A Comparative Analysis of Cryptographic Techniques for Privacy

Preservation in Blockchain-Based Dispute Resolution

Yassine Obeid

, Christiana Zaraket

and Layth Sliman

Efrei Paris, Paris Pantheon-Assas University, Paris, France

Saint Joseph University of Beirut, ESIB, Beirut, Lebanon

Keywords: Confidentiality, Untraceable Transactions, Cryptography, Transparency, Stealth Addresses, Blockchain

Privacy.

Abstract: Digital innovations have profoundly altered the landscape of remote collaboration, yet these innovations

frequently lead to conflicts that necessitate robust and fair decentralized decision-making systems.These

conflicts occur either because they are not yet regulated by law, or because they arise from disputes associated

with onchain applications, or simply because they are easier to resolve online. Public blockchains,

characterized by their transparency and immutability, present viable solutions for these systems. However,

the very transparency that makes blockchains appealing also introduces significant privacy concerns, as the

traceability of transactions can jeopardize the anonymity of participants. Although users can maintain a degree

of pseudoanonymity through cryptographic addresses, their activities remain publicly accessible, which poses

considerable risks if their identities are uncovered. To mitigate these challenges, various cryptographic

methods, including stealth addresses and zero-knowledge proofs (zk-SNARKs), have been developed to

bolster transaction privacy. This paper distinguishes itself by offering an in-depth examination of these

privacy-enhancing techniques, emphasizing their integration within blockchain environments, as well as their

scalability and programmability. Additionally, we address key limitations, such as the balance between

privacy and computational complexity, along with the interoperability issues that arise among privacy-centric

protocols. By providing a comparative analysis and investigating future research avenues, this paper

contributes valuable perspectives on reconciling privacy and transparency in decentralized collaboration

frameworks.

1 INTRODUCTION

In the past few decades, the advent of digital

transformation has markedly improved remote

collaboration, fostering interactions across diverse

industries and geographical boundaries. This

evolution has enabled individuals and organizations

to engage in effective teamwork from afar. However,

these collaborations are not without challenges;

disputes may arise, necessitating the establishment of

decentralized decisionmaking frameworks that are

both resilient and fair. Public blockchains, with their

transparency and immutability, appear promising for

facilitating these decentralized solutions.Yet, this

very transparency raises major privacy concerns, as

the traceability of transactions can compromise the

anonymity of participants.

On public blockchains like Bitcoin and Ethereum,

users operate under a pseudo-anonymous model,

identified by cryptographic addresses. However,

since the details of transactions remain publicly

accessible, if a user’s identity linked to an address is

revealed, their transaction history becomes traceable.

This exposure poses serious privacy risks,

particularly for active participants who may be

vulnerable to tracing and profiling attempts. Thus,

finding a balance between transaction privacy and

transparency is a critical challenge in these

decentralized systems.

Before addressing the issue of privacy, it is

important to consider why public blockchain makes

transactions visible. This transparency is essential for

preventing double-spending, ensuring that each

transaction is verified and unique, thus preventing the

same asset from being used multiple times. One of the

most significant challenges arises from this: making

transactions untraceable and unlinkable on the

blockchain. Untraceability and unlinkability are two

Obeid, Y., Zaraket, C. and Sliman, L.

A Comparative Analysis of Cryptographic Techniques for Privacy Preservation in Blockchain-Based Dispute Resolution.

DOI: 10.5220/0013415500003929

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 27th International Conference on Enterprise Information Systems (ICEIS 2025) - Volume 1, pages 1089-1096

ISBN: 978-989-758-749-8; ISSN: 2184-4992

1089

distinct but crucial concepts. Untraceability involves

the impossibility of determining the sender of a

transaction among a group of potential senders, thus

ensuring a high level of privacy. Unlinkability, on the

other hand, implies the impossibility of verifying that

two outgoing transactions are intended for the same

recipient, further protecting identity and connections

between transactions (Bernabe et al., 2019).

In response to these challenges, researchers have

explored advanced cryptographic methods to render

transactions untraceable while maintaining the

transparency necessary to secure decentralized

processes. Stealth addresses and zk-SNARKs help

obscure transaction origins and destinations. These

techniques enhance user privacy while preserving

system integrity. These methods enable public

blockchains to support secure and privacy-focused

collaborative processes while adhering to

transparency requirements.

This article provides a comprehensive analysis of

cryptographic techniques designed to enhance

transaction privacy and security within decentralized

frameworks. By synthesizing existing literature and

evaluating contemporary methodologies, it lays the

foundation for novel approaches to strengthening

privacy in public blockchain environments, while

addressing trade-offs between anonymity, efficiency,

and usability. We analyze the limitations of current

methods and discuss key challenges in achieving an

effective balance between privacy and transparency.

The remainder of this article is organized as follows:

Section II provides an overview of stealth addresses,

zk-SNARKs, and associated cryptographic

techniques. Section III presents state-of-the-art

methods for untraceable transactions and their

limitations. Section IV identifies key challenges, and

Section V proposes potential research avenues.

Finally, Section VI concludes by offering our

perspective on privacy in public blockchains.

2 BACKGROUND

This section aims to offer a concise summary of

stealth addresses, zk-SNARKs, and various services

designed to render transactions untraceable.

2.1 Stealth Addresses

Stealth addresses illustrated in Figure 1 allow

transactions to be concealed by creating a new

address for each operation. This prevents an observer

from tracking transactions intended for a specific

address. This concept is particularly important in the

context of public blockchains, where the traceability

of transactions poses a significant risk to user

privacy.Stealth addresses are already integrated into

Monero (Monero, 2013), a privacy-focused

cryptocurrency, and there are ongoing efforts to

implement them within Ethereum (Wahrstätter et al.,

2024).

In public blockchains, every transaction is

recorded on a public ledger, meaning that all

addresses and their associated transactions can be

observed. Stealth addresses provide a means to

protect user privacy by generating unique addresses

for each transaction.

When a sender wishes to send an amount to a

recipient, they create a stealth address that does not

exist beforehand. This process involves several steps:

1. Generation of a Stealth Address: The sender

uses their ephemeral public key and the recipient’s

stealth public key to generate a unique stealth

address. This address is not published in the ledger,

making it difficult for an observer to associate it

with the recipient’s identity.

2. Sending the Transaction: Once the stealth

address is generated, the sender can send the

amount to this address. Therefore, the sender is

sending funds to an address that, in the eyes of the

public, is not linked to a specific user, as it was

created specifically for this transaction.

3. Accessing Funds by the Recipient: To access the

funds sent to the stealth address, the recipient

must possess the corresponding private key. To do

this, they use their spending private key (which is

linked to their identity) and a cryptographic

method to recover the funds. By combining their

private key and the ephemeral public key

generated by the sender, they can prove they are

the rightful owner of the stealth address.

4. Spending the Funds: Once the recipient has

access to the stealth address, they can spend the

funds as they wish, again using a stealth address

for their own transactions, thus ensuring that each

new operation remains private.

This ability to create and use stealth addresses

ensures that even if an observer can see the

transaction on the blockchain, they cannot associate

the funds with the recipient’s identity, thereby

enhancing user privacy.

2.2 zk-SNARKs

A zk-SNARK is a cryptographic protocol (Mayer,

2016) that allows a prover to demonstrate to a verifier

BEST 2025 - Special Session on Blockchain and Enhanced Security for a New Era of Trust

1090

Figure 1: Stealth Address Process.

that he knows a solution to a problem or that he has

performed a computation correctly without revealing

any information about the solution itself. This type of

proof has several key characteristics:

• Zero-Knowledge: The verifier learns that the

proof is correct but gains no further information

about the underlying data or computation.

• Succinct: The proof size is very small (often only

a few hundred bytes), regardless of the size of the

computation being proven.

• Non-Interactive: No extensive interaction is

needed between the prover and verifier. The proof

is unique and can be verified directly.

• Argument of Knowledge: The proof guarantees

that the prover genuinely possesses the correct

information or solution.

The main steps in a zk-SNARK are as follows:

1. Setup: this step is used to create public parameters

(often denoted pp) that are utilized by both the

prover and the verifier. Depending on the type of

zk-SNARK, this may require a trusted setup,

where a trusted entity generates these parameters

and then destroys certain secret information.

There are also zk-SNARKs with a universal or

transparent setup, which do not require this trusted

setup phase.

2. Proof Generation: the prover uses the public

parameters and their solution or computation to

generate a succinct proof. The proof is generally

much smaller than the underlying computation or

data.

3. Verification: the verifier uses the proof and

public parameters to verify that the proof is

correct. This is done in constant time (very

quickly) without the verifier needing to know the

prover’s computation or data.

There are different types of zk-SNARK setups, each

designed to meet distinct security and performance

requirements. For instance, some zk-SNARKs

require a trusted setup, where a reliable entity

generates public parameters and removes certain

confidential information to ensure system integrity. In

contrast, zkSNARKs with a universal or transparent

setup eliminate this initial phase by employing

protocols or algorithms that allow any participant to

independently verify the process, avoiding reliance

on a third party. These methodologies cater to a range

of applications, from highly confidential systems

with minimal external involvement to more adaptable

solutions that emphasize transparency in verification.

2.3 Cryptographic Commitments

Cryptographic commitments are protocols that

allow an individual (the committer) to commit to a

secret value in a way that prevents any alteration

afterward while keeping it hidden from other parties

(the verifiers) until a designated moment. This

technique is crucial for many cryptographic and

security protocols, as it ensures both the integrity and

confidentiality of the data without requiring

immediate disclosure. A cryptographic commitment

is often compared to a "locked box": the committer

can seal their value inside (the commitment) but

cannot modify it once the box is closed, with the

"key" remaining secret until the reveal phase. This

commitment process generally unfolds in three main

steps:

1. Commitment Phase: the committer chooses a

secret value m (message) and a random factor r.

Using a commitment function Com, they create a

commitment C =Com(m,r), which hides m and is

computationally infeasible to reverse without

knowing both m and r. The committer then sends

the commitment C to the verifiers, ensuring that m

remains immutable and hidden until the reveal

phase.

2. Holding Phase: the commitment C is retained

without revealing the values of m or r. The verifier

only knows that C represents a specific fixed m,

but they have no access to the actual values of m

or r.

3. Reveal Phase: the committer reveals m and r to

the verifiers. Each verifier can compute Com(m,r)

A Comparative Analysis of Cryptographic Techniques for Privacy Preservation in Blockchain-Based Dispute Resolution

1091

and verify that it matches the initially received C,

thereby ensuring the integrity of m. If the equation

C =Com(m,r) holds, the verifier accepts m as the

committed value.

Different types of cryptographic commitment

setups exist to suit varying security and application

needs. For example, some commitments require a

trusted setup where an entity securely generates and

later destroys certain secret values involved in the

setup process. Other types of commitments, such as

those with a transparent setup, do not rely on a trusted

party, instead using protocols that allow any party to

verify the setup independently. These approaches

offer flexibility across applications that prioritize

either trust minimization or transparency in the

commitment process.

2.4 Ring Signatures

Ring signatures are a cryptographic technique used to

obscure the sender in a transaction, ensuring

anonymity. Ring signatures allow a user’s transaction

to blend with others, making it difficult to determine

the actual signer. This process involves several steps:

1. Formation of the Ring: the sender’s public key

is combined with a selection of other randomly

chosen public keys from the blockchain, creating

a “ring” of possible signers. This ring provides

plausible deniability, as any of these keys could

feasibly be the signer.

2. Signing Process: the sender generates a unique

ring signature using their private key along with

the set of public keys. Importantly, this signature

proves that one of the keys in the ring signed the

transaction, without revealing which one.

3. Verification: the network nodes can verify the

signature’s validity without identifying the actual

signer, ensuring the integrity of the transaction.

This verification ensures that no double-spending

occurs while maintaining the anonymity of the

sender.

Ring signatures significantly enhance privacy by

allowing the source of funds to remain untraceable,

providing users with both security and confidentiality.

3 STATE OF THE ART

In this section, we will examine a range of pertinent

methodologies, emphasizing their advantages while

also addressing their shortcomings.

BaseSAP (Wahrstätter et al., 2024) proposes a

modular protocol to enable untraceable transactions

on public blockchains. This protocol operates as a

layer above foundational protocols like DKSAP,

providing a platform to integrate stealth addresses

through various cryptographic algorithms. In this

approach, senders publish announcements of

ephemeral public keys via an Announcer contract,

allowing recipients to identify transactions intended

for them while ensuring the privacy of involved

parties. To enhance protocol efficiency and reduce

operational costs, mechanisms like "view tags" and

toll or staking systems are included to protect against

Denial of Service (DoS) attacks.

While the protocol initially builds on DKSAP,

advanced versions like PDKSAP (Feng et al., 2020)

and EDKSAP (Feng et al., 2021) offer improvements

in computation, notably through bilinear pairing to

reduce the number of operations required and

processing time. The main differences between these

protocols are summarized in Table 1, highlighting

how each variation optimizes for specific aspects like

privacy, computational efficiency, and parsing

performance.

This modular framework enables BaseSAP to be

adapted to different implementations, addressing

specific privacy and anonymity needs.However, a

limitation of BaseSAP is that it does not conceal the

sender’s address, which may reduce the overall

anonymity in certain scenarios.

Whereas BaseSAP adds a privacy layer on

Ethereum, which does not natively use stealth

addresses, blockchains like Monero have integrated

stealth addresses from the start and combine them

with other cryptographic techniques to further

enhance privacy (Monero, ).

Key privacy technologies include Ring

Confidential Transactions (RingCT) (Noether, 2015),

which conceal transaction amounts using

cryptographic commitments (specifically Pedersen

commitments) to ensure both confidentiality and

verifiability of transaction amounts. Other methods

include stealth addresses, generating a unique address

for each transaction, and ring signatures

(Vijayakumaran, 2018), which obscure the sender’s

identity by mixing their signature with others.

Additionally, transactions can be routed through

Tor/I2P to mask IP addresses, while Dandelion++

(Fanti et al., 2018) protects user anonymity by

obscuring transaction origins before they are publicly

relayed.

Zcash (Ben-Sasson et al., 2014), one of the first

independent blockchains to incorporate zk-SNARKs,

focuses primarily on financial transaction privacy. It

BEST 2025 - Special Session on Blockchain and Enhanced Security for a New Era of Trust

1092

Table 1: Comparison of DKSAP, PDKSAP, and EDKSAP Protocols.

Criterion DKSAP PDKSAP EDKSAP

Utilization of Analysis Key Yes Yes Yes

Spending Key

Yes, separate for

transaction security

Yes, separate Yes, separate

Main Goals

Basic privacy and sender

anonymity

Reduced computations in the

parsing process

Performance improvement

by reducing calculations

Parsing Optimization No

Yes, by reducing computations

with a "view tag"

Yes, through the use of

ilinear pairings

Cryptographic Algorithms

Based on standard

elliptic curve operations

Based on elliptic curves and

"view tags"

Based on bilinear pairings

for optimized computation

allows users to choose between transparent and

shielded transactions, with shielded transactions fully

masking addresses and amounts. However, Zcash

remains limited to private financial transactions and

does not support decentralized applications (dApps),

restricting its ecosystem to use cases centered on

transaction privacy.

Aleo (Aleo, 2024) represents a cutting-edge

blockchain initiative aimed at enhancing privacy

beyond mere transactional confidentiality by

facilitating the development of confidential

decentralized applications (dApps) through its

innovative zeroknowledge virtual machine (zkVM)

(Liu et al., 2024). The zkVM empowers Aleo with a

high degree of programmability, enabling developers

to construct intricate dApps while ensuring the

protection of sensitive data. Nevertheless, this level

of flexibility incurs certain drawbacks; specifically,

the computational demands associated with

confidential applications can be quite substantial,

leading to increased costs for proof generation.

Furthermore, as a nascent blockchain, Aleo

encounters obstacles in achieving interoperability

with more established blockchain networks, which

are often characterized by their closed systems,

distinct consensus mechanisms, and varying privacy

protocols. This situation hinders Aleo’s capacity to

integrate smoothly into the broader blockchain

ecosystem. The relative immaturity of Aleo may also

limit the options available to developers in search of

interoperable solutions, thereby affecting the

proliferation and acceptance of dApps built on the

Aleo platform.

Aztec (Williamson, 2018), in contrast, operates as

a Layer 2 on Ethereum, bringing privacy features to

the Ethereum ecosystem. Through Aztec Connect,

private transfers of ERC-20 tokens and other

confidential operations are possible within the DeFi

space on Ethereum. While its programmability is

more limited than Aleo’s, Aztec offers valuable

privacy for DeFi dApps, effectively masking

transaction amounts and addresses. The solution uses

zk-rollups (Lavaur et al., 2023) to enhance scalability

by grouping multiple transactions into a single

proof.However, Aztec’s application scope is

relatively limited: while it supports DeFi protocols

and private payments. Additionally, developing

dApps on Aztec can be complex, as developers must

adapt their applications to align with Aztec’s privacy

protocols, requiring specific adjustments for

compatibility.

Mimblewimble (Silveira et al., 2024) is a

blockchain protocol focused on privacy and

scalability, proposed in 2016 by an anonymous

developer. Using advanced techniques such as

Pedersen commitments and confidential transactions

to mask transaction amounts and temporary

identifiers for involved parties, Mimblewimble

achieves a high degree of privacy. However, this

protocol has several significant limitations: it does not

support complex smart contracts, restricting its

applications to financial transactions only.

Additionally, its implementation is complex due to

the advanced cryptographic mechanisms it employs,

requiring specific validations and making integration

more challenging than with conventional blockchains.

Despite these limitations, Mimblewimble serves as

the foundation for several existing blockchains,

including Grin and Beam, which use it to enable

confidential and anonymous transactions, as well as

Litecoin, which has integrated it through the

Mimblewimble Extension Blocks (MWEB) for

enhanced privacy options. Table 1 presents a

comparative overview of existing approaches in

terms of privacy and programmability of blockchains

and protocols.

A Comparative Analysis of Cryptographic Techniques for Privacy Preservation in Blockchain-Based Dispute Resolution

1093

Table 2: Comparison of Existing Approaches in Terms of Privacy and Programmability.

Protocol/Blockchain Type Use Case Programmability

Zcash (van Saberhagen, 2013) Independent blockchain Financial transactions Non-programmable

Monero (Vijayakumaran,

2018)

Independent blockchain Financial transactions Non-programmable

Aleo (Bernabe et al., 2019) Independent blockchain Private transactions and dApps

Programmable

(via zkEVM)

Aztec (Silveira et al., 2024) Layer 2 on Ethereum Privacy for Ethereum transactions

Programmable

(via Aztec Connect)

Beam Independent blockchain Financial transactions Non-programmable

Grin Independent blockchain Financial transactions Non-programmable

Litecoin MWEB

Extension for existing

blockchain

Optional private transactions on Litecoin Non-programmable

A comparative overview of the discussed

protocols and blockchains is presented in Table 2,

highlighting key differences in types,use cases and

programmability.

4 DISCUSSION

The subsequent discussion expands upon the

examination of existing privacy-preserving

blockchain solutions and protocols, focusing on the

challenges and trade-offs that arise in relation to their

integration, scalability, and adherence to regulatory

requirements.

Balancing Privacy and Programmability: the

examined blockchains demonstrate diverse strategies

for incorporating privacy; however, a consistent

tradeoff becomes apparent: enhanced privacy

frequently restricts programmability, as illustrated by

Zcash and Monero. The expansion of private features

to accommodate more intricate applications, akin to

those facilitated by Aleo or Aztec, results in increased

computational expenses and integration challenges.

This situation prompts an inquiry into the ideal

equilibrium between flexibility and performance.

Building upon the trade-off between privacy and

programmability, the integration of zk-proof

algorithms into blockchain transactions introduces

another layer of complexity, as the choice of protocol

must balance performance, security, and verification

costs.

Feasibility of zk-Proof Algorithms for Blockchain

Integration: based on the technical characteristics of

each zk-Proof protocol as shown in the table 3,

integrating zero-knowledge proofs into blockchain

transactions requires a balance between performance,

verification costs, and security. For instance,

protocols with compact proof sizes and fast

verification times (such as Groth’16) are particularly

suitable for high-transaction throughput blockchains,

despite the constraints imposed by a trusted setup. On

the other hand, protocols without a trusted setup, such

as Bulletproofs and STARK, are preferable for

applications where security is paramount, although

they come with larger proof sizes and potentially

longer verification times. This technical evaluation

raises questions about the adaptability of each

algorithm depending on the specific constraints of

blockchains and use cases, guiding the choice of the

most suitable protocol for confidential and

programmable implementations while ensuring long-

term feasibility.

Scalability and Adoption within Existing

Ecosystems: solutions such as Aztec’s zk-rollups and

Aleo’s zkVM offer mechanisms for enhancing

privacy on existing blockchains; however, their

implementation necessitates considerable technical

modifications by developers, which can hinder swift

integration. A crucial consideration for the future is

whether these protocols can streamline their

operations while upholding privacy assurances,

thereby promoting broader adoption within

established networks such as Ethereum.

Interoperability and Standardization of Privacy

Technologies: the necessity for interoperability

among blockchains is becoming increasingly vital for

confidential decentralized applications (dApps), as

demonstrated by the challenges faced by initiatives

BEST 2025 - Special Session on Blockchain and Enhanced Security for a New Era of Trust

1094

such as Aleo. A major obstacle is the need to promote

standardized cryptographic methods to enable the

seamless migration of dApps across blockchains.

Achieving this interoperability could enhance the

adoption of privacy protocols and reduce ecosystem

fragmentation.

Resilience to Attacks and System Privacy

Durability: a key consideration is protocol resilience

to attacks, including Denial of Service (DoS) attacks.

The mechanisms presented in BaseSAP are designed

to enhance resilience; however, their long-term

effectiveness remains uncertain. Future research may

explore additional strategies to enhance the resilience

of privacy systems, ensuring their long-term viability

for end users.

Regulatory Considerations and Compliance

Strategies: privacy-focused blockchain solutions,

such as zk-SNARKs and confidential smart contracts,

encounter major regulatory hurdles. While these

technologies strengthen privacy protections, they

often clash with regulatory mandates such as

AntiMoney Laundering (AML) and Know Your

Customer (KYC) policies, as well as data protection

laws like the GDPR. The immutable nature of

blockchain systems conflicts with the GDPR’s right

to erasure provision, and privacy features may hinder

compliance with AML monitoring and verification

requirements.

Table 3: Comparison of Proof Size and Verification Time

for ZKP Algorithms.

Algorithm Proof Size Verification

Time

Groth’16 O(1) O(1)

Bulletproofs O(logN) O(N)

STARK O(poly-log(N)) O(poly-log(N))

5 RESEARCHDIRECTIONS

Advancements in privacy and programmability in

public blockchains open promising research

opportunities to address existing challenges and

improve decentralized solutions. We highlight key

research directions in this domain:

Optimization of Zero-Knowledge Proofs:

improving the efficiency of zk-SNARKs and

zkSTARKs is crucial for reducing computational

costs and verification times while strengthening

protocol security. These advancements are essential

for highthroughput blockchains and can significantly

enhance the usability of privacy-preserving solutions

for various blockchain applications.

Interoperability Between Blockchains: enhancing

the standardization and interoperability of privacy

technologies among different blockchains could drive

wider adoption and facilitate the seamless migration

of confidential decentralized applications (dApps)

across blockchain ecosystems. Exploring secure

bridging solutions and inter-chain communication

protocols is crucial for achieving this goal.

Strengthening the Resilience of Privacy Protocols:

defending against attacks, especially DoS attacks, is

a critical challenge for privacy protocols. Thorough

research is crucial to develop robust selfdefense

mechanisms and assess the long-term resilience of

privacy systems against emerging threats.

Expanding Programmability for Confidential

Applications: improving programmability in

privacy-focused blockchains, particularly in

executing complex smart contracts, remains a major

challenge. While frameworks such as Aleo and Aztec

provide a strong foundation, further research is

needed to balance privacy with application flexibility.

Developing Economically Viable Solutions: the

high cost of private transactions, mainly due to their

computational complexity, hinders widespread

adoption. Creating cost-effective and efficient

solutions could make private transactions more

accessible and encourage their adoption.

6 CONCLUSION

In summary, striking the right balance between

privacy and transparency is essential to fostering trust

in decentralized collaboration frameworks. As

cryptographic techniques continue to evolve, it is

possible to envision a future where secure, private,

and transparent transactions coexist on public

blockchains, thus laying the foundation for a resilient

and fair digital ecosystem.

The rise of digital collaboration has highlighted

the need for privacy-preserving mechanisms in public

blockchains, particularly as interactions in

decentralized systems become more widespread. This

study explores sophisticated cryptographic methods,

including stealth addresses and zk-SNARKs,

designed to enable untraceable and secure

transactions. Furthermore, it evaluates their existing

applications, limitations, and the challenges of

balancing transparency and privacy.

A Comparative Analysis of Cryptographic Techniques for Privacy Preservation in Blockchain-Based Dispute Resolution

1095

Public blockchains, despite advancements in

privacy measures, remain inherently transparent. To

address this challenge, it is essential to develop

advanced cryptographic techniques to enhance

anonymity without compromising security or

efficiency. To unlock the full potential of

decentralized collaboration, future research should

focus on optimizing privacy solutions to reduce

computational costs and enhance scalability.

Furthermore, achieving interoperability among

privacy-enhancing protocols across blockchain

ecosystems could empower users by enabling secure

cross-platform interactions.

Our forthcoming research will focus on exploring

approaches to enhance privacy-preserving solutions

and scalability while ensuring smooth

interoperability across blockchain ecosystems.

REFERENCES

Aleo (2024). Aleo record model: A secure and efficient

blockchain. Online. Available: https://aleo.org/post/

aleo-record-model-secureefficient-blockchain/.

Ben-Sasson, E., Chiesa, A., Garman, C., Green, M., Miers,

I., Tromer, E., and Virza, M. (2014). Zerocash:

Decentralized anonymous payments from bitcoin. In

Proceedings of the IEEE Symposium on Security

Privacy (Oakland), pages 459–474.

Bernabe, J. B., Canovas, J. L., Hernandez-Ramos, J. L.,

Moreno, R. T., and Skarmeta, A. (2019).

Privacypreserving solutions for blockchain: Review

and challenges. In IEEE Access, volume 7, pages

164908– 164940.

Fanti, G., Venkatakrishnan, S. B., Bakshi, S., Denby, B.,

Bhargava, S., Miller, A., and Viswanath, P. (2018).

Dandelion++: Lightweight cryptocurrency networking

with formal anonymity guarantees.

Feng, C., Tan, L., Xiao, H., Qi, X., Wen, Z., and Liu, Y.

(2021). Edksap: Efficient double-key stealth address

protocol in blockchain. In 2021 IEEE 20th

International Conference on Trust, Security and

Privacy in Computing and Communications

(TrustCom), pages 1196–1201.

Feng, C., Tan, L., Xiao, H., Yu, K., Qi, X., Wen, Z., and

Jiang, Y. (2020). Pdksap: Perfected double-key stealth

address protocol without temporary key leakage in

blockchain. In 2020 IEEE/CIC International

Conference on Communications in China (ICCC

Workshops), pages 151–155.

Lavaur, T., Detchart, J., Lacan, J., and Chanel, C. P. C.

(2023). Modular zk-rollup on-demand. Journal of

Network and Computer Applications, 217.

Liu, T., Zhang, Z., Zhang, Y., Hu, W., and Zhang, Y. (2024).

Ceno: Non-uniform, segment and parallel zero-

knowledge virtual machine. Cryptology ePrint Archive,

Paper 2024/387. Available: https://eprint.iacr.org/2024/

387.

Mayer, H. (2016). zk-snark explained: Basic principles.

CoinFabrik. Dec. 13.

Monero. About monero. Online. Available:

https://www.getmonero.org/fr/resources/about/.

Monero (2013). Stealth address. Online. Available:

Modular stealth address protocol for programmable

blockchains. IEEE Transactions on Information

Forensics and Security, 19:3539–3553.

Williamson, Z. J. (2018). The aztec protocol. AZTEC,

Version 1.0.1. https://www.getmonero.org/fr/

moneropedia/stealthaddress.html.

Noether, S. (2015). Ring signature confidential transactions

for monero. Cryptology ePrint Archive, Paper

2015/1098. Available: https://eprint.iacr.org/2015/1098.

Silveira, A., Betarte, G., Cristiá, M., and Luna, C. (2024). A

formal analysis of the mimblewimble cryptocurrency

protocol. Facultad de Ingeniería, Universidad de la

República, Montevideo, Uruguay.

Van Saberhagen, N. (2013). Cryptonote v 2.0. Online.

Available: https://web.archive.org/web/

20201028121818/.

Vijayakumaran, S. (2018). Monero ring signatures.

Wahrstätter, A., Solomon, M., DiFrancesco, B., Buterin, V.,

and Svetinovic, D. (2024). Basesap:

BEST 2025 - Special Session on Blockchain and Enhanced Security for a New Era of Trust

1096