a call trace, which is a tree of function calls and arguments, made through
different contracts during transaction execution. Furthermore, there are tools for
Ya. Dorogyy, V. Kolisnichenko
ISSN 1681–6048 System Research & Information Technologies, 2023, № 4 48
local EVM tracing [69], which allow detailed examination of smart contract
transactions. Development environments, like Truffle, have even more convenient
means to debug on-chain transactions [70].
Automated analysis tools for smart contracts can be used to get a better un-
derstanding of smart contracts. Usually, they are divided into two categories –
static and dynamic analyzers [71].
Static analysis tools perform contract analysis without running them. Slither
framework [72], is one of such tools, is designed to automatically find vulner-
abilities, give information about the contract and its functions, give summary
about the authorization accesses and many other.
Dynamic analysis tools, on the other hand, perform analysis by executing
smart contracts or their parts. Various classes of dynamic analysis tools used for
analyzing smart contracts such as symbolic execution tools, Satisfiability Modulo
Theories (SMT) solvers, taint analyzers and fuzzers [73]. Mythril, Echidna [74]
and Manticore [75] are one of the most widely used tools to find vulnerabilities in
the code, to find a set of inputs that transit a program into an unexpected state or
to explore all possible states. These tools and approaches are not mutually exclu-
sive, but rather they give different perspectives on how a smart contract works.
Commercial tools like MythX [76] combine static and dynamic approaches
to get the best of both worlds and provide most comprehensive results.
Recent research and developments in artificial intelligence (more precisely,
large language models such as ChatGPT [77]), allowed using these technologies
for explaining the code, reverse-engineering [78] and even for finding vulnerabili-
ties [79]. These tools are already used now and will be even more adopted in the
near future to assist during the code analysis.
CONCLUSIONS
Blockchain transaction analysis is a crucial tool for gaining insights into the be-
havior of users on blockchain networks. From anti-money laundering and fraud
detection to supply chain management and tax compliance, there are many appli-
cations for transaction analysis in the world of cryptocurrency and beyond.
Despite the challenges posed by the anonymous and decentralized nature of
blockchain networks, there is a growing awareness of the importance of transpar-
ency and accountability in the cryptocurrency industry. By utilizing the insights
gained through transaction analysis, regulators, businesses, and other stakeholders
can work together to build a more secure, efficient, and sustainable blockchain
ecosystem.
The methods and techniques used in transaction analysis continue to evolve,
and there is a growing need for more sophisticated tools to keep pace with the
complexity of blockchain networks. Advances in machine learning, graph analy-
sis, and other data science techniques are likely to have a significant impact on the
future of blockchain transaction analysis.
In our future work we will analyze multiple blockchain networks to get ad-
vantages of their specifics to improve and develop new methods for analyzing
transactions. We will dive into protocols at different layers and develop solutions
to extract additional information that is not available using traditional methods.
Blockchain transaction analysis: a comprehensive review of applications, tasks and methods
Системні дослідження та інформаційні технології, 2023, № 4 49
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Received 12.05.2023
INFORMATION ON THE ARTICLE
Yaroslaw Yu. Dorogyy, ORCID: 0000-0003-3848-9852, National Technical University
of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine, e-mail: argusyk@gmail.com
Vadym Yu. Kolisnichenko, ORCID: 0009-0009-6472-2807, National Technical Univer-
sity of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine, e-mail:
vadym.kolisnichenko@gmail.com
АНАЛІЗ БЛОКЧЕЙН-ТРАНЗАКЦІЙ: КОМПЛЕКСНИЙ ОГЛЯД
ЗАСТОСУВАНЬ, ЗАВДАНЬ ТА МЕТОДІВ / Я.Ю. Дорогий, В.Ю. Колісніченко
Анотація. Аналіз блокчейн-транзакцій є потужним інструментом для отри-
мання інформації про дії та поведінку учасників у блокчейн-мережах. Розгля-
нуто застосування, завдання та методи, пов’язані з аналізом блокчейн-
транзакцій. Розглянуто різні способи використання аналізу транзакцій, почи-
наючи від його інструментальної ролі в розробленні блокчейн-систем і закін-
чуючи його ключовим значенням у сфері кримінальних розслідувань. Із вико-
ристанням загальних методів і технології, що застосовуються у ході такого
аналізу, розкрито приховані уявлення та знайдено інформацію, яка є неочеви-
дною. Мета рукопису – всебічний погляд на важливе значення аналізу блок-
чейн-транзакцій із розкриттям його ключової ролі у криптовалютній індустрії
та широкий спектр застосувань поза нею.
Ключові слова: блокчейн-транзакції, аналіз транзакцій, відстеження транзак-
цій, аналіз потоків, блокчейн криміналістика.
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| id | journaliasakpiua-article-280231 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-07-17T10:28:10Z |
| publishDate | 2023 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
| record_format | ojs |
| resource_txt_mv | journaliasakpiua/df/ccd2dc557e84b3de5e7ec06fd5c899df.pdf |
| spelling | journaliasakpiua-article-2802312024-02-01T21:03:07Z Blockchain transaction analysis: a comprehensive review of applications, tasks and methods Аналіз блокчейн-транзакцій: комплексний огляд застосувань, завдань та методів Dorogyy, Yaroslaw Kolisnichenko, Vadym блокчейн-транзакції аналіз транзакцій відстеження транзакцій аналіз потоків блокчейн криміналістика blockchain transactions transaction analysis transaction tracing flow analysis blockchain forensics Blockchain transaction analysis is a powerful tool to gain insights into the actions and conduct of participants within blockchain networks. This article aims to extensively examine the applications, tasks, and methods associated with blockchain transaction analysis. We look at various uses of transaction analysis, ranging from its instrumental role in blockchain development to its pivotal significance in the field of criminal investigations. By leveraging common techniques and technologies employed in conducting such an analysis, we unlock hidden insights and uncover information that is not visible at first look. This article offers a wide-ranging perspective on the profound significance of blockchain transaction analysis while shedding light on its key role within the cryptocurrency industry and its wide-ranging applications beyond. Аналіз блокчейн-транзакцій є потужним інструментом для отримання інформації про дії та поведінку учасників у блокчейн-мережах. Розглянуто застосування, завдання та методи, пов’язані з аналізом блокчейн-транзакцій. Розглянуто різні способи використання аналізу транзакцій, починаючи від його інструментальної ролі в розробленні блокчейн-систем і закінчуючи його ключовим значенням у сфері кримінальних розслідувань. Із використанням загальних методів і технології, що застосовуються у ході такого аналізу, розкрито приховані уявлення та знайдено інформацію, яка є неочевидною. Мета рукопису – всебічний погляд на важливе значення аналізу блокчейн-транзакцій із розкриттям його ключової ролі у криптовалютній індустрії та широкий спектр застосувань поза нею. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2023-12-26 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/280231 10.20535/SRIT.2308-8893.2023.4.03 System research and information technologies; No. 4 (2023); 37-53 Системные исследования и информационные технологии; № 4 (2023); 37-53 Системні дослідження та інформаційні технології; № 4 (2023); 37-53 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/280231/290370 |
| spellingShingle | блокчейн-транзакції аналіз транзакцій відстеження транзакцій аналіз потоків блокчейн криміналістика Dorogyy, Yaroslaw Kolisnichenko, Vadym Аналіз блокчейн-транзакцій: комплексний огляд застосувань, завдань та методів |
| title | Аналіз блокчейн-транзакцій: комплексний огляд застосувань, завдань та методів |
| title_alt | Blockchain transaction analysis: a comprehensive review of applications, tasks and methods |
| title_full | Аналіз блокчейн-транзакцій: комплексний огляд застосувань, завдань та методів |
| title_fullStr | Аналіз блокчейн-транзакцій: комплексний огляд застосувань, завдань та методів |
| title_full_unstemmed | Аналіз блокчейн-транзакцій: комплексний огляд застосувань, завдань та методів |
| title_short | Аналіз блокчейн-транзакцій: комплексний огляд застосувань, завдань та методів |
| title_sort | аналіз блокчейн-транзакцій: комплексний огляд застосувань, завдань та методів |
| topic | блокчейн-транзакції аналіз транзакцій відстеження транзакцій аналіз потоків блокчейн криміналістика |
| topic_facet | блокчейн-транзакції аналіз транзакцій відстеження транзакцій аналіз потоків блокчейн криміналістика blockchain transactions transaction analysis transaction tracing flow analysis blockchain forensics |
| url | https://journal.iasa.kpi.ua/article/view/280231 |
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