<?xml version="1.0" encoding="utf-8"?>
<TEI xmlns="http://www.tei-c.org/ns/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:hal="http://hal.archives-ouvertes.fr/" xmlns:gml="http://www.opengis.net/gml/3.3/" xmlns:gmlce="http://www.opengis.net/gml/3.3/ce" version="1.1" xsi:schemaLocation="http://www.tei-c.org/ns/1.0 http://api.archives-ouvertes.fr/documents/aofr-sword.xsd">
  <teiHeader>
    <fileDesc>
      <titleStmt>
        <title>HAL TEI export of hal-03657239</title>
      </titleStmt>
      <publicationStmt>
        <distributor>CCSD</distributor>
        <availability status="restricted">
          <licence target="https://creativecommons.org/publicdomain/zero/1.0/">CC0 1.0 - Universal</licence>
        </availability>
        <date when="2026-05-19T03:35:34+02:00"/>
      </publicationStmt>
      <sourceDesc>
        <p part="N">HAL API Platform</p>
      </sourceDesc>
    </fileDesc>
  </teiHeader>
  <text>
    <body>
      <listBibl>
        <biblFull>
          <titleStmt>
            <title xml:lang="en">Detecting Attacks on a Water Treatment System Using Oneclass Support Vector Machines</title>
            <author role="aut">
              <persName>
                <forename type="first">Ken</forename>
                <surname>Yau</surname>
              </persName>
              <idno type="halauthorid">1102825-0</idno>
              <affiliation ref="#struct-93487"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Kam-Pui</forename>
                <surname>Chow</surname>
              </persName>
              <email type="md5">f83db2f5810964f66ca1e01b70d85636</email>
              <email type="domain">cs.hku.hk</email>
              <idno type="idhal" notation="numeric">989410</idno>
              <idno type="halauthorid" notation="string">857372-989410</idno>
              <affiliation ref="#struct-93487"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Siu-Ming</forename>
                <surname>Yiu</surname>
              </persName>
              <idno type="halauthorid">738129-0</idno>
              <affiliation ref="#struct-93487"/>
            </author>
            <editor role="depositor">
              <persName>
                <forename>Hal</forename>
                <surname>Ifip</surname>
              </persName>
              <email type="md5">2073ac78024b6e13f2714db96e9b1e63</email>
              <email type="domain">inria.fr</email>
            </editor>
          </titleStmt>
          <editionStmt>
            <edition n="v1" type="current">
              <date type="whenSubmitted">2022-05-02 17:23:55</date>
              <date type="whenModified">2022-05-03 09:01:16</date>
              <date type="whenReleased">2022-05-03 09:00:50</date>
              <date type="whenProduced">2020-01-06</date>
              <date type="whenEndEmbargoed">2023-01-01</date>
              <ref type="file" target="https://inria.hal.science/hal-03657239v1/document">
                <date notBefore="2023-01-01"/>
              </ref>
              <ref type="file" subtype="author" n="1" target="https://inria.hal.science/hal-03657239v1/file/503209_1_En_6_Chapter.pdf" id="file-3657239-3193355">
                <date notBefore="2023-01-01"/>
              </ref>
            </edition>
            <respStmt>
              <resp>contributor</resp>
              <name key="200187">
                <persName>
                  <forename>Hal</forename>
                  <surname>Ifip</surname>
                </persName>
                <email type="md5">2073ac78024b6e13f2714db96e9b1e63</email>
                <email type="domain">inria.fr</email>
              </name>
            </respStmt>
          </editionStmt>
          <publicationStmt>
            <distributor>CCSD</distributor>
            <idno type="halId">hal-03657239</idno>
            <idno type="halUri">https://inria.hal.science/hal-03657239</idno>
            <idno type="halBibtex">yau:hal-03657239</idno>
            <idno type="halRefHtml">&lt;i&gt;16th IFIP International Conference on Digital Forensics (DigitalForensics)&lt;/i&gt;, Jan 2020, New Delhi, India. pp.95-108, &lt;a target="_blank" href="https://dx.doi.org/10.1007/978-3-030-56223-6_6"&gt;&amp;#x27E8;10.1007/978-3-030-56223-6_6&amp;#x27E9;&lt;/a&gt;</idno>
            <idno type="halRef">16th IFIP International Conference on Digital Forensics (DigitalForensics), Jan 2020, New Delhi, India. pp.95-108, &amp;#x27E8;10.1007/978-3-030-56223-6_6&amp;#x27E9;</idno>
            <availability status="restricted">
              <licence target="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0 - Attribution<ref corresp="#file-3657239-3193355"/></licence>
            </availability>
          </publicationStmt>
          <seriesStmt>
            <idno type="stamp" n="IFIP-LNCS" corresp="IFIP">IFIP - Lecture Notes in Computer Science</idno>
            <idno type="stamp" n="IFIP">IFIP - International Federation for Information Processing</idno>
            <idno type="stamp" n="IFIP-AICT" corresp="IFIP">IFIP Advances in Information and Communication Technology</idno>
            <idno type="stamp" n="IFIP-TC" corresp="IFIP">IFIP Technical Committees </idno>
            <idno type="stamp" n="IFIP-WG" corresp="IFIP">Working Groups</idno>
            <idno type="stamp" n="IFIP-TC11" corresp="IFIP-TC">IFIP TC11: Security and Privacy Protection in Information Processing Systems</idno>
            <idno type="stamp" n="IFIP-DF" corresp="IFIP-LNCS">IFIP-DF</idno>
            <idno type="stamp" n="IFIP-WG11-9" corresp="IFIP-WG">IFIP-WG11-9</idno>
            <idno type="stamp" n="IFIP-AICT-589" corresp="IFIP-AICT">Advances in Digital Forensics XVI</idno>
          </seriesStmt>
          <notesStmt>
            <note type="commentary">Part 2: Forensic Techniques</note>
            <note type="audience" n="2">International</note>
            <note type="invited" n="0">No</note>
            <note type="popular" n="0">No</note>
            <note type="peer" n="1">Yes</note>
            <note type="proceedings" n="1">Yes</note>
          </notesStmt>
          <sourceDesc>
            <biblStruct>
              <analytic>
                <title xml:lang="en">Detecting Attacks on a Water Treatment System Using Oneclass Support Vector Machines</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Ken</forename>
                    <surname>Yau</surname>
                  </persName>
                  <idno type="halauthorid">1102825-0</idno>
                  <affiliation ref="#struct-93487"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Kam-Pui</forename>
                    <surname>Chow</surname>
                  </persName>
                  <email type="md5">f83db2f5810964f66ca1e01b70d85636</email>
                  <email type="domain">cs.hku.hk</email>
                  <idno type="idhal" notation="numeric">989410</idno>
                  <idno type="halauthorid" notation="string">857372-989410</idno>
                  <affiliation ref="#struct-93487"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Siu-Ming</forename>
                    <surname>Yiu</surname>
                  </persName>
                  <idno type="halauthorid">738129-0</idno>
                  <affiliation ref="#struct-93487"/>
                </author>
              </analytic>
              <monogr>
                <title level="m">IFIP Advances in Information and Communication Technology</title>
                <meeting>
                  <title>16th IFIP International Conference on Digital Forensics (DigitalForensics)</title>
                  <date type="start">2020-01-06</date>
                  <date type="end">2020-01-08</date>
                  <settlement>New Delhi</settlement>
                  <country key="IN">India</country>
                </meeting>
                <editor>Gilbert Peterson</editor>
                <editor>Sujeet Shenoi</editor>
                <imprint>
                  <publisher>Springer International Publishing</publisher>
                  <biblScope unit="serie">Advances in Digital Forensics XVI</biblScope>
                  <biblScope unit="volume">AICT-589</biblScope>
                  <biblScope unit="pp">95-108</biblScope>
                  <date type="datePub">2020</date>
                </imprint>
              </monogr>
              <idno type="doi">10.1007/978-3-030-56223-6_6</idno>
            </biblStruct>
          </sourceDesc>
          <profileDesc>
            <langUsage>
              <language ident="en">English</language>
            </langUsage>
            <textClass>
              <keywords scheme="author">
                <term xml:lang="en">water treatment system</term>
                <term xml:lang="en">forensics</term>
                <term xml:lang="en">one-class SVM</term>
                <term xml:lang="en">Machine learning</term>
              </keywords>
              <classCode scheme="halDomain" n="info">Computer Science [cs]</classCode>
              <classCode scheme="halTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halOldTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halTreeTypology" n="COMM">Conference papers</classCode>
            </textClass>
            <abstract xml:lang="en">
              <p>Critical infrastructure assets such as power grids and water treatment plants are monitored and managed by industrial control systems. Attacks that leverage industrial control systems to disrupt or damage infrastructure assets can impact human lives, the economy and the environment. Several attack detection methods have been proposed, but they are often difficult to implement and their accuracy is often low. Additionally, these methods do not consider the digital forensic aspects.This chapter focuses on the use of machine learning, specifically one-class support vector machines, for attack detection and forensic investigations. The methodology is evaluated using a water treatment testbed, a scaled-down version of a real-world industrial water treatment plant. Data collected under normal operations and attacks are used in the study. In order to enhance detection accuracy, the water treatment process is divided into sub-processes for individual one-class support vector machine model training. The experimental results demonstrate that the trained sub-process models yield better detection performance than the trained complete process model. Additionally, the approach enhances the efficiency and effectiveness of forensic investigations.</p>
            </abstract>
            <particDesc>
              <org type="consortium">TC 11</org>
              <org type="consortium">WG 11.9</org>
            </particDesc>
          </profileDesc>
        </biblFull>
      </listBibl>
    </body>
    <back>
      <listOrg type="structures">
        <org type="institution" xml:id="struct-93487" status="VALID">
          <idno type="ROR">https://ror.org/02zhqgq86</idno>
          <orgName>The University of Hong Kong</orgName>
          <orgName type="acronym">HKU</orgName>
          <desc>
            <address>
              <addrLine>Pokfulam, Hong Kong</addrLine>
              <country key="HK"/>
            </address>
            <ref type="url">http://www.hku.hk/</ref>
          </desc>
        </org>
      </listOrg>
    </back>
  </text>
</TEI>