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Received 11 October 2023, accepted 21 November 2023, date of publication 30 November 2023,
date of current version 8 December 2023.
Digital Object Identifier 10.1109/ACCESS.2023.3337806
Blockchain-Based Trust Management for Virtual
Entities in the Metaverse: A Model for Avatar
and Virtual Organization Interactions
KAMRAN AHMAD AWAN 1 , IKRAM UD DIN 1 , (Senior Member, IEEE),
AHMAD ALMOGREN 2 , (Senior Member, IEEE),
AND BYUNG SEO-KIM 3 , (Senior Member, IEEE)
1 Department of Information Technology, The University of Haripur, Haripur 22620, Pakistan
2 Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia
3 Department of Software and Communications Engineering, Hongik University, Sejong-si 30016, South Korea
Corresponding author: Byung Seo-Kim ([email protected])
This work was supported in part by the National Research Foundation (NRF), South Korea, through the Project BK21 FOUR; and in part
by King Saud University, Riyadh, Saudi Arabia, through the Researchers Supporting Project RSP2023R184.
ABSTRACT As blockchain technology and decentralized systems evolve, the security of these
infrastructures faces challenges from increasingly sophisticated threats. This research introduces a
methodology designed to strengthen the security parameters of distributed systems, with a specific focus
on its applicability within the Metaverse. Our probabilistic trust model dynamically allocates weights to
system nodes based on their observed behaviour and the reputation of associated entities. This mechanism
effectively counters a range of security threats, including the Sybil, Good/Bad mouthing, and On/Off
attacks. By integrating blockchain technology, we establish a robust trust foundation within the Metaverse,
ensuring enhanced security for digital interactions. To further combat deceptive activities and reduce
superfluous intermediaries, our model incorporates smart contracts. Beyond their transactional utility, these
contracts function as trust regulators for interactions among Metaverse avatars. Our trust model efficiently
differentiates various virtual entities, assigning trust scores that resonate with their specific classifications.
We also introduce a decentralized dispute resolution framework, where virtual entities act as impartial
arbiters, promoting transparency and fairness in conflict resolution. We have implemented our proposed
solution on real-time blockchain platform in comparison with the existing appraoches, i.e., BTCGS and
MSBC-CTrust. The evident enhancements in threat detection capabilities and the agility in neutralizing these
threats validate our model’s resilience and adaptability.
INDEX TERMS Metaverse, virtual environment, blockchain, trust management, virtual environment,
security, privacy preservation, reputation management, avatar trust.
I. INTRODUCTION
The rapid progression of the metaverse [1] brings to the
fore the critical concern of establishing and preserving trust
amongst its virtual entities, including avatars and virtual organizations [2], [3]. Traditional trust management strategies,
dependent on central bodies or third-party intermediaries, are
The associate editor coordinating the review of this manuscript and
approving it for publication was Deepak Mishra
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.
ill-suited to the decentralized nature of the metaverse [4],
highlighting the exigent need for a robust, decentralized
trust system resistant to cyber threats and ensuring transparency and accountability for all participants. Blockchain
technology, with its decentralized foundation and transparent
operational ethos, stands out as a viable solution to this
challenge [5]. However, employing blockchain for metaversal
trust management remains a nascent research area. The
transformative properties of blockchain and its decentralized
2023 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/
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K. A. Awan et al.: Blockchain-Based Trust Management for Virtual Entities in the Metaverse
networks, encompassing transparency, immutability, and the
elimination of intermediaries, have fundamentally reshaped
transactional and informational exchange paradigms. The
ethos of decentralization has spurred the development of
distributed applications and platforms, transferring control
from singular entities to node networks. Despite their advantages, decentralized systems confront security challenges,
with malicious entities continually attempting to exploit
vulnerabilities.
Recognizing the profound capabilities of distributed systems and blockchain, this paper aims to present measures to
strengthen their security profiles. Our primary focus lies in
exploring the potential of blockchain for trust management
within the metaverse and devising a trust management
framework for virtual entities. Within the metaverse, trust is
integral to facilitating user interactions and transactions with
other virtual entities. A deficiency in trust can hinder user
engagement and limit potential opportunities, particularly
in an environment devoid of physical interactions. As the
metaverse continues to mature, the need for decentralized
trust management for its virtual entities becomes increasingly
evident [6]. Conventional trust mechanisms, predicated on
intermediaries or central bodies, fall short in the metaversal
context due to their inherent centralization, heightened
costs, and attack vulnerabilities. Consequently, a transparent,
decentralized trust system is paramount for secure exchanges
between digital entities in the metaverse. The foundation
of social and economic metaversal interactions lies in trust
between avatars and virtual organizations. Implementing
distributed trust systems [7] for the metaverse demands a
transparent, decentralized approach, a pursuit fraught with
complexities. Blockchain, by maintaining immutable and
transparent records, presents an avenue to foster trust in
virtual spaces without the crutch of intermediaries or central
authorities [8].
With the advent of the metaverse, the necessity for a
robust trust management system becomes paramount. This
paper proposed a model that capitalizes on the intrinsic
qualities of blockchain technology, such as transparency
and immutability, to provide a trusted, secure, and decentralized trust management system for virtual entities. Our
model integrates smart contracts, reputation systems, and
a decentralized dispute resolution mechanism to foster a
secure environment for these entities. Trust ratings, assigned
to virtual entities, are adaptive, reflecting the ever-evolving
metaverse based on individual attributes and actions. Through
the utilization of smart contracts, encoded directly on the
blockchain, trust agreements between entities are automated,
ensuring authenticity, transparency, and mitigating intermediary intervention and potential fraud. The reputation system,
by providing accessible ratings of each entity, promotes
virtuous behavior, thereby enriching the metaversal community. Additionally, the model encompasses a decentralized
dispute resolution mechanism, ensuring equitable and transparent conflict resolution. Our contributions can be outlined
as:
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1) Utilization of blockchain technology tailored for trust
management in the metaverse, crafting a reliable
environment for virtual entities.
2) Adaptation of smart contracts to facilitate trust agreements, thereby eradicating intermediaries. Despite the
widespread application of smart contracts in various
blockchain systems, our model uniquely applies them
to manage trust amongst virtual entities in the metaverse.
3) Recognition of the diverse nature of metaverse entities,
allowing the system to discern between different entity
types and apportion trust levels accordingly.
4) Introduction of a decentralized dispute resolution feature, appointing select entities as arbitrators, ensuring a
transparent, decentralized conflict resolution process.
The remainder of this article is structured as follows:
Section II delineates related research. Section IV elucidates our methodology for countering specific attacks on
reputation-centric trust systems, such as the Good Mouthing
Attack, Bad Mouthing Attack, and Sybil Attack, using tools
like reputation-driven voting and trust metrics. Experimental
simulations are detailed in Section V. The concluding
remarks are presented in Section VIII.
II. RELATED WORK
The Metaverse represents a novel digital environment,
allowing users to immerse themselves in a myriad of
activities spanning gaming, social interactions, education,
and commerce. Its promise is undeniable, aiming to redefine
our engagement with digital platforms. Nevertheless, the
establishment of trust in the Metaverse is pivotal and has
garnered significant academic attention. A comprehensive
comparison of various research studies that delve into the
intersections of Blockchain and Metaverse technologies is
essential for understanding their contributions, limitations,
and potential future directions. Table 1 provides a detailed
comparative analysis of notable contributions in this domain,
elucidating their primary focus, inherent challenges, proposed future research trajectories, and key remarks.
Zhang et al. [9] delved into trust-building mechanisms,
assessing their influence on purchase intentions within
Metaverse shopping scenarios. Their findings posit a direct
positive correlation between trust and purchase intent.
Intriguingly, age emerged as a moderator, underscoring the
need for age-sensitive trust-building strategies. On a parallel
tangent, Ali et al. [10] advocated for the amalgamation
of Explainable AI and Blockchain within the Metaverse,
specifically for bolstering trust and ensuring data security in
healthcare applications. Their proposition centers on facilitating virtual interactions between patients and healthcare
providers, emphasizing the critical role of trust in healthcare
transformations through the Metaverse.
Sathya [11] accentuated the role of Blockchain technology,
presenting it as a cornerstone for Metaverse trust. The
research accentuates the indispensability of decentralized
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K. A. Awan et al.: Blockchain-Based Trust Management for Virtual Entities in the Metaverse
TABLE 1. Comparative analysis of blockchain and metaverse approaches.
trust paradigms, with Blockchain heralded as an instrument
for fostering such trust. Similarly, Lin et al. [12] introduced
a Blockchain-based trustworthy governance framework tailored for Metaverse production scenarios. Their methodology
seeks to enhance trustworthiness in Metaverse manufacturing
engagements, underscoring the centrality of trust in this
domain.
Adding to this narrative, Badruddoja et al. [13] championed the integration of Blockchain and Trusted AI, aiming
to amplify the Metaverse’s capabilities. Their blueprint is
anchored in fostering secure and credible interactions with
digital assets. Gai et al. [14] put forth a multi-signer lock
mechanism for user access controls in the Metaverse, built
upon Blockchain foundations. Their focus remains steadfast
on trust as a mechanism for bolstering Metaverse security and
privacy.
Broadening the scope to the Internet of Things
(IoT), Liu et al. [15] conducted an extensive survey
on Blockchain-mediated trust management. Their work
underlines the prospective synergy between Blockchain
and the enhancement of trust within IoT ecosystems.
Wu et al. [16] proposed a unique Primary-Secondary
Blockchain architecture equipped with a cross-domain trust
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ticket. Their architectural design aspires to manage trust
across disparate domains within the Metaverse, emphasizing
trust’s role in safeguarding cross-domain transactions. Lastly,
Manoj et al. [17] proposed a secure framework for IoT data
sharing, integrating oracle-based access controls tailored for
agricultural risk management. Their solution endeavors to
preserve the integrity and confidentiality of agricultural data
within the Metaverse, highlighting trust as an instrumental
factor in Metaverse-driven agricultural endeavors.
III. BLOCKCHAIN AND TRUST MANAGEMENT IN THE
CONTEXT OF THE METAVERSE
The Metaverse, an expansive and decentralized virtual shared
space, has rapidly emerged as a nexus of technological
evolution, encapsulating advancements in virtual reality,
blockchain, and decentralized systems. Ensuring trust within
this boundless digital realm becomes pivotal. While trust
management in decentralized systems has been extensively
studied, its intricacies within the Metaverse remain relatively
uncharted. Moreover, the synergy between blockchain and
trust management presents a promising solution. This section
delves into a comprehensive review of recent works that touch
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K. A. Awan et al.: Blockchain-Based Trust Management for Virtual Entities in the Metaverse
TABLE 2. Comparison of referenced articles concerning trust and security
mechanisms in the context of the Metaverse.
upon these themes, seeking to understand their relevance and
potential limitations in the context of the Metaverse.
Ali et al. [10] present an intricate fusion of the Metaverse
with healthcare, emphasizing the importance of trust. Their
work brings forth the healthcare domain as a testament
to the potential applications of the Metaverse beyond
gaming and social interaction. As healthcare data is critically
sensitive, the integration of explainable AI and blockchain
is proposed to ensure data security and enhance trust. The
research underscores a pivotal aspect: trust is not just about
transactions or interactions but also about understanding and
explaining processes to users, especially in domains where
stakes are high, such as medical decision-making. However,
while the paper beautifully stitches the narrative of Metaverse
in healthcare, it focuses more on a theoretical synthesis,
with less emphasis on the practical challenges that might
arise in deploying blockchain-based trust mechanisms in a
healthcare-centric Metaverse.
Xu et al. [18] venture into the realm of designing a
blockchain-enabled Metaverse that operates on trustless
principles. The term ‘trustless’ in blockchain parlance refers
to the notion that interactions occur without participants
needing to trust each other, thanks to the immutable and
transparent nature of blockchain transactions. The authors
meticulously unravel the layers of how trustless operations
can be seamlessly integrated into a Metaverse. However,
one might argue that the Metaverse, by its inherent design
and purpose, is more than just transactions. The emotional,
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social, and experiential aspects of user interactions might
demand a more nuanced approach to trust than what a
purely trustless architecture can offer. The approach of
Moudoud and Cherkaoui [19] stands as an emblem of the
potential amalgamation of advanced learning techniques
with blockchain for the Metaverse. By integrating multitasking federated learning with blockchain, they envision a
Metaverse where trust and security are fostered organically.
Their approach hints at the adaptability of decentralized
systems, where learning from data can potentially enhance
the trustworthiness of interactions. However, the Metaverse’s
dynamic nature might pose challenges in ensuring that federated learning models are always up-to-date and reflective of
the continuously evolving trust dynamics.
Corne et al. [20] offer an intriguing perspective on the
marriage of blockchain technology with the tourism sector
and further its implications for the Metaverse. The paper
underlines the crucial determinants for adopting blockchain
in tourism and extrapolates this to envision Metaversal
applications. By bridging the physicality of tourism with the
digital expanse of the Metaverse, this study offers a unique
lens. However, one might question the direct applicability
of determinants from a sector as tangible as tourism to the
fluid, dynamic Metaverse, which operates on a spectrum
of different interactional paradigms. Mourtzis et al. [21]
delve deep into the possibilities of blockchain technology
in an industrial setting within the Metaverse. As industries
pivot towards this new-age digital ecosystem, the importance
of secure, transparent, and tamper-proof systems increases
manifold. Their paper highlights the paradigm shifts in
industrial processes due to the blockchain’s introduction.
Yet, the challenges of scaling, interoperability, and real-time
synchronization in an industrial Metaverse context need
further exploration.
The approach by Islam and Tan [22] zeroes in on the
burgeoning domain of digital assets within a Web 3 based
Metaverse. The inherent value and transferability of digital
assets necessitate a trust mechanism. Their insights into
how blockchain can underpin these trust requirements are
enlightening. However, while the paper accentuates the
transactional aspect of trust, it might benefit from addressing
the experiential facets of trust interactions within a diverse
Metaversal community. Rajawat et al. [23] tackle the twin
challenges of security and scalability in the Metaverse using
blockchain-based consensus mechanisms. By ensuring that
all nodes in the network agree upon the truthfulness of
transactions, the paper posits an enhanced security posture.
The dynamic and expansive nature of the Metaverse might
necessitate an adaptive consensus approach that the paper
could further explore.
Ren et al.’s [24] work on HCNCT provides an architectural
foundation for a blockchain-based Metaverse. By introducing
a cross-chain interaction scheme, the paper addresses some
critical challenges regarding interoperability between different blockchain networks. This endeavor paves the way for a
unified, cohesive Metaverse. However, practical challenges
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K. A. Awan et al.: Blockchain-Based Trust Management for Virtual Entities in the Metaverse
in terms of transaction latency and chain synchronization
might emerge as potential bottlenecks. TMETA, as proposed
by Wang et al. [25], champions trust management for IoT
services using a digital twin aided blockchain mechanism.
The paper’s approach of simulating physical IoT entities
in the digital space and managing trust dynamics can be
revolutionary. But the Metaverse, with its vast array of
interactions, might demand an even more intricate trust
fabric, expanding beyond the IoT-centric viewpoint.
IV. PROPOSED METHODOLOGY
This section introduces the proposed methodology for a
blockchain-anchored trust management system tailored for
the metaverse. The emphasis is on creating a steadfast
platform enabling secure interactions for virtual entities.
The methodology integrates smart contracts to streamline
trust agreements and eliminates intermediaries. A diversified
trust model is introduced, accounting for the varied nature
of virtual entities, supplemented by a decentralized dispute
resolution system. A salient feature of our approach is
the management of Avatar Trust and Reputation. In the
metaverse, avatars function as the primary interface, influencing interaction quality based on their trustworthiness. The
proposed model assigns trust ratings to avatars based on historical behaviour and peer evaluations. This trust is quantified
through Reputation Management, which periodically reviews
an avatar’s actions. Positive behaviours bolster reputation,
while negative actions detrimentally affect it. The combined
effects of Avatar Trust and Reputation Management amplify
the security and trustworthiness within the metaverse.
In decentralized systems, particularly those intrinsic to
the Metaverse, entities and their interactions inherently
exhibit characteristics of variability and uncertainty. This
unpredictable nature of behaviors calls for a trust model
that does not merely rely on deterministic, fixed parameters.
Instead, a more nuanced approach is needed, one that can
adapt to the fluidity of such environments. The proposed
dynamic, probabilistic network-oriented trust model has
been formulated with these considerations at its core.
Traditional deterministic models for trust evaluation, which
are grounded on fixed variables and static conditions, often
struggle to accurately represent or predict behaviors in the
Metaverse. Such models might be effective in environments
where behaviors are consistent and predictable, but they
become less reliable when applied to the unpredictable
Metaverse ecosystem. The core of the proposed trust model
embraces a probabilistic approach, allowing for an adaptive
representation of trust that takes into account the uncertainties
associated with each node’s behavior. By doing so, the model
becomes more resilient and adaptive, ensuring that trust
evaluations are timely and reflective of the current state of
the network, rather than being rooted in historical or static
data. Furthermore, by being network-oriented, the model
recognizes the interdependencies and relational dynamics
between nodes, thereby providing a more comprehensive and
holistic view of trust in the system.
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Historically, trust models in decentralized systems relied
on fixed weight allocation mechanisms, predominantly based
on past interactions and static attributes. Such approaches,
while effective in relatively consistent environments, exhibit
limitations when confronted with the dynamic nature and
evolving threats present within the Metaverse. These traditional mechanisms often struggle to promptly adapt to abrupt
behavioral changes or recognize the significance of external
affiliations in trust evaluation. The inherent dynamism and
complexity of the Metaverse demand a more adaptable trust
assessment mechanism. Our model’s distinct approach to
weight allocation is rooted in two primary considerations:
real-time behavior of nodes and the reputation of affiliated
entities.
• Behavior-based Weight Allocation: By dynamically
adjusting weights according to the recent behaviors
of nodes, our model maintains a timely and accurate
representation of each node’s trustworthiness. This
ensures that sudden deviations from expected behavior
patterns, even from historically reliable nodes, do not go
unnoticed or unaddressed.
• Incorporating Affiliated Entity Reputation: An
entity’s reputation within its affiliated group or
organization can provide crucial context to its behaviors
within the broader network. By integrating this affiliated
reputation into the weight allocation process, the
model can achieve a more nuanced and comprehensive
trust assessment, effectively bridging the gap between
individual node behaviors and larger organizational
dynamics.
To elucidate the advantage of our approach, consider
the following scenario: Suppose a node, which has consistently demonstrated reliability in past interactions, suddenly
exhibits anomalous behaviors. Traditional weight allocation
mechanisms, grounded in historical data, might fail to detect
or adequately respond to this behavioral shift. In contrast,
our proposed model, with its dynamic weight adjustments
factoring in both current behavior and the reputation of the
affiliated entity, is primed to detect such anomalies and take
appropriate, timely measures to address potential threats.
A. ARCHITECTURAL FRAMEWORK OF PROPOSED
METHODOLOGY
The methodology harnesses blockchain to architect a
trust-centric environment for the metaverse’s virtual entities.
Key components of the architectural framework are depicted
in Figure 1.
1) Blockchain-based Trust Management: The system
deploys a blockchain network to underpin the trust
management framework. Trust-related records, encompassing ratings, agreements, and dispute resolutions,
are preserved indelibly on the blockchain, fortifying
transaction transparency.
2) Automated Trust Agreements and Intermediary Removal: Trust agreements in the metaverse
are automated through smart contracts, eliminating
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K. A. Awan et al.: Blockchain-Based Trust Management for Virtual Entities in the Metaverse
intermediary intervention, reducing fraud potential and
bolstering system efficiency.
3) Heterogeneous Trust Model: The proposed model
mirrors the multifaceted nature of metaverse’s virtual
entities. It discriminates between entities based on
inherent attributes and behaviours, allocating trust
ratings appropriately.
4) Decentralized Dispute Resolution Mechanism: The
system integrates a decentralized approach to dispute
redress. A designated cohort of virtual entities functions as arbitrators, ensuring resolutions are fair and
devoid of centralized bias.
TABLE 3. Summary of notations and their implications in the proposed
model.
B. BLOCKCHAIN-ORIENTED TRUST MANAGEMENT
The metaverse’s flourishing ecosystem relies heavily on
the ability to foster trustworthy interactions. Trust, in this
context, serves as the bedrock of the engagements between
the metaverse’s virtual entities. In this study, we propose a
methodology that leverages the functionalities of blockchain
technology to architect a sophisticated trust management
system, thereby fostering a secure environment for reliable interactions among the metaverse’s virtual entities.
Specifically, our methodology automates trust agreements
via smart contracts, which aids in mitigating the potential
for fraudulent transactions and eliminates the need for
intermediaries. Inherent to our methodology is a trust model
that is attuned to the diverse nature of virtual entities within
the metaverse, categorizing disparate types of virtual entities
and assigning trust levels corresponding to their behaviors
and characteristics. To elucidate the mathematical framework
employed in our study, we have systematically cataloged
and detailed the notations integral to our proposed model.
As delineated in Table 3, each notation embodies a specific
parameter, its mathematical relevance, and the associated
implications within the context of our research.
The process of the proposed blockchain-oriented trust
management is delineated in Algorithm 1. The primary input
parameters of this algorithm include a list of virtual entities
V , the corresponding trust features F, feedback f , weights w,
and the state of the blockchain at time t − 1, Bt−1 . The output
of this algorithm is the overall trust value Tt for the virtual
entities at time t.
At the beginning, we initialize P0 and B0 as the initial
trust parameter values and the initial state of the blockchain,
respectively. The algorithm proceeds by iterating through
each virtual entity v in the list of virtual entities V . For
each virtual entity, the set of features Cv characterizing its
interaction with other virtual entities is computed. Following
this, the trust value Tv for each virtual entity is computed by
summing over the product of the weight wk and the function
fk applied to the set of features Cv , for each feature k. Once
the trust values Tv for all virtual entities have been calculated,
the algorithm proceeds to compute Pt . The computation
of Pt involves hashing the previous trust parameters Pt−1 ,
concatenated with the identity of each virtual entity vi and
their corresponding trust value Tvi .
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Algorithm 1 Blockchain-Oriented Trust Management
Input: List of virtual entities V , trust features F,
feedback f , weights w, state of the blockchain
at t − 1, Bt−1
Output: Overall trust value Tt
1 P0 ← initial trust parameter values; B0 ← initial state
of the blockchain;
2 foreach v ∈ V do
3
Cv ← set of features that characterize the
interaction
P of v with other virtual entities;
Tv ← nk=1 wk fk (Cv );
4 end
5 Pt ← H (Pt1 ||v1 ||Tv1 || . . . ||vN ||TvN );
6 Bt ← addb lock(Bt−1 , Pt ); Tt ← H (Pt ||Bt );
7 return Tt ;
The next step is the addition of a new block to the
blockchain. The function addb lock takes in the state of the
blockchain at t − 1 and the newly computed trust parameters
Pt and returns the updated state of the blockchain Bt . Finally,
the overall trust value Tt is computed by hashing the current
trust parameters Pt and the current state of the blockchain Bt .
This provides an additional layer of security and ensures the
integrity of the trust computations. The algorithm terminates
by returning the overall trust value Tt , providing a comprehensive, trustworthy, and blockchain-based mechanism
for managing interactions between virtual entities in the
metaverse.
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K. A. Awan et al.: Blockchain-Based Trust Management for Virtual Entities in the Metaverse
FIGURE 1. Architectural framework of the blockchain aided trust management system.
In order to ensure the integrity of trust computations,
our methodology employs a composite hashing mechanism
that combines the robust features of SHA-256 and SHA-3
algorithms to hash trust parameters. Let us denote the trust
value assigned by a specific virtual entity i to another virtual
entity j as Ti,j . This value is calculated using the equation:
Ti,j =
n
X
wk fk (Ci,j )
(1)
k=1
In Equation 1, wk signifies the weight attributed to the
k th feature, while fk designates the function that maps the
feature to a trust score. Ci,j refers to the set of features
that characterizes the interaction between the virtual entities
i and j. This encompasses factors such as reputation,
behaviour, historical interactions, and performance. The trust
values computed via this process are subsequently stored
on the blockchain through the use of smart contracts.
These autonomous programs, executed by the nodes of
the blockchain network, enforce the trust agreement terms
between virtual entities, thereby ensuring transparency and
immutability of the trust values.
Our methodology incorporates a distinctive hashing mechanism to further reinforce the integrity of trust computations.
This mechanism marries the advantages of the SHA-256
and SHA-3 algorithms for hashing trust parameters. Let
us represent a secure hashing function that maps an input
x to a fixed-length output as H (x). Our methodology
introduces an advanced hashing algorithm custom-built for
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trust computations within the metaverse. This mechanism
hashes the current state of the blockchain along with trust
parameters, as represented by the following equation:
Pt = H (Pt−1 ||pi ||wi ||fi )
(2)
In Equation 2, Pt represents the hash of trust parameters
at time t, Pt−1 denotes the hash of trust parameters at time
t − 1, pi signifies the identity of the i-th virtual entity, wi
indicates the weight associated with the i-th virtual entity,
and fi designates the feedback received from the i-th virtual
entity. The state of the blockchain is hashed according to the
equation:
Bt = H (Bt−1 ||bt )
(3)
In Equation 3, Bt represents the hash of the current state of
the blockchain at time t, Bt−1 denotes the hash of the current
state of the blockchain at time t − 1, and bt signifies the
new block added to the blockchain at time t. The hash of the
overall trust computation at time t is derived by combining
the hashes of the trust parameters and the current state of the
blockchain:
Tt = H (Pt ||Bt )
(4)
In Equation 4, Tt represents the hash of the overall trust
computation at time t. This arrangement ensures that any
changes made to the trust parameters or the state of the
blockchain result in a change in the hash value for the overall
trust computation, thereby fortifying the system’s security
and integrity.
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C. TRUST AGREEMENT AUTOMATION AND
INTERMEDIARY SUPPRESSION
Towards the goal of constructing a robust trust management framework for metaverse inhabitants, we advocate
an approach grounded in the automation of trust accords
and the suppression of middlemen. Capitalizing on the
power of smart contracts, our design streamlines trust
negotiations between virtual avatars, symbolized as Vi ,
and organizations, denoted as Oj , thereby curtailing the
necessity for intermediaries. This subsequently mitigates the
likelihood of fraudulent conduct and maladministration. A
schematic representation of this mechanism can be observed
in Algorithm 2. The Algorithm encapsulates the intricate
process of automated trust agreement formulation and intermediary removal, grounded in the dynamics between virtual
avatars and organizations in the Metaverse. The fundamental
premise of the algorithm is to streamline interactions based
on trust assessments, optimizing the interaction processes
and negating the necessity for intermediaries whenever
feasible. During the initialization phase, key parameters such
as the minimum (Trustmin ) and maximum (Trustmax ) trust
thresholds, and avata
