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<title>UTas ePrints - Detecting Clone Radio Frequency Identification Tags</title>
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<meta content="Mirowski, Luke Thomas" name="eprints.creators_name" />
<meta content="ltm@utas.edu.au" name="eprints.creators_id" />
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<meta content="2007-02-22" name="eprints.datestamp" />
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<meta content="Detecting Clone Radio Frequency Identification Tags" name="eprints.title" />
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<meta content="RFID, clones, cloning, security" name="eprints.keywords" />
<meta content="The theft of Radio Frequency Identification (RFID) tag identity, commonly referred to as tag cloning, is a serious threat to RFID systems. It can enable an attacker to gain access to a secure facility, make fraudulent purchases, or disrupt supply chains. It may even enable crimes like financial gain, people smuggling, and drug trafficking, terrorism and money laundering. Presently there is no practical solution to defend against tag cloning. This thesis details research that aims to detect the presence of clone tags which may be the first step in defending against them and preventing RFID-enabled crimes from occurring. An intrusion detection system has been developed using statistical anomaly detection to identify clone tags. The feasibility of the approach has been tested by evaluating its performance in detecting synthesized attacks inside a sanitized RFID audit log. The results suggest that intrusion detection systems can be used to detect cloned tags but that the weaknesses of statistical anomaly detection are also apparent when used on RFID data. " name="eprints.abstract" />
<meta content="2006-11" name="eprints.date" />
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<meta content="University of Tasmania" name="eprints.institution" />
<meta content="School of Computing" name="eprints.department" />
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<meta content="The theft of Radio Frequency Identification (RFID) tag identity, commonly referred to as tag cloning, is a serious threat to RFID systems. It can enable an attacker to gain access to a secure facility, make fraudulent purchases, or disrupt supply chains. It may even enable crimes like financial gain, people smuggling, and drug trafficking, terrorism and money laundering. Presently there is no practical solution to defend against tag cloning. This thesis details research that aims to detect the presence of clone tags which may be the first step in defending against them and preventing RFID-enabled crimes from occurring. An intrusion detection system has been developed using statistical anomaly detection to identify clone tags. The feasibility of the approach has been tested by evaluating its performance in detecting synthesized attacks inside a sanitized RFID audit log. The results suggest that intrusion detection systems can be used to detect cloned tags but that the weaknesses of statistical anomaly detection are also apparent when used on RFID data. " name="DC.description" />
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<h1 class="ep_tm_pagetitle">Detecting Clone Radio Frequency Identification Tags</h1>
<p style="margin-bottom: 1em" class="not_ep_block"><span class="person_name">Mirowski, Luke Thomas</span> (2006) <xhtml:em>Detecting Clone Radio Frequency Identification Tags.</xhtml:em> Honours thesis, University of Tasmania.</p><p style="margin-bottom: 1em" class="not_ep_block"></p><table style="margin-bottom: 1em" class="not_ep_block"><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_797' );" href="http://eprints.utas.edu.au/792/1/Detecting_Clone_Radio_Frequency_Identification_Tags.pdf" onmouseout="EPJS_HidePreview( event, 'doc_preview_797' );"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" class="ep_doc_icon" border="0" /></a><div class="ep_preview" id="doc_preview_797"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/792/thumbnails/1/preview.png" class="ep_preview_image" border="0" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/792/1/Detecting_Clone_Radio_Frequency_Identification_Tags.pdf"><span class="ep_document_citation">PDF (Complete thesis)</span></a> - Requires a PDF viewer<br />394Kb</td></tr></table><div class="not_ep_block"><h2>Abstract</h2><p style="padding-bottom: 16px; text-align: left; margin: 1em auto 0em auto">The theft of Radio Frequency Identification (RFID) tag identity, commonly referred to as tag cloning, is a serious threat to RFID systems. It can enable an attacker to gain access to a secure facility, make fraudulent purchases, or disrupt supply chains. It may even enable crimes like financial gain, people smuggling, and drug trafficking, terrorism and money laundering. Presently there is no practical solution to defend against tag cloning. This thesis details research that aims to detect the presence of clone tags which may be the first step in defending against them and preventing RFID-enabled crimes from occurring. An intrusion detection system has been developed using statistical anomaly detection to identify clone tags. The feasibility of the approach has been tested by evaluating its performance in detecting synthesized attacks inside a sanitized RFID audit log. The results suggest that intrusion detection systems can be used to detect cloned tags but that the weaknesses of statistical anomaly detection are also apparent when used on RFID data. </p></div><table style="margin-bottom: 1em" cellpadding="3" class="not_ep_block" border="0"><tr><th valign="top" class="ep_row">Item Type:</th><td valign="top" class="ep_row">Thesis (Honours)</td></tr><tr><th valign="top" class="ep_row">Keywords:</th><td valign="top" class="ep_row">RFID, clones, cloning, security</td></tr><tr><th valign="top" class="ep_row">Subjects:</th><td valign="top" class="ep_row"><a href="http://eprints.utas.edu.au/view/subjects/280399.html">280000 Information, Computing and Communication Sciences > 280300 Computer Software > 280399 Computer Software not elsewhere classified</a></td></tr><tr><th valign="top" class="ep_row">ID Code:</th><td valign="top" class="ep_row">792</td></tr><tr><th valign="top" class="ep_row">Deposited By:</th><td valign="top" class="ep_row"><span class="ep_name_citation"><span class="person_name">Prof Arthur Sale</span></span></td></tr><tr><th valign="top" class="ep_row">Deposited On:</th><td valign="top" class="ep_row">22 Feb 2007</td></tr><tr><th valign="top" class="ep_row">Last Modified:</th><td valign="top" class="ep_row">09 Jan 2008 02:30</td></tr><tr><th valign="top" class="ep_row">ePrint Statistics:</th><td valign="top" class="ep_row"><a target="ePrintStats" href="/es/index.php?action=show_detail_eprint;id=792;">View statistics for this ePrint</a></td></tr></table><p align="right">Repository Staff Only: <a href="http://eprints.utas.edu.au/cgi/users/home?screen=EPrint::View&eprintid=792">item control page</a></p>
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