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UTD CS 6V81 - Lecture #19 Biometrics and Privacy - I

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Introduction to BiometricsOutlineSome Privacy concernsData Mining as a Threat to PrivacySome Privacy Problems and Potential SolutionsPrivacy Preserving Data MiningPrivacy ControllerSemantic Model for Privacy ControlPlatform for Privacy Preferences (P3P): What is it?Platform for Privacy Preferences (P3P): Key PointsPlatform for Privacy Preferences (P3P): OrganizationsPlatform for Privacy Preferences (P3P): SpecificationsPlatform for Privacy Preferences (P3P): Specifications (Concluded)P3P and Legal IssuesChallenges and DiscussionBiometrics and PrivacyRelationship: Biometrics and PrivacyHIPPA and BiometricsPrivacy Concerns Associated with Biometric DeploymentsInformational PrivacyPersonal PrivacyPrivacy Sympathetic Qualities of Biometric SystemsApplication Specific Privacy RisksBioPrivacy FrameworkBioPrivacy Framework (Concluded)Risk RatingsBiometrics for Private Data Sharing?Introduction to BiometricsDr. Bhavani ThuraisinghamThe University of Texas at DallasLecture #19Biometrics and Privacy - IOctober 31, 2005OutlineOverview of PrivacyBiometrics and PrivacySome Privacy concernsMedical and Healthcare-Employers, marketers, or others knowing of private medical concernsSecurity-Allowing access to individual’s travel and spending data-Allowing access to web surfing behaviorMarketing, Sales, and Finance-Allowing access to individual’s purchasesBiometrics-Biometric technologies used to violate privacyData Mining as a Threat to PrivacyData mining gives us “facts” that are not obvious to human analysts of the dataCan general trends across individuals be determined without revealing information about individuals?Possible threats:-Combine collections of data and infer information that is private Disease information from prescription dataMilitary Action from Pizza delivery to pentagonNeed to protect the associations and correlations between the data that are sensitive or privateSome Privacy Problems and Potential SolutionsProblem: Privacy violations that result due to data mining-Potential solution: Privacy-preserving data miningProblem: Privacy violations that result due to the Inference-Inference is the process of deducing sensitive information from the legitimate responses received to user queries-Potential solution: Privacy Constraint ProcessingProblem: Privacy violations due to un-encrypted data-Potential solution: Encryption at different levelsProblem: Privacy violation due to poor system design-Potential solution: Develop methodology for designing privacy-enhanced systemsProblem: Privacy violation due to Biometrics systems-Privacy sympathetic BiometricsPrivacy Preserving Data MiningPrevent useful results from mining -Introduce “cover stories” to give “false” results -Only make a sample of data available so that an adversary is unable to come up with useful rules and predictive functionsRandomization-Introduce random values into the data and/or results-Challenge is to introduce random values without significantly affecting the data mining results-Give range of values for results instead of exact valuesSecure Multi-party Computation-Each party knows its own inputs; encryption techniques used to compute final resultsPrivacy ControllerUser Interface ManagerConstraintManagerPrivacy ConstraintsQuery Processor:Constraints during query and release operationsUpdate Processor:Constraints during update operationDatabase Design ToolConstraints during database design operationDatabaseDBMSSemantic Model for Privacy ControlPatient JohnCancerInfluenzaHas diseaseTravels frequentlyEnglandaddressJohn’s addressDark lines/boxes containprivate informationPlatform for Privacy Preferences (P3P): What is it?P3P is an emerging industry standard that enables web sites to express their privacy practices in a standard formatThe format of the policies can be automatically retrieved and understood by user agentsIt is a product of W3C; World wide web consortiumwww.w3c.orgMain difference between privacy and security-User is informed of the privacy policies- User is not informed of the security policiesPlatform for Privacy Preferences (P3P): Key PointsWhen a user enters a web site, the privacy policies of the web site is conveyed to the userIf the privacy policies are different from user preferences, the user is notifiedUser can then decide how to proceedUser/Client maintains the privacy controller-That is, Privacy controller determines whether an untrusted web site can give out public information to a third party so that the third party infers private informationPlatform for Privacy Preferences (P3P): OrganizationsSeveral major corporations are working on P3P standards including:-Microsoft-IBM-HP-NEC-Nokia-NCRWeb sites have also implemented P3PSemantic web group has adopted P3PPlatform for Privacy Preferences (P3P): SpecificationsInitial version of P3P used RDF to specify policiesRecent version has migrated to XMLP3P Policies use XML with namespaces for encoding policiesExample: Catalog shopping-Your name will not be given to a third party but your purchases will be given to a third party-<POLICIES xmlns = http://www.w3.org/2002/01/P3Pv1><POLICY name = - - - -</POLICY></POLICIES>Platform for Privacy Preferences (P3P): Specifications (Concluded)P3P has its own statements a d data types expressed in XMLP3P schemas utilize XML schemasXML is a prerequisite to understanding P3PP3P specification released in January 2005 uses catalog shopping example to explain conceptsP3P is an International standard and is an ongoing projectP3P and Legal IssuesP3P does not replace lawsP3P work together with the lawWhat happens if the web sites do no honor their P3P policies-Then appropriate legal actions will have to be takenXML is the technology to specify P3P policiesPolicy experts will have to specify the policiesTechnologies will have to develop the specificationsLegal experts will have to take actions if the policies are violatedChallenges and DiscussionTechnology alone is not sufficient for privacyWe need technologists, Policy expert, Legal experts and Social scientists to work on PrivacySome well known people have said ‘Forget about privacy”Should we pursue working on Privacy?-Interesting research problems-Interdisciplinary research-Something is better than nothing-Try to prevent privacy violations-If violations occur then prosecutePrivacy is a major


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UTD CS 6V81 - Lecture #19 Biometrics and Privacy - I

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