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<div class=Section1>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><a href="http://www.ehealthinformation.ca/CAI/index.asp">http://www.ehealthinformation.ca/CAI/index.asp</a><o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
<p class=style4><font size=1 color=black face=Verdana><span style='font-size:
8.5pt;font-family:Verdana;color:black'>With the increasing adoption of
electronic medical/health records and the rising use of electroinc data capture
tools in clinical research, large electronic repositories of personal health
information (PHI) are being built up. At the same time, large medical data
breaches are becoming common. Data breaches may be caused by errors committed
by insiders at the data custodian sites, or by malicious insiders. Data
breaches can also be caused by outsiders breaking into the data repositories.
These data breaches represent legal and financial liabilities for the data
custodians, and erode public trust in the ability of data custodians to manage
their PHI.<o:p></o:p></span></font></p>
<p class=style4><font size=1 color=black face=Verdana><span style='font-size:
8.5pt;font-family:Verdana;color:black'>An area that has grown in importance to
manage the risks from breaches is data leak prevention (DLP). DLP technologies
monitor communications or networks to detect PHI leaks. When a leak is detected
the affected individual or organization is notified, at which point they can
take remedial action. DLP can prevent a PHI leak or detect it after it happens.
For example, if DLP is deployed to monitor email then a PHI alert can be
generated before the email is sent. If DLP is used to monitor PHI leaks on the
Internet (e.g., on peer-to-peer file sharing networks or on web sites), then
the alerts pertain to leaks that have already occured, at which point the
affected individual or data custodian can attempt to contain the damage and
stop further leaks.<o:p></o:p></span></font></p>
<p class=style4><font size=3 face="Times New Roman"><span style='font-size:
12.0pt'>Computational AI is a key enabling technology for next-generation DLP
technologies. This workshop aims to bring together researchers working on
computational tools for DLP. Topics of interest include, but are not limited </span></font><font
size=1 color=black face=Verdana><span style='font-size:8.5pt;font-family:Verdana;
color:black'><o:p></o:p></span></font></p>
<p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><font
size=1 color=black face=Verdana><span style='font-size:8.5pt;font-family:Verdana;
color:black'>+ reviews: reviews of DLP systems and methods; and reviews of PHI
leaks that are occuring. <o:p></o:p></span></font></p>
<p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><font
size=1 color=black face=Verdana><span style='font-size:8.5pt;font-family:Verdana;
color:black'>+ methods: detection of personally identifying information in
text; detection of health information in different types of text (e.g.,
professionally written vs. lay person generated); and re-identification risk
assessment;<o:p></o:p></span></font></p>
<p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><font
size=1 color=black face=Verdana><span style='font-size:8.5pt;font-family:Verdana;
color:black'>+ applications: monitoring the web and peer-to-peer file sharing
networks for PHI leaks; detection of PHI in email or other communications; and tools
for dealing with PHI leaks in an automated way (e.g., de-identification). <o:p></o:p></span></font></p>
<p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><font
size=1 color=black face=Verdana><span style='font-size:8.5pt;font-family:Verdana;
color:black'>+ evaluation: empirical evaluation of deployed systems; theoretical
methods of risk assessment; and new methods for evaluating such systems. <o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
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