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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
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              <elementText elementTextId="3139">
                <text>Faculty Publications</text>
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    <name>Conference Paper</name>
    <description>Faculty Publications- Conference Papers</description>
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      <name>Dublin Core</name>
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        <element elementId="39">
          <name>Creator</name>
          <description>An entity primarily responsible for making the resource</description>
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            <elementText elementTextId="256518">
              <text>Roy Jyrwa, Jethro Jarvis; Sinha, Somnath; Dutta, Binayak</text>
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        <element elementId="50">
          <name>Title</name>
          <description>A name given to the resource</description>
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            <elementText elementTextId="256519">
              <text>Comparative Analysis of Noise Generated in BGV Homomorphic Encryption: Lattigo vs FHEgen Parameters</text>
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          <name>Date</name>
          <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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            <elementText elementTextId="256520">
              <text>01-01-2025</text>
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        <element elementId="48">
          <name>Source</name>
          <description>A related resource from which the described resource is derived</description>
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            <elementText elementTextId="256521">
              <text>4th International Conference on Automation, Computing and Renewable Systems, ICACRS 2025 - Proceedings;pp.1183-1188</text>
            </elementText>
          </elementTextContainer>
        </element>
        <element elementId="43">
          <name>Identifier</name>
          <description>An unambiguous reference to the resource within a given context</description>
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            <elementText elementTextId="256522">
              <text>&lt;a href="https://doi.org/10.1109/ICACRS67045.2025.11324134" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICACRS67045.2025.11324134&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105032730674?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105032730674?origin=resultslist&lt;/a&gt;</text>
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          <name>Coverage</name>
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              <text>Roy Jyrwa J.J., Christ University, Department of Computer Science, Karnataka, Bengaluru, India; Sinha S., Christ University, Department of Computer Science, Karnataka, Bengaluru, India; Dutta B., Christ University, Department of Computer Science, Karnataka, Bengaluru, India</text>
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          <name>Description</name>
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              <text>Post-quantum cryptography has emerged as a critical field following advances in quantum computing that threaten classical encryption schemes such as RSA and ECC. Fully Homomorphic Encryption (FHE), particularly the Brakerski-Gentry- Vaikuntanathan (BGV) scheme based on the Ring Learning with Errors (RLWE) problem, provides a promising solution for secure computations on encrypted data. A fundamental challenge in BGV implementations is the growth of noise during homomorphic operations, which must remain below a decryption threshold to ensure correctness. This study presents a comparative analysis of noise generation in BGV implementations using two distinct parameter selection approaches: Lattigo's pre-validated generic parameters and FHEgen's automatically generated application-specific parameters. Through empirical measurements using Lattigo v6.1.1, we evaluated five parameter sets across initial noise after encryption, noise expansion during homomorphic multiplication, and overall noise growth patterns. Our results demonstrate that Lattigo N13 achieves marginally lower post-multiplication noise (0.0587 log2 bits, or 4.15% lower in magnitude), though FHEgen achieves substantially higher verified security (210 bits vs. 50-60 bits). However, Lattigo's range of pre-validated parameters (LogN = 12 to LogN = 15) offers greater flexibility for varying computational depths. We conclude that the choice between parameter selection approaches depends on application requirements: FHEgen is preferable for well-defined computational needs with noise optimization priorities, while Lattigo is advantageous when flexibility and extensive validation are critical. This work provides practical insights for FHE practitioners in selecting parameters that balance security, noise management, and computational efficiency.  2025 IEEE.</text>
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        <element elementId="49">
          <name>Subject</name>
          <description>The topic of the resource</description>
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              <text>BGV scheme; FHEgen; Fully Homomorphic Encryption; Industry; Innovation; Lattigo; Noise optimization; Parameter selection; Post-quantum cryptography; RLWE</text>
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          <name>Publisher</name>
          <description>An entity responsible for making the resource available</description>
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            <elementText elementTextId="256526">
              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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          <name>Relation</name>
          <description>A related resource</description>
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              <text>ISBN: 979-833154886-5;</text>
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          <name>Language</name>
          <description>A language of the resource</description>
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            <elementText elementTextId="256528">
              <text>English</text>
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          <name>Type</name>
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              <text>Conference paper</text>
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          <name>Rights</name>
          <description>Information about rights held in and over the resource</description>
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            <elementText elementTextId="256530">
              <text>Restricted Access; Hardcopy may be available in the library</text>
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          <name>Format</name>
          <description>The file format, physical medium, or dimensions of the resource</description>
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            <elementText elementTextId="256531">
              <text>online</text>
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