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    <journal-meta>
      <journal-id journal-id-type="publisher-id">IJLTEMAS</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Latest Technology in Engineering, Management &amp; Applied Science (IJLTEMAS)</journal-title>
        <abbrev-journal-title abbrev-type="publisher">IJLTEMAS</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">2278-2540</issn>
      <publisher>
        <publisher-name>IJLTEMAS</publisher-name>
      </publisher>
    </journal-meta>

    <article-meta>
      <!-- IDs -->
      <article-id pub-id-type="publisher-id">324</article-id>
            <article-id pub-id-type="doi">10.51583/IJLTEMAS.2026.150800130</article-id>
      
      <!-- Categories -->
            <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artificial Intelligence</subject>
        </subj-group>
      </article-categories>
      
      <!-- Title -->
      <title-group>
        <article-title>NBATS: Banknote Authentication and Cash-Compliance Intelligence (A Tiered, Privacy-Preserving Framework for Counterfeit Detection and Cash Provenance in India)</article-title>
      </title-group>

      <!-- Authors -->
      <contrib-group>
                <contrib contrib-type="author">
                    <name>
            <surname>G. Udepurkar</surname>
            <given-names>Sachin</given-names>
          </name>
                              <aff>
            Partner &amp; Management Consultant |Qualified Independent Director (IICA)|PGDFM (MBA–Finance &amp; Microfinance), IIFM Bhopal |Occupational Therapist – Ergo medicine ,GMC, Nagpur | Certified in Base &amp; Advanced SAS|R Programming |Licentiate Insurance |Corporate Social Responsibility IICA, India &amp; Audencia Nantes School of Management, France |AI Mastery Programme ,Coursiv, Navi Mumbai / Nagpur                        <country>India</country>
                      </aff>
                    
        </contrib>
              </contrib-group>

      <!-- Volume / Issue / Pages -->
            <volume>15</volume>
                  <issue>8</issue>
                        <fpage>1787</fpage>
            <lpage>1796</lpage>
            
      <!-- Dates -->
      <history>
                <date date-type="received">
          <day>07</day>
          <month>09</month>
          <year>2026</year>
        </date>
                        <date date-type="accepted">
          <day>12</day>
          <month>09</month>
          <year>2026</year>
        </date>
              </history>

            <pub-date pub-type="epub">
        <day>22</day>
        <month>09</month>
        <year>2026</year>
      </pub-date>
      
      <!-- DOI Self-URI -->
            <self-uri xlink:href="https://doi.org/10.51583/IJLTEMAS.2026.150800130"/>
      
      <!-- Keywords -->
            <kwd-group kwd-group-type="author">
                <kwd>banknote authentication</kwd>
                <kwd>counterfeit detection</kwd>
                <kwd>cash traceability</kwd>
                <kwd>privacy-preserving systems</kwd>
                <kwd>financial compliance</kwd>
              </kwd-group>
      
    </article-meta>
  </front>

  <!-- ============================================================ BODY (Abstract) -->
  <body>
        <sec>
      <title>Abstract</title>
      <p>Cash remains a dominant medium of exchange in India despite rapid digital-payment growth, and its physical nature makes counterfeiting, duplicate circulation, and untraceable high-value cash movement persistent challenges for monetary authorities. The Reserve Bank of India (RBI) already operates a mature framework for detecting and reporting counterfeit currency at banks and currency chests, yet this framework is largely confined to designated touchpoints and does not extend authenticated verification across the broader cash ecosystem. This paper proposes the National Banknote Authentication and Traceability System (NBATS), a conceptual architecture that authenticates physical banknotes through multi-feature verification - serial-number recognition, security-thread and watermark analysis, and optical/ultraviolet characteristics while recording only selected, purpose-limited cash-handling events rather than continuous holder-level possession. The architecture is organised into five layers: the banknote itself, an authentication device, an event ledger, an alert engine, and a tiered investigation interface, supported by a proposed Cash Provenance Confidence Score that combines authenticity, serial validity, issuance consistency, and historical anomaly indicators into a single risk metric. Three participation tiers like voluntary public verification aligned to guidelines within applicable framework, mandatory verification for regulated cash-intensive businesses, and integrated banking/currency-chest authentication are proposed to balance feasibility against comprehensiveness. The paper explicitly foregrounds privacy-by-design, data minimisation, purpose limitation, and role-based access as central design constraints, situating the proposal within India's Digital Personal Data Protection Act, 2023, and within international literature on privacy-preserving digital-currency architectures. Five research questions and five testable hypotheses are formulated to guide future empirical work, including pilot studies and accuracy benchmarking of multi-feature authentication against serial-number-only verification. The paper concludes that a phased, tiered, and privacy-constrained architecture is more implementable and more defensible than a universal note-tracking mandate, and identifies pilot design, cryptographic protocol selection, and stakeholder-acceptance studies as priorities for subsequent research.</p>
    </sec>
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    <ref-list>
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