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Penn State Law Review Winter, 2010 Articles *809 PEOPLE CAN BE SO FAKE: A NEW DIMENSION TO PRIVACY AND TECHNOLOGY SCHOLARSHIP M. Ryan Calo [FNa1] Copyright (c) 2010 The Dickensen School of Law of The Pennsylvania State University; M. Ryan Calo This article updates the traditional discussion of privacy and technology, focused since the days […]

1 PRIVACY INVASIVE GEO -MASHUPS: PRIVACY 2.0 AND THE LIMITS OF FIRST GENERATION INFORMATI ON PRIVACY LAWS Mark Burdon † ABSTRACT Online technological advances are pioneering the wider distribution of geospatial information for general mapping purposes. The use of popular web – based applications, such as Google Maps, is ensuring that mapping based applications are […]

ENCRYPTION SAFE H ARBOURS AND D ATA BREACH N OTIFICATION LAWS Mark Burdon a, Jason Reid a and Rouhshi Low a ABSTRACT Data breach notification laws require organizations to notify affected persons or regulatory authorities when an unauthorized acquisition of personal data occurs. Most laws provide a safe harbour to this obligation if acquired data […]

DRAFT – PUBLISHED IN WINTER 2002 -2003 1 Cookies, The Constitution, and The Common Law: A Framework for the Right of Privacy on The Internet M ATTHEW C. KECK * That the individual shall have the full protection in person and in property is a principle as old as the common law; but it has […]

1 PRESERVING IDENTITIES: PROTECTING PERSONAL IDENTIFYING INFORMATION THROUGH ENHANCED PRIVACY POLICIES AND LAWS by Robert Sprague* and Corey Ciocchetti** “The common law has always recognized a man’s house as his castle . . . . Shall the courts thus close the front entrance to constituted authority, and open wide the back door to idle or […]

Future&of&Privacy&Forum&July&2015&&1″De#Identification-and-Student-Data-Understanding-De#Identification-of-Education-Records-and-Related-Requirements-of-FERPA–Appropriate”and”well/designed”student”data”use”by”schools,”families,”researchers,”and”service”providers,”greatly”enhances”teaching”and”learning.”New”technologies”linked”to”high”capacity”broadband”networks”offer”educators”and”other”stakeholders”access”to”powerful”analytical”tools,”rich”data,”and”dynamic”digital”resources,”which”can”improve”student”outcomes”and”inform”important”education”policy”reforms.”These”technology”advancements,”however,”also”invite”new”risks”for”exposing”personally”identifiable”student”data”to”unauthorized”disclosures,”misuse,”and”abuse.”In”order”to”reap”technology’s”benefits”without”encountering”these”pitfalls,”educational”agencies”and”institutions,”and”their”outside”partners,”must”develop”and”implement”more”effective”strategies”and”tools”for”promoting”students’”privacy”and”confidentiality.””””Data”de/identification”represents”one”privacy”protection”strategy”that”should”be”in”every”student”data”holder’s”playbook.”Integrated”with”other”robust”privacy”and”security”protections,”appropriate”de/identification”–”choosing”the”best”de/identification”technique”based”on”a”given”data”disclosure”purpose”and”risk”level”–”provides”a”pathway”for”protecting”student”privacy”without”compromising”data’s”value.”This”paper”provides”a”high”level”introduction”to:”(1)”education”records”de/identification”techniques;”and”(2)”explores”the”Family”Educational”Rights”and”Privacy”Act’s”(FERPA)”application”to”de/identified”education”records.1″The”paper”also”explores”how”advances”in”mathematical”and”statistical”techniques,”computational”power,”and”Internet”connectivity”may”be”making”de/identification”of”student”data”more”challenging”and”thus”raising”potential”questions”about”FERPA’s”long/standing”permissive”structure”for”sharing”non/personally”identifiable”information.”””The-Three#Legged-Stool-of-De#Identification:-Personally-Identifiable-Information,-De#identification-Strategies,-and-Data-Sharing-Purposes-&-Disclosure-Risk-Assessment–“Data”de/identification”is”a”technically”and”legally”complex”issue”with”special”nuances”across”industries”and”areas”of”law.”This”paper”narrowly”examines”the”issue”from”the”perspective”of”education”records”and”FERPA.”The”U.S.”Department”of”Education’s”Privacy”and”Technical”Assistance”Center”(PTAC)”defines”de/identification”as”the””process”of”removing”or”obscuring”any”personally”identifiable”information”from”student”records”in”a”way”that”minimizes”the”risk”of”unintended”disclosure”of”the”identity”of”individuals”and”information”about”them.”2″Understanding”PTAC’s”definition”is”critical”to”complying”with”FERPA”and”ensuring”adherence”to”de/identification”best”practice.”With”that”goal”in”mind,”this”section”introduces”three”core”student”data”de/identification”concepts”drawn”from”PTAC’s”definition”and”FERPA”(law”and”regulations):”personally”identifiable”information”(PII);”de/identification”processes;”disclosure”purpose”and”risk”assessment.”””!&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&1″Family”Educational”Rights”and”Privacy”Act,”20″U.S.C.”1232g.”2″Data!De&identification:!An!Overview!of!Basic!Terms.”U.S.”Department”of”Education”Privacy”Technical”Assistance”Center,”PTAC/GL,”Oct”2012″(updated”May”2013).&& Future&of&Privacy&Forum&July&2015&&2″Personally!Identifiable!Information!!”Educational”agencies”and”institutions,”and”their”partners,”use”de/identification”to”sever”or”obscure”connections”between”useful”education”data”and””personally”identifiable”data.””FERPA’s”sharing”prohibitions”and”requirements”(explored”later”in”the”paper)”only”apply”to”PII.”In”other”words,”non/personally”identifiable”information”may”be”shared”and”retained”without”restriction”(with”a”narrow”exception”related”to”de/identified”data”connected”to”a”record”locator).”As”a”result,”understanding”the”law’s”definition”of”PII”is”critical”to”making”determinations”about”how”student”data”may”be”used,”when,”and”by”whom.”Under”FERPA,”PII”includes,”but”is”not”limited”to:”””a)The”student’s”name”b)The”name”of”the”student’s”parent”or”other”family”members;”c)The”address”of”the”student”or”student’s”family;””d)A”personal”identifier,”such”as”the”student’s”social”security”number,”student”number,”or”biometric”record;””e)Other”indirect”identifiers,”such”as”the”student’s”date”of”birth,”place”of”birth,”and”mother’s”maiden”name;””f)Other”information”that,”alone”or”in”combination,”is”linked”or”linkable”to”a”specific”student”that”would”allow”a”reasonable”person”in”the”school”community,”who”does”not”have”knowledge”of”the”relevant”circumstances,”to”identify”the”student”with”reasonable”certainty;”or””g)Information”requested”by”a”person”who”the”educational”agency”or”institution”reasonably”believes”knows”the”identity”of”the”student”to”whom”the”education”record”relates.3″””Educational”agencies”or”institutions,”and”partner”entities,”such”as”technology”vendors,”community”based”organizations,”or”researchers,”interested”in”using”de/identification”as”a”privacy”protection”strategy,”must”pay”particular”attention”to”the”definition’s”inclusion”of””indirect”identifiers””and””other”information.””Data”de/identification”techniques”are”used”to”remove”the”direct”identifiers”described”above,”as”well”as”indirect”identifiers”and”other”information,”which”if”left”unaddressed,”could”be”used”to”identify”individual”students.”Other”examples”of”indirect”identifiers”include”race,”religion,”weight,”activities,”employment”information,”medical”information,”education”information,”and”financial”information.4″””Data!De&Identification!Techniques!!!!!Data”de/identification”–”removing”or”obscuring”PII”/”begins”with”eliminating”all”direct”student”identifiers”from”an”education”record,”but”education”agencies”and”institutions,”and”other”data”holders,”must”take”further”steps”to”ensure”that”indirect”identifiers”or”other”information”do”not”enable”an”unauthorized”actor”from”determining”a”student’s”identity.”These”further”steps”involve”using”sophisticated”mathematical”and”statistical”de/identification”techniques,”including”&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&3&FERPA,”10″U.S.C.”1232g;””34″CFR”§”99.3.”&4″See”Privacy”and”Technical”Assistance”Online”Glossary:&http://ptac.ed.gov/glossary.”Last”visited,”April”12,”2015.& Future&of&Privacy&Forum&July&2015&&3″leveraging”technology”to”ensure”the”methods”are”accurately”and”comprehensively”applied”across”large”and”complex”data”sets.”Selection”of”an”appropriate”de/identification”strategy”will”vary”based”on”specific”context,”including”whether”it”will”be”applied”to”individual”level”data”(information”collected”and”recorded”separately”for”each”student)”or”aggregate”data”(data”combined”from”several”measurements).”The”former”requires”much”more”robust”protections.”””The”U.S.”Department”of”Education’s”PTAC”provides”helpful”guidance”materials,”including”case”studies,”that”provide”detailed”information”about”de/identification”approaches,5″but”common”methods”include”the”following”strategies.6″”See”Addendum”A”for”high”level”examples”of”each”technique.”””Blurring-Reducing”the”precision”of”disclosed”data”to”minimize”the”certainty”of”individual”identification.”For”example”converting”continuous”data”elements”into”categorical”elements”that”subsume”unique”cases.””Perturbation-Making”small”changes”to”the”data”to”prevent”identification”of”individuals”from”unique”or”rare”population”groups.””For”example,”swapping”data”among”individual”cells”to”introduce”uncertainty.””Suppression-Removing”data,”for”example”from”a”cell”or”row,”to”prevent”the”identification”of”individuals”in”small”groups”or”those”with”unique”characteristics.””Usually”requires”suppression”of”non/sensitive”data.”””Sharing!Purpose!&!PII!Disclosure!Risk!assessment!!”Educational”agencies”and”institutions”planning”to”use”de/identification”techniques”to”enable”unconsented”data”sharing”–”in”instances”when”a”FERPA”disclosure”exception”does”not”apply”/”must”make”a””reasonable”determination”that”the”student’s”identity”is”not”personally”identifiable”because”of”unique”patterns”of”information”about”the”student”whether”through”single”or”multiple”releases,”and”taking”into”account”other”reasonably”available”information.”7″The”standard”for”making”this”determination”is”discussed”later”in”the”paper,”but”neither”FERPA,”nor”the”U.S.”Department”of”Education’s”FERPA”regulations,”provide”a””safe”harbor””listing”specific”steps”that”lead”to”appropriate”de/identification.”Instead,”federal”policy”provides”a”standard”for”making”case/by/case”judgments”of”PII”disclosure”risk”at”the”educational”agency,”institution,”or”approved”party”level.8″This”case/by/case”approach”means”that”the”list”of”indirect”identifiers”that”must”be”removed”or”obscured”to”achieve”appropriate”de/identification”will”likely”vary”by”circumstance.””””&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&5&Privacy”and”Technical”Assistance”Center:”http://ptac.ed.gov.”For”example,”Frequently!Asked!Questions!on!Disclosure!Avoidance,”PTAC/FAQ/2,”October”2012″(updated”May”2013),”Data!De&identification:!An!Overview!of!Basic!Terms,”PTAC/GL,”Oct”2012″(updated”May”2013),”Case!Study!#5:!Minimizing!Access!to!PII:!Bet!Practices!for!Access!Controls!and!Disclosure!Avoidance!Techniques,”PTAC/CS/5,”October”2012.”&6&See”also,”Federal”Committee”on”Statistical”Methodology’s”Statistical”Policy”Working”Paper”22″Report”on”Statistical”Disclosure”Limitation”Methodology,”(73″Fed.”Reg.”74806/35,”Dec”9,”2008).”7″73″FR”73833,”December”9,”2008.&8″73″FR”74834,”December”9,”2008.” Future&of&Privacy&Forum&July&2015&&4″Selecting”an”appropriate”de/identification”method”depends”in”part”on”examining”the”planned”data”sharing”purpose.”The”data”sharing”purpose”and”de/identification”strategy”must”be”compatible.9″For”example,”researchers”interested”in”examining”students’”performance”over”time”might”require”access”to”detailed,”accurate”academic”information”spanning”several”years”(limiting”use”of”de/identification”techniques”that”diminish”a”data’s”validity).”Researchers”studying”a”student”cohort’s”growth”toward”a”state’s”college”and”career”ready”standards”using”a”specific”pedagogy,”for”example,”would”not”be”able”to”use”data”de/identified”using”a”technique”that”limits”the”data’s”reliability”and”validity.”(Alternatively,”this”type”of”longitudinal”research”might”be”conducted”using”de/identified”data”linked”to”a”record”locator”to”enable”the”originating”educational”agency”or”institution”to”provide”de/identified”data”for”the”same”students”over”time.”Use”of”such”a”locator”does”not”render”the”data””personally”identifiable””under”FERPA,”but”it”does”trigger”special”requirements.)”Conversely,”data”shared”for”purposes”that”require”less”data”precision”and”accuracy,”such”as”software”training”or”technology”research”and”development,”could”use”much”more”aggressive”de/identification”strategies,”such”as”using”techniques”that”replace”sensitive”information”with”inauthentic”or”modified”data.”””Please”note,”using”de/identification”techniques”as”a”privacy”tool”does”not”always”involve”removing”all”PII,”but”in”situations”when”PII”remains”part”of”a”given”data”set”(i.e.”where”the”data”has”not”been”completely”de/identified),”unconsented”sharing”may”only”occur”with”consent”or”consistent”with”an”appropriate”FERPA”exception.”For”example,”an”educational”agency”or”institution”sharing”PII”under”a”qualified”FERPA”exception”may”wish”to”use”de/identification”techniques”to”minimize”PII”released”to”an”outside”entity,”even”though”they”may”lawfully”share”a”range”of”student”level”information.”To”be”more”specific,”a”researcher”might”conduct”a”study”that”requires”a”discrete”list”of”indirect”identifiers”that”together”could”lead”to”the”student’s”identification,”such”as”a”student’s”age,”race”and”family”financial”information,”but”not”requiring”other”PII”found”in”the”same”education”records.”In”such”an”instance,”these”three”pieces”of”personally”identifiable”student”data”–”and”other”information”attached”them”/”would”remain”subject”to”FERPA’s”disclosure”limitations”and”other”requirements,”but”de/identification”techniques”(e.g.,”suppression)”could”provide”additional”protection”for”the”student”by”removing”data,”for”example”from”a”cell”or”row,”unnecessary”to”the”study.”Researchers”lawfully”using”PII”in”this”context”and”other”cases,”however,”must”completely”de/identify”any”report”or”other”information”before”releasing”it”to”the”public”or”other”parties,”including”other”researchers.10″””Entities”planning”to”use”de/identification”techniques”must”mitigate”the”risk”of”exposing”the”identity”of”individual”students.”Therefore,”after”examining”the”requirements”of”a”given”data”sharing”purpose,”education”data”holders”must”also”assess”the”risks”associated”with”their”planned”disclosure,”including”considering”past”data”releases”(the”risk”of”re/identification”is”cumulative),”sample”size,”the”nature”of”the”data”recipient,11″whether”the”data”will”be”further”shared”or”made”&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&9&Data!De&identification:!An!Overview!of!Basic!Terms.”U.S.”Department”of”Education”Privacy”Technical”Assistance”Center,”PTAC/GL,”Oct”2012″(updated”May”2013),”p.”4.&10″73″FR”74834,”December”9,”2008.””11″The”Department”of”Education”has”said””there”is”no”statutory”authority”in”FERPA”to”modify”the”prohibition”on”disclosure”of”personally”identifiable”information”from”education”records,”or”the”exceptions”to”the”written”consent”requirement,”based”on”the”track”record”of”the”party,”including”journalists”and”researchers,”in”maintaining”the”confidentiality”of”information”from”education” Future&of&Privacy&Forum&July&2015&&5″public,”and”other”contextual”conditions.12″More”aggressive”de/identification”strategies”are”required”in”situations”when”the”student”data”is”potentially”at”greater”risk”of”re/identification.”””For”example,”de/identified”data”shared”for”a”specific”purpose”with”a”trusted”public”or”private”entity”such”as”a”state”department”of”education,”institution”of”higher”education,”or”professional”vendor”with”strict”legal”and”contract”protections”(e.g.,”an”agreement”with”strict”re/disclosure”limitations),”might”be”less”likely”to”be”widely”available”later”(decreasing”the”re/identification”threat”associated”with”cumulative”data”releases),”compared”for”example”to”annual”school”or”district”performance”data”posted”directly”to”a”public”website”to”comply”with”federal”and”state”accountability”requirements.”Why”is”greater”public”availability”of”a”properly”de/identified”data”set”a”potential”problem?”In”some”cases,”de/identified”data”might”be”subject”to”nefarious”comparisons”with”other”data”sets”(e.g.,”with”widely”available”student””directory”information”)”or”other”attempts”to”reveal”PII.”When”data”enters”the”public”domain,”it”could”be”exposed”to”cutting/edge”tools”and”techniques”designed”to”compare”the”de/identified”data”to”other”publicly”available”data”sets”and”thus”reveal”a”students’”identity”(the”FERPA”implications”of”such”a”breakthrough”are”discussed”further”below).””Although”experts”disagree”about”the”extent”to”which”new”technologies”and”techniques”can””back”map””de/identified”data”to”reveal”a”student’s”identity,”a”serious”statistical”analysis”that”ensures”all”direct”and”indirect”identifiers”have”been”removed”can”be”performed”to”ensure”any”re/identification”risk”is”remote.””””In”short,”prudent”student”data”holders”should”consider”using”–”in”light”of”new”data”mining”and”comparison”techniques”that”might”be”more”effective”than”is”commonly”accepted”–”the”most”aggressive”de/identification”strategies”possible”when”data”will”be”made”public”or”shared”widely.””When”data”is”shared”with”limited”restricted”parties”under”strong”controls”and”under”a”FERP”exception,”a”combination”of”technical,”administrative”and”contractual”controls”will”be”appropriate”for”reasonable”de/identification”measures”that”may”preserve”greater”utility”of”the”data.””Application-of-FERPA-to-De#Identified-Records–“As”a”general”rule,”FERPA”prohibits”the”disclosure”of”education”records”containing”personally”identifiable”student”data”without”parent”or”eligible”student”consent.13″Therefore,”the”release”of”education”records”that”have”been”appropriately”de/identified”–”purged”of”direct”and”all”necessary”indirect”identifiers”in”a”given”context”/”is”not”considered”a””disclosure””under”FERPA,”since”by”definition”such”records”do”not”contain”PII.14″”Properly”de/identified”student”data”thus”may”be”shared”without”limitation”under”FERPA”(although”other”federal”and”state”privacy”laws”may”apply).”Furthermore,””de/identified”information”from”education”records”is”not”subject”to”any”&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&records”that”they”have”received.””(73″FR”74834).””Nonetheless,”the”recipients’”identity”should”likely”be”considered”among”other”variables”in”each”risk”assessment.”12″Frequently!Asked!Questions!–!Disclosure!Avoidance,!p.”4,”PTAC/FAQ/2,”Oct”2012″(updated”May”2013).”p.2/3&13″20″U.S.C.”1232g(b)(1)”14″34″CFR”99.31(b)(1)” Future&of&Privacy&Forum&July&2015&&6″destruction”requirements”because,”by”definition,”it”is”not”‘personally”identifiable”information.”15″The”Department”has”said,”however,”a”party”releasing”de/identified”student”data”might”mitigate”risks”associated”with”future”data”releases”by”independently”requiring”data”destruction”in”some”circumstances.16″””There”is”one”important”exception,”however,”to”FERPA’s”unconsented”sharing”exception”for”de/identified”data.”De/identified”data”coupled”with”a”record”code”or”locator”by”an”educational”agency”or”institution”–”allowing”it”to”be”matched”later”to”the”record”source”/”may”only”be”shared”for”education”research.”Although”the”Department’s”regulations”and”guidance”do”not”specifically”discuss”the”question,”it”appears”that”educational”agencies”or”institutions”may”select”any”qualified”third”party”to”conduct”research”under”this”provision,”but”all”secondary”(non/research)”uses”of”de/identified”data”with”a”record”locator”are”prohibited.”Furthermore,”the”data”sharing”entity”may”not”disclose”information”about”how”it”generated”and”assigned”the”record”code,”or”other”information”that”might”allow”a”data”recipient”to”identify”a”student”based”on”the”record”code.”Lastly,”the”record”code”must”not”be”based”on”a”student’s”social”security”number”or”other”personal”information.17″Such”a”data”set”remains”categorized”as””de/identified,””and”may”thus”be”shared”without”parent”or”eligible”student”consent,”but”unlike”other”de/identified”data”it”may”only”be”shared”for”the”research”purpose”specified”to”the”educational”agency”or”institution,”consistent”with”the”other”requirements”described”above.””””Before”such”data”sharing”can”occur,”however,”the”education”record”must”be”properly”de/identified.”As”referenced”above,”the””releasing”party”is”responsible”for”conducting”its”own”analysis”and”identifying”the”best”methods”to”protect”the”confidentiality”of”information”from”education”records”it”chooses”to”release.”18″This”determination”depends”on”FERPA’s”disclosure”risk”assessment”standard.”This”standard”asks”whether”a””reasonable”person”in”the”school”community”who”does”not”have”personal”knowledge”of”the”relevant”circumstances””could”use”the”released”data,”and”other”publicly”available”data,”to”identify”an”individual”student”with””reasonable”certainty.”19″This”standard”extends”to”possible”data”holders”beyond”the”literal”school”community.””The”Department”of”Education”does”not”require”educational”agencies”and”institutions”to”use”specific”data”disclosure”avoidance”techniques”to”achieve”this”standard,”and”stated”in”a”recent”rulemaking,””it”is”not”possible”to”prescribe”or”identify”a”single”method”to”minimize”the”risk”of”disclosing”personally”identifiable”information”that”will”apply”in”every”circumstance…”20″The”Department”has”also”said””determining”whether”a”particular”set”of”methods”for”de/identifying”data”and”limiting”disclosure”risk”is”adequate”cannot”be”made”without”examining”the”underlying”data”sets,”other”data”that”have”been”released,”publicly”available”directories”and”other”data”that”are”linked”or”linkable”to”the”information”in”questions.21″In”other”words,”the”party”releasing”data”&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&15&73″FR”15585,”March”24,”2008&16&73″FR”74835,”December”9,”2008&17″34″CFR”99.31(b)(2)(i)/(iii).”18″73″FR”74835,”December”9,”2008.””19″34″CFR”§”99.3,”34″CFR”§99.31(b)(1)”20″73″FR”74835,”December”9,”2008″21″Ibid”at”74835& Future&of&Privacy&Forum&July&2015&&7″must”perform”a”context”specific”analysis”and”identify”the”best”method”for”protecting”student”information”subject”to”disclosures.”Proper”application”of”the”accepted”mathematical”and”statistical”de/identification”strategies”described”earlier”in”the”paper”meet”this”legal”standard”in”many”instances,”but”by”law”each”sharing”context”must”be”independently”analyzed”against”the”Department’s”reasonableness”standard.22″””Some”experts”have”argued”that”given”recent”cases”where”researchers”have”leveraged”access”to”other”publicly”available”data”sets”to”identify”specific”individuals,”absolute”data”de/identification”may”be”impossible,”or”at”a”minimum,”increasingly”difficult.23″In”light”of”this”uncertainty,”data”sharing”parties”should”very”carefully”analyze”each”proposed”disclosure”of”de/identified”data”against”FERPA’s”reasonableness”standard”and”also”consider”using”contracts”that”specify”protections”–”above”and”beyond”FERPA””/”that”could”further”minimize”the”risk”of”re/identification.””””De#Identified-Data:-Retention-and-Destruction-“FERPA”permits”third”party”data”holders,”including”vendors,”to”retain”and”use”appropriately”de/identified”data”–”so”long”as”it”is”not”associated”with”a”record”locator”/for”any”secondary”purpose.””Furthermore,”FERPA”does”not”describe”how”de/identified”data”should”be”managed,”including,”as”described”above,”when”and”how”the”data”should”be”destroyed.”Vendors”and”other”third”party”holders”must,”however,”ensure”that”a”given”de/identified”data”set”is”not”subject”to”relevant”contract”terms,”or”other”Federal,”state,”and”local”privacy”laws”and”regulations,”which”might”contain”more”stringent”data”retention”or”destruction”requirements.24″For”example,”personal”data”subject”to”the”Children’s”Online”Privacy”Protection”Act”may”only”be”retained”so”long”as”is”necessary”to”fulfill”the”purpose”for”which”it”was”collected,”and”COPPA”covered”entities”must”delete”the”information”using”reasonable”measures”to”protect”against”its”unauthorized”access”or”use.25″”””Although”FERPA”does”not”govern”the”use,”retention”and”destruction”of”properly”de/identified”data,”third”parties”should”have”sound”policies”–”guided”by”National”Institute”of”Standards”and”Technology”or”PTAC”best”practice”recommendations”/”addressing”these”issues.”This”internal,”independent”step”includes”ensuring”that”de/identified”data”is”destroyed”when”it”is”no”longer”needed,”in”order”to”minimize”re/identification”risks”associated”with”possible”future”efforts”to”compare”and”link”the”data”with”other”data”sets.”Data”holders”must”also”ensure”that”they”take”proper”actions”to”destroy”data.”Simply”deleting”data”is”not”sufficient”in”most”cases”and”PTAC’s”data”destruction”best”practices”provide”helpful”guidance.”PTAC”recommends”that”data”holders””make”risk/based”decisions”on”which”[destruction]”method”/”[e.g.”clearing,”purging,”or”destroying”data]”/””is”most”appropriate”based”on”the”data”type,”risk”of”disclosure,”and”the”impact”if”that”data”were”to”be”disclosed”without”authorization.”26″The”data”de/identification”method”used”to”remove”&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&22″34″CFR”99.31.(b)(1).”See”also,”PTAC”Frequently!Asked!Questions!–!Disclosure!Avoidance,!p.”4,”PTAC/FAQ/2,”Oct”2012″(updated”May”2013).””23″Broken!Promises!of!Privacy:!Responding!to!the!Surprising!Failure!of!Anonymization,”Paul”Ohm,”University”of”Colorado”Law”School,”UCLA”Law”Review,”Vol.”57,”p.”1701,”2010″.-24″Privacy”and”Technical”Assistance”Center,”Best!Practices!for!Data!Destruction,!p.”5,”PTAC/IB/5,”May”2014.””25″16″C.F.R.”§”312.10.”26″PTAC”Best”Practices”for”Data”Destruction,”p.”5.”” Future&of&Privacy&Forum&July&2015&&8″PII”from”a”data”set”should”be”a”central”factor”in”making”this”determination.”Data”holders”seeking”additional”guidance”on”proper”destruction”strategies”should”consult”recommendations”made”by”the”National”Institute”of”Standards”and”Technology”and”other”expert”sources.27″”Conclusion-De/identification”offers”an”important”tool”for”educational”agencies,”institutions”and”their”partners”seeking”to”maximize”student”data’s”potential”value”to”improving”teaching”and”learning,”while”also”carefully”protecting”student”privacy”and”confidentiality.”Proper”data”de/identification”requires,”however,”deep”technical”knowledge”and”expertise”and”adherence”to”industry”best”practice.””Therefore,”student”data”holders”should”not”attempt”to”de/identify”student”data”sets”without”competent”support.”They”should”also”consult”competent”legal”counsel”to”ensure”that”their”data”management”policies”and”practices”–”including”de/identification”strategies”/”comply”with”FERPA”and”all”other”relevant”federal,”state,”and”local”laws”and”requirements”potentially”applicable”to”the”data”they”manage.”&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&27″National”Institute”of”Standards”and”Technology”(NIST)”Special”Publication”800/88″Rev.”1:”Guidelines”for”Media”Sanitization.”December”2014.””& !Illustration!of!Common!De1Identification!Measures!in!Aggregate!Data!Sets!!!!!!!!!!!!!!!!!!!!!!Joan’s!Director!Identifiers!Student!Name:!Joan!Smith!Students!Parents:!John!Smith!&!Jackie!Smith!Address:!0000!00th!Street,!!Washington,D.C.!Student!Number:!4444!Social!Security!Number:!555C555C555!!Joan’s!Indirect!Identifiers!Data!of!Birth:!11/01/2000!Race:!Alaska!Native!Gender:!Female!Place!of!Birth:!Washington,!D.C.!Family!Income:!$85,000!GPA:!3.75!!!!All!Direct!Identifiers!Removed!Joan’s!Indirect!Identifiers!!Data!of!Birth:!2000!Race:!Unique!Characteristic!Removed!Gender:!Female!Mother’s!Maiden!Name:!Unique!Characteristic!Removed!Place!of!Birth:!MidCAtlantic!Family!Income:!$50,000!C!$100,000!GPA:!3.5!–!4.0!Mike’s!Indirect!Identifiers!!Data!of!Birth:!1999!!Race:!Unique!Characteristic!Removed!Gender:!Female!Mother’s!Maiden!Name:!Unique!Characteristic!Removed!Place!of!Birth:!Midwest!Family!Income:!$50,000!C!$100,000!GPA:!3.5!–!4.0!Joan’s!Indirect!Identifiers!!Data!of!Birth:!2000!Race:!Unique!Characteristic!Removed!Gender:!Male!Mother’s!Maiden!Name:!Unique!Characteristic!Removed!Place!of!Birth:!Northeast!Family!Income:!$50,000!C!$100,000!GPA:!3.5!–!4.0!!!All!Direct!Identifiers!Removed!Joan’s!Indirect!Identifiers!!Data!of!Birth:!11/01/2000!Race:!Alaska!Native!Gender:!Female!Place!of!Birth:!Washington,!D.C.!Family!Income:!$85,000!GPA:!3.75!!!!All!Direct!Identifiers!Removed!Joan’s!Indirect!Identifiers!!Data!of!Birth:!2000!Race:!Minority!Gender:!Female!Mother’s!Maiden!Name:!Johnson!Place!of!Birth:!MidCAtlantic!Family!Income:!$50,000!C!$100,000!GPA:!3.5!–!4.0!Raw$Individual$Student$Data$in$Aggregate$Data$Table$!Redacted$Individual$Student$Level$Data$in$Aggregate$Data$Table$$Blurring$(Reducing$Data$Precision$including$$Using$Broader$Categories)$$Suppression$(Removing$Data$from$a$Cell$or$Row)$Perturbation$(Small$Data$Changes,$including$through$$Swapping$Data$among$Cells)$$$

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