Analyzing Vulnerabilities of Bitcoin: A Study of Sybil, Finney, and

Vector76 Attacks and Their Mitigation Strategies

Qinhan Ren

School of Cyber Engineering, Xidian University, Xi'an, China

Keywords: Bitcoin, Sybil Attack, Finney Attack, Blockchain Networks.

Abstract: This study explores three critical attack vectors includes Sybil, Finney, and Vector76 that pose significant

threats to the security of Bitcoin and other blockchain networks. The research analyzes the mechanics of each

attack and evaluates their success rates under different network conditions. The Sybil attack is examined in

the context of node creation and identity manipulation in decentralized networks. The Finney attack is

analyzed for its exploitation of transaction timing vulnerabilities, while the Vector76 attack is studied for how

it leverages network propagation delays to achieve double spending. By investigating these attack

mechanisms, the study identifies network synchronization and enhanced transaction processing as potential

mitigation strategies. The findings highlight the importance of improving block propagation speeds and real-

time monitoring systems to strengthen the resilience of blockchain networks. These insights offer valuable

guidance for developers and researchers working to bolster the security and stability of decentralized systems,

ensuring better protection against evolving threats in cryptocurrency environments.

1 INTRODUCTION

The growth of blockchain techniques and

cryptocurrencies promote the Bitcoin to become the

bedrock in the digital economy. Bitcoin, which is a

decentralized cryptocurrency, operates on a peer-to-

peer network without a central authority. Meanwhile

it ensures the transparency and security by

cryptographic techniques and the Proof of Work

(PoW) consensus mechanism (Nakamoto, 2008).

This decentralized nature contains several

vulnerabilities, which makes the network susceptible

when it faces to various forms of attack. Among these

critical threats are the Sybil, Finney, and Vector76

attacks. They not only exploit different parts of

Bitcoin's infrastructure but also target their consensus

mechanism, transaction verification, and propagation

processes (Bonneau et.al, 2015). Understanding and

mitigating these attacks is significant for the security

and stability of Bitcoin and other cryptocurrencies

which has been built on the similar consensus

mechanism. These attacks not only threaten the

integrity of transactions but also undermine the trust

in the overall network system.

https://orcid.org/0009-0002-6613-8902

First introduced by Douceur in 2002, the Sybil

attack is one of the most considered forms of attack

in the decentralized systems (Douceur, 2002). In this

attack, a single malicious actor creates multiple

identities in a network to obtain disproportionate

control over the system, which potentially disrupts

consensus. Although The Sybil attack is always

problematic in peer-to-peer networks, Bitcoin’s PoW

mechanism provides some protection like making

identity creation costly through mining. Nevertheless,

this cannot completely prevent such attack, since

powerful adversaries companied by significant

computational resources could still influence the

network (Heilman et.al, 2015). On the other hand, the

Finney attack, which has been first described by

Bitcoin creator Satoshi Nakamoto, exploits the

concept of double-spending by pre-mining a block

which contains a transaction and broadcasting it after

transaction has been accepted (Karame et.al,

2012).While this attack might be rare, it highlights a

fundamental vulnerability in the method which used

by the Bitcoin when it handles transaction finality and

trust. The Vector76 attack is an advanced form of

double-spending. It combines elements of the Finney

attack with race attacks. In that case, the Vector76

428

Ren and Q.

Analyzing Vulnerabilities of Bitcoin: A Study of Sybil, Finney, and Vector76 Attacks and Their Mitigation Strategies.

DOI: 10.5220/0013525400004619

In Proceedings of the 2nd International Conference on Data Analysis and Machine Learning (DAML 2024), pages 428-431

ISBN: 978-989-758-754-2

attack could take advantage of the timing between

transaction confirmation and block propagation to

defraud recipients (Decker and Wattenhofer, 2014).

Nowadays, growing researches have been

handled to mitigate these vulnerabilities. Bonneau et

al. provided a comprehensive overview of the

challenges of Bitcoin, which contains vulnerabilities

of Bitcoin like the Sybil Attack (Bonneau and et.al,

2015). Their work emphasized the importance of

network design and consensus mechanisms in

protecting the cryptocurrency under these threats.

Moreover, Heilman et al. raised the concept of eclipse

attacks. It is a variant of Sybil attacks which isolates

nodes from the rest of the network. Hence, it allows

adversaries to control the victim’s view of the

blockchain. Solutions of that attack such as increasing

the number of block confirmations, implementing

stronger identity verification systems, or even

boosting node communication protocols have been

introduced to face to these attacks Bitcoin continues

to evolve (Rosenfeld, 2014). However, the methods

used by attackers keep to update (Wen et.al., 2021).

It necessitates ongoing research and updates of the

Bitcoin protocol (Hamdi et. al., 2024).

This paper aims to provide a thorough review of

the various attacks that present significant threats to

blockchain systems, with a particular focus on how

these attacks compromise the integrity, security, and

functionality of blockchain networks. As

decentralized platforms, blockchains are vulnerable

to a wide range of attack vectors, such as 51% attacks,

double-spending attacks, Sybil attacks, and smart

contract vulnerabilities. These threats can undermine

the trust and reliability of blockchain systems, posing

severe consequences for applications such as

cryptocurrency transactions, decentralized finance

(DeFi), and other sectors relying on blockchain

technology (Gervais et al., 2016).

The paper not only categorizes these attacks based

on their methodology and potential damage but also

critically evaluates the existing defense strategies

employed by blockchain networks. These defense

mechanisms include consensus algorithms (like Proof

of Work and Proof of Stake), cryptographic

techniques, network monitoring, and smart contract

auditing tools. While some strategies have proven

effective in mitigating certain threats, this paper

highlights their limitations in addressing more

sophisticated or evolving attack methods. For

instance, while Proof of Work offers strong security

through decentralization, it is energy-intensive and

may lead to mining centralization, which itself

presents security risks.

Furthermore, this study explores future directions

for bolstering blockchain security. It delves into

emerging defense strategies such as hybrid consensus

mechanisms, zero-knowledge proofs, and machine

learning-based anomaly detection. By analyzing

these approaches, the paper seeks to offer insights

into potential innovations that could enhance

blockchain resilience. Ultimately, the analysis

contributes to a deeper understanding of the evolving

challenges in blockchain security, aiming to guide

future research and development efforts in creating

more secure and robust blockchain ecosystems.

2 METHODOLOGIES

2.1 Research Process

The primary objective of this study is to analyze the

vulnerabilities in consensus mechanism of Bitcoin by

focusing on three specific attack vectors: Sybil,

Finney, and Vector76 attacks. This research adopts a

systematic approach, which involves a

comprehensive literature review, technical analysis of

the attack mechanisms, and an evaluation of existing

mitigation strategies. The study begins by outlining

the fundamental concepts of these attacks, with a

particular focus on how they exploit the decentralized

nature of Bitcoin architecture. The technical

breakdown of each attack is presented in detail,

explaining how they operate and pinpointing the

stages and components that enable these

vulnerabilities. The paper illustrates the mechanisms

behind the Sybil, Finney, and Vector76 attacks,

providing a deeper understanding of their inner

workings.

This is supported by detailed analysis and visual

figures that map out the stages of each attack. The

research is divided into several key stages. First, a

thorough review of existing literature is conducted to

gain insights into previous studies and

methodologies. Following this, a technical analysis of

Bitcoin network is performed, with a focus on

identifying potential weaknesses in the transaction

validation process, block propagation, and consensus

formation. The study then introduces a visual pipeline

figure that illustrates the transaction flow and

identifies key points where each attack vector could

intervene. This includes identity creation in the Sybil

attack, pre-mining in the Finney attack, and timing

manipulation in the Vector76 attack. Finally, the

research assesses the effectiveness of current defense

mechanisms and offers recommendations to

strengthen Bitcoin network against these

Analyzing Vulnerabilities of Bitcoin: A Study of Sybil, Finney, and Vector76 Attacks and Their Mitigation Strategies

429

vulnerabilities. The flow of the study is depicted in

Figure 1.

Figure 1: Research process (Picture credit: Original).

2.2 Attack Method

This study focusses on three prominent attacks in the

Bitcoin network: Sybil, Finney, and Vector76. Posing

significant risks to the network's security and

integrity, each of the attack exploits different aspects

of Bitcoin’s consensus and transaction validation

process. The Sybil attack is based on the principle of

identity manipulation. In that case, a malicious actor

creates multiple fake nodes to gain disproportion over

the network (Douceur, 2002). Leading to potential

disruptions in consensus and decision-making

processes, the main concept of the Sybil attack is

constructed by its ability of changing the system with

the falsified identities. The primary characteristic of

the Sybil attack is its scalability because a single

attacker can create numerous identities with a low

cost.

The Finney attack is an early double-spending

attack which exploits the gap between block mining

and transaction confirmation. In this attack, the

adversary pre-mines a block which includes a

transaction sending coins to themselves. Before

broadcasting this pre-mined block, the attacker makes

a transaction with the same coins to a different

recipient (Karame, 2012). Once the second

transaction is accepted, the pre-mined block is

broadcast, invalidating the second transaction and

effectively allowing double-spending. This attack

highlights vulnerabilities in the transaction finality.

The Vector76 attack combines elements of the race

attack and the Finney attack. It relies on the timing

between the block propagation and transaction

confirmation. Once the attack handles the timing, it

can exploit the double-spending vulnerability.

Specifically, when the attacker sending a conflicting

transaction to a merchant, the attacker broadcasts a

valid block simultaneously. In that case, before the

conflicting block invalidates it, the attacker can

convince the merchant that the transaction is valid by

manipulating the timing (Decker and Wattenhofer,

2014). The defining feature of the Vector76 attack is

its reliance of precise timing manipulation, which

offers a more sophisticated form of double-spending.

2.3 Defense Method

To counter these attacks on Bitcoin, several defense

mechanisms have been proposed and implemented,

each of them tailored to the specific characteristics of

the Sybil, Finney, and Vector76 attack.

Against Sybil attacks, Bitcoin’s PoW inherently

offers some resistance by making it computationally

expensive to generate multiple fake identities.

Because of creating multiple identities requires

significant computational resources, the cost of

executing a successful Sybil attack becomes

prohibitively high. Additional defenses include

increasing node diversity and using reputation-based

systems, where nodes gain influence based on trust or

participation, rather than the number of identities.

For Finney attacks, the most effective

countermeasure is increasing the number of required

block confirmations before accepting a transaction as

final. By waiting for multiple confirmations,

merchants can reduce the risk of accepting a

transaction that might later be invalidated by a pre-

mined block. Some proposals also suggest using real-

time transaction monitoring systems to detect

anomalies associated with double-spending attempts.

To prevent Vector76 attacks, improvements of the

block propagation protocol, like the adoption of

compact blocks or the fast block relay techniques, are

able to minimize the time gap between block

broadcast and confirmation. Furthermore, combining

the transaction malleability combines with a more

robust transaction verification processes can prevent

attackers from manipulating the network’s timing.

3 RESULT AND DISCUSSION

Generating fake nodes, the Sybil attack overwhelm

the peer-to-peer network. One of its key strengths is

the scalability, which means the more nodes the

attacker can create, the more powerful the attack

becomes. In that case, the scalability makes the Sybil

attack particularly effective in the decentralized

network. However, the Sybil attack has significant

weaknesses. The main drawback is its reliance, which

generates and maintains a large scale of fake nodes,

which are resource-intensive when networks

implement mechanisms like PoW or proof-of-stake

(PoS) that require effort to maintain each node.

Additionally, networks can defend against the Sybil

attack by enforcing node reputation systems or

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limiting the number of new connections a node can

make.

Enabling double-spending without the control of

the significant portion of the network, the Finney

attack exploits the vulnerability of unconfirmed

transactions in Bitcoin. The advantages of this attack

make the attack a relatively low-cost attack compared

to others. However, the Finney attack is limited in the

scope. Its effectiveness is highly dependent on the

ability to pre-mine blocks and control transaction

timing, making it less reliable. As a result, it is less

likely to be widely effective in the network which

owns high transaction volume or fast confirmation

times. Additionally, requiring multiple confirmations

for transactions effectively nullifies this attack, as it

is only viable for transactions that are accepted after

zero confirmations.

Combining aspects of the Finney attack with a

race attack, the Vector76 attack is a more

sophisticated method of double-spending. Its strength

lies in its ability to exploit the timing differences

between transaction broadcasting and block

propagation. By broadcasting a transaction to a

portion of the network while mining an alternate

block that excludes this transaction, the attacker can

reverse the original transaction when the alternate

block is propagated. Nevertheless, because the

Vector76 attack requires precise control over the

transaction timing and the block propagation which

makes it difficult to execute consistently, the

complexity of the Vector76 attack is the weakness of

itself. Furthermore, improvements in the network

synchronization can significantly reduce the chances

of success. Solutions such as reducing block

propagation delay and requiring multiple

confirmations reduce the effectiveness of this attack.

4 CONCLUSIONS

This research focused on analyzing three common

Bitcoin attack methods: Sybil, Finney, and Vector76.

Through a comprehensive approach, this study

evaluated these attack vectors by examining their

underlying mechanisms, success rates, and associated

defensive measures. The analysis combined

theoretical models with practical simulations to

reveal the operational characteristics and real-world

impacts of these attacks on blockchain networks. The

experiments demonstrated both the vulnerabilities

these attacks exploit and the limitations of current

defense strategies. Moving forward, network

synchronization will be a key area of research to

enhance blockchain security. Future studies will

emphasize improving block propagation speeds and

developing real-time detection systems to more

effectively counter these attack vectors. At the same

time, efforts will focus on maintaining scalability and

system performance, ensuring that increased security

does not compromise the efficiency or robustness of

blockchain networks. This research underscores the

need for continuous advancements in both attack

mitigation and system optimization to keep pace with

evolving threats in the cryptocurrency ecosystem.

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