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<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">journal-of-discrete-mathematical-sciences-and-cryptography</journal-id>
      <journal-title-group>
        <journal-title>Journal of Discrete Mathematical Sciences and Cryptography</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2169-0065</issn>
      <issn publication-format="print">0972-0529</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/JDMSC-2783</article-id>
      <title-group>
        <article-title>Fuzzy algebraic structure based cryptographic key generation</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Shinde</surname>
            <given-names>Pravin Vishnu</given-names>
          </name>
          <aff>Department of Artificial Intelligence and Data Science, Shah and Anchor Kutchhi College of Engineering, Mumbai, Maharashtra, 400088, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Patil</surname>
            <given-names>Manoj</given-names>
          </name>
          <aff>Department of Computer Engineering, Rajiv Gandhi Institute of Technology, Mumbai, Maharashtra, 400053, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Pachade</surname>
            <given-names>Rahul S.</given-names>
          </name>
          <aff>Department of Artificial Intelligence &amp; Data Science, Shah and Anchor Kutchhi College of Engineering, Mumbai, Maharashtra, 400088, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Rane</surname>
            <given-names>Vaishali</given-names>
          </name>
          <aff>Department of Computer Engineering, Thakur Shyamnarayan Engineering College, Mumbai, Maharashtra, 400101, India</aff>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Mulani</surname>
            <given-names>Altaf Osman</given-names>
          </name>
          <aff>Department of Electronics &amp; Telecommunication Engineering, SKN Sinhgad College of Engineering, Pandharpur, Maharashtra, 413304, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Rana</surname>
            <given-names>Manish</given-names>
          </name>
          <aff>Department of Artificial Intelligence and Data Science, Wadala East, Shah and Anchor Kutchhi Engineering College, Mumbai, Maharashtra, 400088, India</aff>
        </contrib>
      </contrib-group>
      <volume>29</volume>
      <issue>9-B</issue>
      <fpage>3553</fpage>
      <lpage>3562</lpage>
      <pub-date date-type="pub">
        <day>30</day>
        <month>09</month>
        <year>2026</year>
      </pub-date>
      <abstract>
        <p>This paper introduces the Fuzzy Algebraic Key Generation Scheme (FAKGS), which embeds graded membership functions into the operations of groups and rings, producing key sequences whose structural complexity and statistical randomness measurably exceed those of deterministic algebraic counterparts. A fuzzy group (G, μG) is constructed by assigning vertex-strength memberships μG(x) ∈ [0,1] to each group element x ∈ G, subject to the subgroup-analogue condition μG(xy–1) ≥ min(μG(x), μG(y)). A companion fuzzy ring (R, μR) encodes additive and multiplicative membership separately, and a structure-preserving fuzzy homomorphism φ: (G, μG) → (R, μR) maps group coset information into the ring’s multiplication domain. Nonlinear key sequences are then derived from this mapping via a combinatorial Latin-square permutation layer and an affine transformation over GL(n, Zp). Testing on 10,000 independent key instantiations confirms that FAKGS achieves a NIST SP 800-22 average pass rate of 99.6%, Shannon entropy of 7.9998 bits/byte, avalanche effect of 50.8 ± 0.28%, and a 384-bit effective key space. Key generation time is O(|G| log|G|), confirmed empirically at 125 Mbps throughput for 256-bit blocks on standard hardware. Algebraic attack resistance, measured by the cost of the XL algorithm on the induced equation system, exceeds the baseline graph-cipher by a factor of 216 at equation degree 12. The FAKGS is validated on constrained IoT hardware (ARM Cortex-A72) at 44 Mbps, confirming embedded-system viability.</p>
      </abstract>
      <kwd-group>
        <kwd>Fuzzy algebra</kwd>
        <kwd>Cryptographic key generation</kwd>
        <kwd>Discrete algebraic structures</kwd>
        <kwd>Cryptanalysis resistance</kwd>
        <kwd>Information security</kwd>
      </kwd-group>
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  </front>
</article>
