A Real‑Time, Standards‑Aligned Integration of Blockchain and Zero

Trust Architecture for Threat Detection and Data Integrity in

Distributed IT Systems

Gaurav Pandey

, Abhay Shukla

, S. Saroja Devi

, K. Parthiban

, G. Dharunkumar

and A. Swathi

Department of Applied Science, FET, Rama University, Kanpur‑208024, Uttar Pradesh, India

Department of Computer Science and Engineering, FET, Rama University, Kanpur, Uttar Pradesh, India

Department of Information Technology, J.J. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India

Department of Management Studies, Nandha Engineering College, Vaikkalmedu, Erode 638052, Tamil Nadu, India

Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad‑500043, Telangana, India

Keywords: Blockchain Security, Zero Trust Architecture, Real‑Time Threat Detection, Data Integrity, Cybersecurity

Framework.

Abstract: In a time of advanced cyberthreats and mission critical data, traditional security architectures are not enough

to safeguard the dynamic IT environments. The present work presents an innovative hybrid of Blockchain

technology and Zero Trust Architecture (ZTA) as a united, dynamic security model for distributed enterprise

systems. Unlike existing models that are theoretical models or are non-interoperable, the proposed work

provides a practical model based on industry standards such as NIST ZTA prescriptions and HLP protocols.

Blockchain provides unforgeable, decentralized access control and auditability whereas Zero Trust imposes

identity-based, constant verification on every endpoint. It includes a threat detection module that uses machine

learning for greater responsiveness and precision. The system is evaluated with simulated enterprise

environments and realistic cybersecurity datasets, and is shown to enable real-time intrusion detection whilst

ensuring end-to-end data integrity. This fulfills the void between theory and implementation, and provides a

standard based, extensible, model aligned with the dynamic digital threat landscape. injection of BALB/c

mice with NTs as a prophylactic strategy to further investigate the potency of immune responses.

1 INTRODUCTION

The swift digitization of world industries and the

increasingly decentralized nature of IT infrastructures

is changing cybersecurity in a fundamental way.

Traditional outside-in security models, which once

formed the basis for enterprise protection, are

woefully outdated in the face of contemporary

threats. Existing models fall short in mitigating new

types of attack used by cyber adversaries, which

leverage lateral movement, stolen credentials, and

insider threats as a means to evade static solutions. In

reaction, the landscape of cybersecurity is evolving

towards more flexible and robust structures such as

the Zero Trust Architecture (ZTA) and blockchain

technology.

Zero Trust Architecture, based on the principle of

"never trust, always verify," questions the notion of

trust-at-will inside network boundaries. This requires

persistent authentication, rigid access controls, and

vigilant monitoring of user and device behavior.

Although ZTA brings much benefit for both threat

containment and access evidences, it does not have

the built-in features of tamper-proof auditability or

distributed consensus. This is where blockchain

technology offers a very interesting supplement.

Leveraging the technology capabilities of blockchain

for distributed ledger capability and

cryptographically secure integrity, an organization

could implement transparent, trustable systems where

access decisions and security events are permanently

recorded and tamper-proof.

Despite the strengths that blockchain and ZTA

bring individually, there is significant a research and

implementation gap at the intersection of these two

technologies in practical systems. Most of the

previous works often consider them separately or

Pandey, G., Shukla, A., Devi, S. S., Parthiban, K., Dharunkumar, G. and Swathi, A.

A Real-Time, Standards-Aligned Integration of Blockchain and Zero Trust Architecture for Threat Detection and Data Integrity in Distributed IT Systems.

DOI: 10.5220/0013859300004919

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

In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies (ICRDICCT‘25 2025) - Volume 1, pages

145-150

ISBN: 978-989-758-777-1

145

theoretically, but without comprehensive

combination and practical validation. Second, a

majority of models do not consider the urgency of

real-time malware threat detection and response,

which is a non-negotiable imperative in the current

threat landscape in which the velocity of attack

frequently exceeds the velocity of detection.

This gap is addressed in this work by crafting and

deploying integrated cybersecurity architecture

combining blockchain and Zero Trust in a single

solution and best fit for real-time threat identification

and data integrity. The proposed model follows not

only some of the most recognized industrial standards

like NIST Zero Trust model, but in addition it

integrates machine learning driven analytics and

blockchain-based access control for the most

complete, scalable, and secure IT ecosystem. We

hope this work will serve as a solid building block to

help future-proof enterprise security in light of

advancing cyber threats and data-based operations.

2 PROBLEM STATEMENT

Enterprise IT security is continually challenged by

increa-sing complexities and interdependencies

between digital infrastructures. Classic security

approaches, such as perimeter-based protection and

trust by default, are not enough to address

sophisticated adversaries using advanced persistent

threats (APTs), insider attacks, or unauthorized east-

west traffic within your network. And while Zero

Trust Architecture (ZTA) has become the new

buzzword with its emphasis on continuous

verification and least access, it provides neither the

permanence nor the process auditability necessary for

high assurance. On the other hand, blockchain

technology enables decentralized trust and tamper-

proof storage of data base while without proper

contextual, rule-based enforcement mechanisms

required for dynamic access control and threat

detection. In addition, research today often looks at

the two separately with just complete solution

presented and the needs of the entire network

security (specifically timing of threats being

identified in real time and integrity of entire data

path). This fragmented tactical strategy exposes

enterprise systems to attacks that can take advantage

of detection and trust blindspots and loss of control.

We urgently need a unified solution that encompasses

not only blockchain and Zero Trust but also provides

for proactive, intelligent response capabilities in real

time and continues to be compliant with industry

norms.

3 LITERATURE SURVEY

The convergence of Zero Trust Architecture (ZTA)

and blockchain has become an emerging research

topic in cybersecurity which is akin to a trend to

secure geographically distributed IT infrastructures

from attacks that are becoming more and more

sophisticated. Mounting Evidence: Blockchain Can

Increase Data Integrity and Trust in a Decentralized

World Several papers have separately shown the

promise that blockchain holds for increasing data

integrity and trust in a decentralized environment. For

example, Wang and Li (2022) apply blockchain to

provide immutable audit trails in edge computing,

and Pokhrel at al. (2024) applied this to privacy

aware industrial systems. Meng and Li (2022) present

a decentralized data integrity mechanism and

illustrate the strength of blockchain in combating

tampering in a distributed range system.

At the same time, the idea of Zero Trust has risen

as a post-perimeter security framework. Alevizos et

al. (2021) and Chaudhry et al. (2023) proposed

frameworks with a strong verification of identity and

a permanent track on worker s performance. These

works are in accordance with the guidelines

suggested by NIST yet provide no integration to the

supportive technologies to realise these principles in

a decentralized or cloud-native environment. Liu and

Wang (2022) proposes a blockchain-based

methodology of access control in multi-cloud and

comments on the synergism direction, the approach,

however, is theoretical and is unable to realize real-

time detection.

Some other work has tried to mix blockchain and

ZTA’s ideas. Ali and Khan (2023) introduce a

convergence architecture for cyber-physical systems,

and Lin and He (2021) cover access control in

industrial IoT, where blockchain could be utilized to

apply Zero Trust principles. Nevertheless, these

works are usually limited to specific domains like IoT

or healthcare, such as Alharbi and Hussain (2023)

and Din et al. (2024), thereby restricting their

applicability to more general IT systems.

Furthermore, several works do not fully evaluate their

approaches in real-environments, as we found

simulation or conceptual modeling were used, e.g.

within Hassan et al. (2021) and Ahmed et al. (2023).

Bot traffic detection in real time is an

underserved area in this space. Lin and Wang (2022)

and Yousaf et al. (2022) consider intrusion detection

systems in the Zero Trust model and blockchain, but

do not examine its integration with intelligent,

automated responses. The realization of real-time

analytics is also accordant with Gao and Liu (2021)

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that it is highly desirable for AI-based detection in

blockchain. But there is little empirical evidence in

support of it. Li and Chen (2022) and Zhao and Zhang

(2023) are stepping toward anomaly detection from a

decentralized perspective but its system architectural

harmony with ZTA is missing.

Ali et al mention machine learning for predictive

threat detection in Zero Trust blockchain architecture.

(2023) and Singh and Sharma (2024), but are still in

the stage of concept. Likewise, researches carried out

by Chaudhary and Tyagi (2022) and Raj and co-

workers (2023) introduce blockchain in order to

provide transparency and accountability and fail to

address the dynamic access and risk scoring

characteristic of Zero Trust. In addition, there are

few references directly referencing the prevalent

standards such as NIST ZTA or blockchain systems

with enterprise capabilities like Hyperledger, which

was commented by Wang et al. (2023) and supported

by Abbas and Raza (2024).

Altogether, these pieces constitute a fragmentary

but promising corpus of material. Although each of

these works is valuable, the absence of the end-to-

end cooperative, standards-based, and real-time-

enabled systems based on blockchain and ZTA covers

a major gap in the literature. This paper addresses this

gap members: by proposing and implementing an

end-to-end architecture that integrates Zero Trust

and blockchain, and that leverages AI in the context

of threat detection, that validates the approach using

large-scale, realistic enterprise data alongside usage

scenarios for cybersecurity.

4 METHODOLOGY

To this end, this research uses design-science

approach to architecture Modeling, deploying of a

prototype and performance testing of security

solutions to develop and test a unified cyber secure

framework that fuse the BlcokChain and the Zero

Trust Architecture (ZTA). The procedural

development is cyclic and composed of the

following four main steps: system design, system

implementation, data set integration, and evaluation.

The design of the system should start by

conceptualizing an integrated architecture that brings

Zero Trust principles like least privilege access,

micro-segmentation and continuous authentication

with Blockchain abilities to support decentralization,

data immutability and trustless consensus. The

architecture closely relates to NIST Zero Trust

reference model, and includes blockchain

components with the Hyperledger Fabric since it

allows for a modular architectural framework and an

enterprise-ready support for smart contracts and

permissioned ledgers.

Implementation is done by layering model. At

its core, blockchain is employed to generate secure,

tamper-proof records of access events, identity

verification, and policy updates. Smart contracts are

created to dynamically apply access control rules

using context-aware information like user roles,

behavior analytics and up-to-date threat intelligence.

The ZTA layer consists of identity providers, policy

engines, and enforcement points which consult the

blockchain for decision making as well as as logs.

There is also a machine learning module which

monitors system logs, user behaviors and network

traffic to identify anomalies and advanced real-time

intrusions. The model employs open-source

cybersecurity datasets as the prototypes (CIC-

IDS2018 and UNSW-NB15) and supervised

learning methods to guarantee real-time threat

detection at high accuracy.

To simulate a real enterprise environment, the

framework is running in a virtualized networking

system using Docker and Kubernetes. Simulated

user functions, endpoints, services, and threat vectors

make up this environment which allows for controlled

experimentation. Integration tests are used to test the

interoperation between the blockchain and ZTA

components, and stress testing examines system

performance with large amounts of transactions and

exposed access.

The performance metrics include accuracy of

detection, response time, throughput, and resource

usage. Comparison with traditional security

architectures and stand-alone block-chain or ZTA

solution is performed and the effectiveness and

resilience of the proposed approach is illustrated. The

results are evaluated quantitatively and qualitatively

for the capability of the system to detect security

threats in real time and to preserve data integrity in a

distributed IT environment.

This methodological approach ensures

vulnerability research does not only contribute a

conceptual innovation but provides a practically

feasible and empirically grounded cyber security

solution, customized for today's enterprise systems.

Figure 1 show the Workflow of the integrated Zero

Trust and Blockchain-based architecture for real-time

threat detection and secure access control.

A Real-Time, Standards-Aligned Integration of Blockchain and Zero Trust Architecture for Threat Detection and Data Integrity in

Distributed IT Systems

147

Figure 1: Workflow of the Integrated Zero Trust and

Blockchain-Based Architecture for Real-Time Threat

Detection and Secure Access Control.

5 RESULTS AND DISCUSSION

The development and evaluation of the presented

integrated framework led to promising results in

increasing the cybersecurity posture by combining

the use of blockchain and Zero Trust pomises. The

system was validated in a controlled emulation of an

enterprise system using enterprise virtualization

software under a variety of threat vectors and access

styles to simulate real-world network experiences.

The test platform made it possible to monitor the

responsiveness, dependability and flexibility of the

framework when dealing with access control and

threats detection in real time.

Its improved speed and accuracy of threat

detection was one of the most notable results. The

trained machine learning module based on CIC-

IDS2018 and UNSW-NB15 datasets reached a

detection accuracy of 96% albeit showing a better

performance against the baseline models with no

blockchain logging and Zero Trust access filtering.

And most importantly, the system showed low

detection-to-response latency (i.e., <300 ms on

average), which distinguished the proposed system

from the competition with ability of preventing rather

than reacting to threat actions. The results further

prove that combining AI-powered analytics in a Zero

Trust setting, supported by the immutable event

logging from blockchain, results in a more intelligent,

accountable security posture.

Figure 2: Performance Comparison of Threat Detection

Models Used in the Proposed Framework.

The underlying blockchain was used to great

effect to ensure data had not been tampered with and

to create an immutable trail of evidence. Each access

request, policy assault and threat event was logged

into an immutable ledger, to help with forensic

analysis and compliance audits. This feature not only

improved transparency, but also prevented insider

attacks since it was impossible to tamper with log

data, known to be a weak point in centralized systems.

Moreover, smart contracts for policy enforcement

rendered unnecessary centralised enforcement points,

mitigating single points of failure. Figure 2 show the

Performance comparison of threat detection models

used in the proposed framework.

System cross-compatability and robustness under

stress were also tested. Even though the blockchain

operations are inherently slow, we used techniques

like off-chain storage for non-critical data and

asynchronous consensus for audit logs to still give a

minimum impact on the system performance. The

system achieved stable throughput and low overhead

even in the presence of large numbers of access and

transaction requests, indicating practical scalability in

deployment.

Not only did these combined Zero Trust and

blockchain solutions fulfill their respective functions

of access approval and data integrity, but they were

also found to realize a deep synergy. For example,

Identity validation in ZTA was maintained on an

ongoing basis, and contextual data were delivered to

smart contracts while blockchain made ZTA more

visible and robust. This bi-directional reinforcement

allowed the dynamic trust boundary to be maintained

and helped in correlating the real-time user behaviour

with network anomalies.

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But, yes, there are some limitations to consider in

this analysis. The framework did provide good results

in the controlled settings, but blockchain scalability,

the complexity of smart contracts, and real-time

analytics in large scale systems are several open

issues for future improvements. Moreover, the

regulatory issues of blockchain privacy and

jurisdiction should be considered for broader

adoption in regulated sectors.

In summary, the results of the experiment prove

the practical potential of an integrated Zero Trust–

Blockchain framework to secure enterprise IT

systems from contemporary computer threats.

Beyond these immediate implications for real-time

security threats and response, the combination

supports ongoing trust, resilience and auditability that

provides for future building blocks of security for an

ever more distributed and data rich digital economy.

6 CONCLUSIONS

With the digital world becoming more hostile and

sophisticated, there is a clear need to stow not to

traditional security mindsets, but to more dynamic

and intelligent ones that effectively add a stronger

level of trust. In this work, we have proposed a new

hybrid framework of combining the Blockchain and

Zero Trust Architecture that can answer the critical

requirements of real-time threatening detection, data

integrity and the least trusts establishment in

enterprise systems. By combining the long-term,

decentralized assurance of blockchain with the short-

term, identify-focused, adaptive security policies of

ZTA, the described architecture provides a complete

security line of battle that is proactive and transparent.

The results of this research work show that the

integration of these two technologies leads to a

mutually supporting universe: the blockchain

enforces and confirms the access control decision,

while the Zero Trust policy improves and guides the

use of smart contract and audit trial. By integrating

ML-powered analytics, the system is even more

robust, as it allows for the ability to predictively

detect threats and rapidly respond to an issue,

shortening the gap between threat alert and threat

removal.

In addition to providing a new set of technical

contributions, this work further promotes Zero Trust

and blockchain deployment becoming practical

reality, as it complies with the real-world standards

like NIST ZTA, and potentially being deployed on

enterprise-scale platforms like Hyperledger Fabric.

This guarantees both theoretical novelty and practical

applicability in the contemporary enterprise

environments.

However, this study also recognizes some

limitations including the performance of blockchain

and integrating real-time analytics at scale

complexity. Such challenges accentuate potential

future directions for investigation even further, such

as lightweight blockchain protocols integration,

federated learning for decentralized threat detection,

or cross domain policy harmonization.

In short, the integrated system proposed in this

research presents a robust, scalable and intelligent

solution for enterprise cybersecurity. It provides a

blueprint and jumpstart to research and

implementation work that makes the concepts of Zero

Trust and the benefits of blockchain to security a set

of convergent principles and technologies rather than

duelling ones.

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