<p>Information and Communication Technology (ICT) has significantly transformed the defense sector, enhancing asset longevity and reducing operational costs. This cutting-edge research emphasizes the potential of Digital Twins (DTW) technology to provide effective solutions for improving defense asset management. This paper introduces an innovative mechanism for securing defense asset data through the incorporation of the Internet of Things (IoT), DTW technology, and blockchain technology. Specifically, a comprehensive context-aware framework for monitoring the operational status of defense assets is proposed. Additionally, an Artificial Intelligence-inspired Convolutional Neural Network (CNN) technique is suggested for sequentially processing asset data to analyze real-time anomalies in military equipment. The framework ensures data security by utilizing advanced blockchain features, particularly through a Reputation-based Byzantine Fault Tolerance (RBFT) method within the consortium network. The proposed technique has been validated through extensive experimental simulations, showing enhanced performance with a latency rate of 1.55 s, data processing cost of (O((<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10586_2025_5467_Article_IEq1.gif" Format="GIF" Height="12" Rendition="HTML" Resolution="72" Type="Linedraw" Width="13" /> </InlineMediaObject> <EquationSource Format="TEX">$\eta$</EquationSource> <EquationSource Format="MATHML"><math> <mi>η</mi> </math></EquationSource> </InlineEquation>-1)<InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10586_2025_5467_Article_IEq2.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="22" /> </InlineMediaObject> <EquationSource Format="TEX">$\log$</EquationSource> <EquationSource Format="MATHML"><math> <mo>log</mo> </math></EquationSource> </InlineEquation> <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10586_2025_5467_Article_IEq1.gif" Format="GIF" Height="12" Rendition="HTML" Resolution="72" Type="Linedraw" Width="13" /> </InlineMediaObject> <EquationSource Format="TEX">$\eta$</EquationSource> <EquationSource Format="MATHML"><math> <mi>η</mi> </math></EquationSource> </InlineEquation>)), and high accuracy in model testing, achieving specificity (91.72%), sensitivity (93.47%), precision (92.40%), and F-Measure (92.44%).</p>

Smart methodology for defence asset management in blockchain environment

期刊论文
发表日期：

2025年9月11日

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Abdullah Aljumah,
Tariq Ahamed Ahanger,
Imdad Ullah,
Munish Bhatia

摘要

Information and Communication Technology (ICT) has significantly transformed the defense sector, enhancing asset longevity and reducing operational costs. This cutting-edge research emphasizes the potential of Digital Twins (DTW) technology to provide effective solutions for improving defense asset management. This paper introduces an innovative mechanism for securing defense asset data through the incorporation of the Internet of Things (IoT), DTW technology, and blockchain technology. Specifically, a comprehensive context-aware framework for monitoring the operational status of defense assets is proposed. Additionally, an Artificial Intelligence-inspired Convolutional Neural Network (CNN) technique is suggested for sequentially processing asset data to analyze real-time anomalies in military equipment. The framework ensures data security by utilizing advanced blockchain features, particularly through a Reputation-based Byzantine Fault Tolerance (RBFT) method within the consortium network. The proposed technique has been validated through extensive experimental simulations, showing enhanced performance with a latency rate of 1.55 s, data processing cost of (O(( $\eta$ $η$ -1) $\log$ $log$ $\eta$ $η$ )), and high accuracy in model testing, achieving specificity (91.72%), sensitivity (93.47%), precision (92.40%), and F-Measure (92.44%).