<?xml version="1.0" encoding="UTF-8"?>
<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">journal-of-information-and-optimization-sciences</journal-id>
      <journal-title-group>
        <journal-title>Journal of Information and Optimization Sciences</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2169-0103</issn>
      <issn publication-format="print">0252-2667</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/JIOS-2209</article-id>
      <title-group>
        <article-title>Malware detection using machine learning</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Dhongade</surname>
            <given-names>Gauri</given-names>
          </name>
          <aff>Department of Information Technology, MATS University, Raipur, Chhattisgarh, 492001, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Chandrakar</surname>
            <given-names>Omprakash</given-names>
          </name>
          <aff>Department of Information Technology, MATS University, Raipur, Chhattisgarh, 492001, India</aff>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Khande</surname>
            <given-names>Rajeshree</given-names>
          </name>
          <aff>Department of Technology and Management, Shri Balaji Institute of Technology &amp; Management, Sri Balaji University, Pune, Pune, Maharashtra, 411033, India</aff>
        </contrib>
      </contrib-group>
      <volume>47</volume>
      <issue>8</issue>
      <fpage>2877</fpage>
      <lpage>2889</lpage>
      <pub-date date-type="pub">
        <day>31</day>
        <month>08</month>
        <year>2026</year>
      </pub-date>
      <abstract>
        <p>In this era of Artificial Intelligence and huge online activities, safeguarding sensitive data and protecting personal information is essential in this era. Cyber-attacks can cause the monetary loss as well as reputational loss of the victim organizations. Malware is one type of cyber-attacks; it refers to malicious software that intentionally designed to damage or exploit or harm the data and networks. Detection of malware attacks using traditional based systems will fail to detect new types of variants. This Papers aims to provide ways for malware detection using the machine learning algorithms. Malware Dataset is processed using preprocessing techniques and then machine learning algorithms like Logistic Regression, Ransom Forest, Ada boost will be used to analyse the data and provide high accuracy in classification and detection of malwares. Data Preprocessing techniques and ML algorithms will give significant results as compared to traditional ways.</p>
      </abstract>
      <kwd-group>
        <kwd>Cybersecurity</kwd>
        <kwd>Malware detection</kwd>
        <kwd>Machine learning</kwd>
        <kwd>Classification</kwd>
        <kwd>Random forest</kwd>
        <kwd>Artificial intelligence</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>access</meta-name>
          <meta-value>open</meta-value>
        </custom-meta>
        <custom-meta>
          <meta-name>retracted</meta-name>
          <meta-value>no</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
</article>
