<?xml version="1.0" encoding="UTF-8" ?>
<rdf:RDF
 xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
 xmlns="http://purl.org/rss/1.0/"
 xmlns:dc="http://purl.org/dc/elements/1.1/"
 xmlns:cc="http://web.resource.org/cc/"
 >
<!--
  This ontology document is licensed under the Creative Commons
  Attribution License. To view a copy of this license, visit
  http://creativecommons.org/licenses/by/2.0/ or send a letter to
  Creative Commons, 559 Nathan Abbott Way, Stanford, California
  94305, USA.
-->
 <channel rdf:about="/list/resources/format/html/">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <image rdf:resource="" />  <title><![CDATA[AISL RSS Resource Feed]]></title>
  <link>/list/resources/format/html/</link>
  <description><![CDATA[Assured Information Sharing LifeCycle RSS Resource Feed]]></description>
  <items>
   <rdf:Seq>
    <rdf:li resource="http://www.utdallas.edu/~mxk055100/publications/incentive-trust-assured-info-sharing.pdf"/>
    <rdf:li resource=""/>
    <rdf:li resource=""/>
    <rdf:li resource=""/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdf/pkdd09_mmasud.pdf"/>
    <rdf:li resource=""/>
    <rdf:li resource=""/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_dlo.pdf"/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_zyin.pdf"/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_jgao.pdf"/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_ysun.pdf"/>
    <rdf:li resource=""/>
    <rdf:li resource=""/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdf/vldb09_mskim.pdf"/>
    <rdf:li resource=""/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdfvldb09_cchen.pdf"/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdfvldb09_twu.pdf"/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdf/ijcai09_dengcai.pdf"/>
    <rdf:li resource=""/>
    <rdf:li resource=""/>
    <rdf:li resource=""/>
    <rdf:li resource=""/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdf/dcoss09_maifi.pdf"/>
    <rdf:li resource=""/>
    <rdf:li resource="http://www.cs.uiuc.edu/homes/hanj/pdf/icdcs_jinggao.pdf"/>
    <rdf:li resource="http://www.cs.umbc.edu/~hillol/NGDM07/abstracts/talks/JHan.pdf"/>
    <rdf:li resource=""/>
    <rdf:li resource=""/>
    <rdf:li resource="http://www.profsandhu.com/confrnc/misconf/ifiptm_tiupam_pre_09.pdf"/>
    <rdf:li resource="http://www.profsandhu.com/confrnc/misconf/isi-workshop-09.pdf"/>
   </rdf:Seq>
  </items>
 </channel>
 <image rdf:about="">
  <title></title>
  <link></link>
  <url></url>
 </image>
 <item rdf:about="http://www.utdallas.edu/~mxk055100/publications/incentive-trust-assured-info-sharing.pdf">
  <title><![CDATA[Incentive and Trust Issues in Assured Information Sharing]]></title>
  <link>http://www.utdallas.edu/~mxk055100/publications/incentive-trust-assured-info-sharing.pdf</link>
  <description><![CDATA[Assured information sharing among different organizations in a
coalitional environment is an important first step in accomplishing many critical
tasks. For example, different security agencies may need to share intelligence
information for detecting terrorist plots. At the same, each organization
participating in the assured information sharing process may have different
incentives. In this paper, we explore the effects of different incentives and
potential trust issues among organizati...]]></description>
  <dc:date>2009-11-11</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Applying Differential Privacy to Search Queries in a Policy Based Interactive Framework]]></title>
  <description><![CDATA[Web search logs are of growing importance to researchers as they help understanding search behavior and search engine performance. However, search logs typically contain sensitive information about users and therefore considerable caution must be exercised when considering releasing the logs to the research community. Current approaches to releasing search logs focus on either protecting the privacy of users or enhancing the utility of data to researchers. In this work, we address the privacy...]]></description>
  <dc:date>2009-11-06</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Ensembles in Adversarial Classification for Spam]]></title>
  <description><![CDATA[The standard method for combating spam, either in email or on the web, is to train a classifier on manually labeled instances. As the spammers change their tactics, the performance of such classifiers tends to decrease over time. Gathering and labeling more data to periodically retrain the classifier is expensive. We present a method based on an ensemble of classifiers that can detect when its performance might be degrading and retrain itself, all without manual intervention. Experiments with...]]></description>
  <dc:date>2009-11-02</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Scalable Distributed Change Detection from Astronomy Data Streams using Local, Asynchronous Eigen Monitoring Algorithms]]></title>
  <description><![CDATA[This paper considers the problem of change detection using local
distributed eigen monitoring algorithms for next generation
of astronomy petascale data pipelines such as the Large Synoptic
Survey Telescopes (LSST). This telescope will take repeat images
of the night sky every 20 seconds, thereby generating 30 terabytes
of calibrated imagery every night that will need to be coanalyzed
with other astronomical data stored at different locations
around the world. Change point detection an...]]></description>
  <dc:date>2009-11-01</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdf/pkdd09_mmasud.pdf">
  <title><![CDATA[Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdf/pkdd09_mmasud.pdf</link>
  <dc:date>2009-09-21</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Access control policy comparison]]></title>
  <dc:date>2009-09-18</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[A Local Distributed Peer-to-Peer Data Mining Algorithm Using Multi-Party Optimization Based Privacy Preservation]]></title>
  <dc:date>2009-09-08</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_dlo.pdf">
  <title><![CDATA[Classification of Software Behaviors for Failure Detection: A Discriminative Pattern Mining Approach]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_dlo.pdf</link>
  <description><![CDATA[Software is a ubiquitous component of our daily life. We of-
ten depend on the correct working of software systems. Due
to the di±culty and complexity of software systems, bugs
and anomalies are prevalent. Bugs have caused billions of
dollars loss, in addition to privacy and security threats. In
this work, we address software reliability issues by proposing
a novel method to classify software behaviors based on past
history or runs. With the technique, it is possible to gener-
alize ...]]></description>
  <dc:date>2009-08-30</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_zyin.pdf">
  <title><![CDATA[Exploring Social Tagging Graph for Web Object Classification]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_zyin.pdf</link>
  <description><![CDATA[This paper studies web object classification problem with
the novel exploration of social tags. Automatically classifying
web objects into manageable semantic categories has
long been a fundamental preprocess for indexing, browsing,
searching, and mining these objects. The explosive growth
of heterogeneous web objects, especially non-textual objects
such as products, pictures, and videos, has made the problem
of web classification increasingly challenging. Such objects
often suffer fr...]]></description>
  <dc:date>2009-08-30</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_jgao.pdf">
  <title><![CDATA[Heterogeneous Source Consensus Learning via Decision Propagation and Negotiation]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_jgao.pdf</link>
  <description><![CDATA[Nowadays, enormous amounts of data are continuously gen-
erated not only in massive scale, but also from di®erent,
sometimes con°icting, views. Therefore, it is important to
consolidate di®erent concepts for intelligent decision mak-
ing. For example, to predict the research areas of some
people, the best results are usually achieved by combining
and consolidating predictions obtained from the publication
network, co-authorship network and the textual content of
their publications....]]></description>
  <dc:date>2009-08-30</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_ysun.pdf">
  <title><![CDATA[Ranking-Based Clustering of Heterogeneous Information Networks with Star Network Schema]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdf/kdd09_ysun.pdf</link>
  <description><![CDATA[A heterogeneous information network is an information
network composed of multiple types of objects. Cluster-
ing on such a network may lead to better understanding of
both hidden structures of the network and the individual role
played by every object in each cluster. However, although
clustering on homogeneous networks has been studied over
decades, clustering on heterogeneous networks has not been
addressed until recently.
A recent study proposed a new algorithm, RankClus, for
clu...]]></description>
  <dc:date>2009-08-30</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Policy-based Malicious Peer Detection in Ad Hoc Networks]]></title>
  <description><![CDATA[Mobile Ad hoc Networks (MANETs) are susceptible to various node misbehaviors due to their unique features, such as highly dynamic network topology, rigorous power constraints and error-prone transmission media. Significant research efforts have been made to address the problem of misbehavior detection.  However, little research work has been done to distinguish truly malicious behaviors from the faulty behaviors. Both the malicious behaviors and the faulty behaviors are generally equally trea...]]></description>
  <dc:date>2009-08-29</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Surfing a web of trust: reputation and reciprocity on CouchSurfing.com]]></title>
  <dc:date>2009-08-29</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdf/vldb09_mskim.pdf">
  <title><![CDATA[A Particle-and-Density Based Evolutionary Clustering Method for Dynamic Networks]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdf/vldb09_mskim.pdf</link>
  <dc:date>2009-08-21</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Game-theoretic approach toward privacy preserving distributed data mining]]></title>
  <dc:date>2009-08-21</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdfvldb09_cchen.pdf">
  <title><![CDATA[Mining Graph Patterns Efficiently via Randomized Summaries]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdfvldb09_cchen.pdf</link>
  <dc:date>2009-08-21</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdfvldb09_twu.pdf">
  <title><![CDATA[Promotion Analysis in Multi-Dimensional Space]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdfvldb09_twu.pdf</link>
  <dc:date>2009-08-21</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdf/ijcai09_dengcai.pdf">
  <title><![CDATA[Locality Preserving Nonnegative Matrix Factorization]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdf/ijcai09_dengcai.pdf</link>
  <dc:date>2009-07-21</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Social Influence and the Diffusion of User Created Content]]></title>
  <description><![CDATA[Social in
uence determines to a large extent what we adopt
and when we adopt it. This is just as true in the digi-
tal domain as it is in real life, and has become of increas-
ing importance due to the deluge of user-created content on
the Internet. In this paper, we present an empirical study
of user-to-user content transfer occurring in the context of
a time-evolving social network in Second Life, a massively
multiplayer virtual world.
We identify and model social in
uence based o...]]></description>
  <dc:date>2009-07-06</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Access Control Policy Combining: Theory Meets Practice]]></title>
  <description><![CDATA[Many access control policy languages, e.g., XACML, allow a policy
to contain multiple sub-policies, and the result of the policy on
a request is determined by combining the results of the sub-policies
according to some policy combining algorithms (PCAs). Existing
access control policy languages, however, do not provide a formal
language for specifying PCAs. As a result, it is difficult to extend
them with new PCAs. While several formal policy combining
algebras have been proposed, they...]]></description>
  <dc:date>2009-06-30</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[An Algebra for Fine-Grained Integration of XACML Policies]]></title>
  <description><![CDATA[Collaborative and distributed applications, such as dynamic coalitions
and virtualized grid computing, often require integrating access
control policies of collaborating parties. Such an integration
must be able to support complex authorization specifications and
the fine-grained integration requirements that the various parties
may have. In this paper, we introduce an algebra for fine-grained
integration of sophisticated policies. The algebra, which consists
of three binary and two un...]]></description>
  <dc:date>2009-06-30</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Automating Role-based Provisioning by Learning from Examples]]></title>
  <description><![CDATA[Role-based provisioning has been adopted as a standard component
in leading Identity Management products due to its low administration
cost. However, the cost of adjusting existing roles to entitlements
from newly deployed applications is usually very high. In
this paper, a learning-based approach to automate the provisioning
process is proposed and its effectiveness is verified by real provisioning
data. Specific learning issues related to provisioning are
identified and relevant solu...]]></description>
  <dc:date>2009-06-30</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdf/dcoss09_maifi.pdf">
  <title><![CDATA[Finding Symbolic Bug Patterns in Sensor Networks]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdf/dcoss09_maifi.pdf</link>
  <dc:date>2009-06-30</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Mining Frequent Approximate Sequential Patterns]]></title>
  <dc:date>2009-06-30</dc:date>
 </item>
 <item rdf:about="http://www.cs.uiuc.edu/homes/hanj/pdf/icdcs_jinggao.pdf">
  <title><![CDATA[Modeling Probabilistic Measurement Correlations for Problem Determination in Large-Scale Distributed Systems]]></title>
  <link>http://www.cs.uiuc.edu/homes/hanj/pdf/icdcs_jinggao.pdf</link>
  <dc:date>2009-06-30</dc:date>
 </item>
 <item rdf:about="http://www.cs.umbc.edu/~hillol/NGDM07/abstracts/talks/JHan.pdf">
  <title><![CDATA[Research Challenges for Data Mining in Science and Engineering]]></title>
  <link>http://www.cs.umbc.edu/~hillol/NGDM07/abstracts/talks/JHan.pdf</link>
  <description><![CDATA[With the rapid development of computer and information
technology in the last several decades, an enormous amount
of data in science and engineering has been and will con-
tinuously be generated in massive scale, either being stored
in gigantic storage devices or °owing into and out of the
system in the form of data streams. Moreover, such data
has been made widely available, e.g., via the Internet. Such
tremendous amount of data, in the order of tera- to peta-
bytes, has fundamental...]]></description>
  <dc:date>2009-06-30</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Supporting RBAC with XACML+OWL]]></title>
  <description><![CDATA[XACML does not natively support RBAC and even the specialized XACML profiles are not able to support many relevant constraints such as static and dynamic separation of duty. Extending XACML to support such constraints, however, is an issue that requires extensions not only to the XACML language but also to the XACML reference architecture and engine. In this paper we introduce XACML+OWL,a framework that integrates OWL ontologies and XACML policies for supporting RBAC. The basic idea is to dec...]]></description>
  <dc:date>2009-06-30</dc:date>
 </item>
 <item rdf:about="">
  <title><![CDATA[Trustworthiness-centric Assured Information Sharing]]></title>
  <dc:date>2009-06-16</dc:date>
 </item>
 <item rdf:about="http://www.profsandhu.com/confrnc/misconf/ifiptm_tiupam_pre_09.pdf">
  <title><![CDATA[TIUPAM: A Framework for Trustworthiness-Centric Information Sharing]]></title>
  <link>http://www.profsandhu.com/confrnc/misconf/ifiptm_tiupam_pre_09.pdf</link>
  <description><![CDATA[Information is essential to decision making. Nowadays, decision makers
are often overwhelmed with large volumes of information, some of which
may be inaccurate, incorrect, inappropriate, misleading, or maliciously introduced.
With the advocated shift of information sharing paradigm from “need
to know” to “need to share” this problem will be further compounded. This
poses the challenge of achieving assured information sharing so that decision
makers can always get and utilize the...]]></description>
  <dc:date>2009-06-15</dc:date>
 </item>
 <item rdf:about="http://www.profsandhu.com/confrnc/misconf/isi-workshop-09.pdf">
  <title><![CDATA[A Characterization of the Problem of Secure Provenance Management]]></title>
  <link>http://www.profsandhu.com/confrnc/misconf/isi-workshop-09.pdf</link>
  <description><![CDATA[Data (or information) provenance has many
important applications. However, prior work on data
provenance management almost exclusively focused on the
collection, representation, query, and storage of provenance
data. In contrast, the security aspect of provenance
management has not been understood nor adequately
addressed. A natural question then is: What would a
secure provenance management system — perhaps as an
analogy to secure database management systems — look
like? In this...]]></description>
  <dc:date>2009-06-11</dc:date>
 </item>
</rdf:RDF>
