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Observed versus Disclosed Provenance Challenges in Observed Provenance Conclusions:|)%" kImagine & Every computational object you created had complete provenance. You could identify the source and history of every object you ever received. You could query this complete history. All these features worked regardless of what tools you used. D@M'< g(What is Automatic Provenance Collection?0A system that makes all this happen. Requires no user intervention. Provenance collection is the default. Works seamlessly and unobtrusively while you work using whatever tools you normally use. Examples Is this memo based upon confidential data? Why do these two invocations produce different results? dd%&b  dW'Provenance-Aware Storage Systems (PASS)0Storage systems (e.g., file systems) in which provenance is a first class entity. Provenance: is generated and maintained as transparently as possible. can be indexed and queried. will be created from objects imported from non-PASS sources. is maintained in the presence of deletes, copies, renames, etc.H^ZZ^V=? aCollecting Provenance  % sort a > b fork open b (W) exec  sort a open a (R) read a write b close a close b *`!ZRl Observed vs Disclosed Provenance Observed provenance: Extract provenance from stream of events System does not control events Disclosed provenance: Application or user identifies provenance Provenance disclosed to database Examples: User annotations Provenance-aware applications Workflow specifications ZHZZUZGZZHU/ i!Challenges in Observed Provenance5Granularity Versions Cycles False provenance SecurityD6  p GranularitytAutomatic systems track provenance at the granularity that they see (files, tuples, & ). Users think about provenance in coarser, semantically meaningful terms (experiments, projects, workflows). This mismatch leads to problems: Users want to know about  gcc 4.0, not its change history from the beginning of time.:WXk!W ,L:qVersionsProvenance + mutable data = versioning. Consider: Open A, read A, write A, close A A s provenance changed. We implicitly created a new version. The provenance system must preserve versions. Avoiding excessive versions leads to & l2!( ! %.&rCyclesCannot really happen: A cannot be both B s parent and B s child. Violate causality. So, how do they happen? Open A, read A, write A, close A A is its own parent, unless you create A . But what if (read A, write A) is in a loop? One version per loop iteration? Ideally, one version for entire loop. How do you identify the loops?l!WeA!  +, &  $$v Cycles (2)  u Cycles (3)dThe cycles can be arbitrarily complex. Why do they happen in observed systems and not disclosed systems? In disclosed systems, the disclosures are made by someone who knows how to do the grouping. Cycle detection/breaking is automatically doing what the human is doing when s/he decides where and what to disclose. Our algorithm is not as smart as people. \iZZ'B>  v*sFalse Provenance(Recorded provenance that did not affect the output. Examples: Many utilities read one or more start-up files, but not all those startup files affect every output. A workflow might specify an input file that is only sometimes used. Neither observed nor disclosed systems can avoid this completely.6>B>BtSecurity Provenance and the data it describes have different security characteristics. Protecting provenance requires protecting: Attributes (e.g., command line, environment) Relationships (e.g., ancestors) Composition of security is hard. Unfortunately, it is a requirement.byMEN+- !#j ConclusionseAutomatic collection is useful. It is also challenging. There is a ton of interesting research to do.0f - o Questions!Thanks to: Network Appliance IBM Research The Harvard PASS Team: Uri Braun, Simson Garfinkel, David Holland, Kiran-Kumar Muniswamy-Reddy Participants in the October, 2005 PASS Workshop Our users! http://www.eecs.harvard.edu/~margo/syrah ZZ*!Z   H0 )bL  J!/1>?AB C D EGHIJKLNPn  0` ` ̙33` 333MMM` ff3333f` f` f` 3>?" dd@$|?" dd@  " @ ` n?" dd@   @@``PR    @ ` ` p>>  (    6 P  T Click to edit Master title style! !  0   RClick to edit Master text styles Second level Third level Fourth level Fifth level!     S  0  `p  *  0H `   @*p  C :A"logo-transparent"0(v  ^fA޽h @ ?redback 3f̙33 Default Design'  0  9(    6蹒 p  T Click to edit Master title style! !  0ȼ  P`  W#Click to edit Master subtitle style$ $P  C A"po v  ^fA޽h @ ?redback 3f̙33 0 zr`P (  P P 08& P   P*   P 00+    R*  d P c $ ?    P 0.  @  RClick to edit Master text styles Second level Third level Fourth level Fifth level!     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3f̙33___PPT10i.rN+D=' O= @B +P  0    tq (  tr t S l P    F `2 t 0 P  t <# `( .$ t 0$- 2 7P$2 t 66  0  9A$ t S BC@DE(FjJ (PP8@ @   S" P    t <@   <Read A2  t 6J  0  <A $  t S BCpDE(FjJ p0PHX`  @   S"  8  t < ]   =Write A t <|.o ,$ 0 JRead A ?  @ t C B`C@DE(FAjJ PX`PP@(((@ @   S"  ` ,$D 0H t 0޽h ? 3f̙33___PPT10.vo'+)|D' O= @B DF' = @BA?%,( < +O%,( < +DA' =%(D' =%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*t%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*t%(+8+0+t0 + K 0L0 D(  Dl D C wcP  c l D C wc c H D 0޽h ? 3f̙33___PPT10i.r5k+D=' O= @B + C 0L0 (@(  00q" (l ( C @cP  c r ( S c c H ( 0޽h ? 3f̙33___PPT10i.rF+D=' O= @B + B 0)L0 ,(  ,l , C cP  c l , C c c H , 0޽h ? 3f̙33___PPT10i.rF+D=' O= @B + L 0[L0 (  l  C ԗcP  c l  C c c H  0޽h ? 3f̙33___PPT10i.r+D=' O= @B + N 0/L0 @(  l  C P   l  C   H  0޽h ? 3f̙33___PPT10i.rP+D=' O= @B + 0 PhS(  h^ h S P     h c $DP @   IGive the history hereH h 0޽h#6 ? ̙33zW 0 :2 H(  Hd H c $P    c& H s *|cP @  c^___PPTMac1180   |namdtTimes New Roman&Monotype Typography  <___PPT10R___PPT94, DProvenance is merely a special kind of query over which we provide better query capabilities than find | grep. We ve built such a system -- the V1 PASS Prototype &o2i6H H 0޽h#6 ? ̙33g 0 x( ek,lD va R  3 P    c~  C LcP @  c  H  0޽h#6 ? ̙3380___PPT10.r0Sk 0 <4( dnni ght R  3 P    c:  C cP @  c Imagine that from the moment you say down at your computer to the moment you left, every single thing that you did and every object that you created and modified was maintained with full provenance.H  0޽h#6 ? ̙3380___PPT10.r*k l 0   ( d@ R  3 P    p  C pP @  p^___PPTMac1180   |namdtTimes New Roman&Monotype Typography  8___PPT10N___PPT90( 6PASS is most definitely an observed system -- when we talk about automatic collection, we re talking about observed systems. Advantages of observed: unlimited toolset, there even when you didn t request it, no need to modify applications Many of the challenges I ll discuss result from the fact that as an observer, you know much less about the intention and semantics of the operations that are happening. The line isn t necessarily clear, but if the intended provenance is explicitly provided (e.g., a makefile, a workflow), we consider it disclosed, because there is an act of disclosure regarding the intention of the provenance. Acknowledge the grey line here&H  0޽h#6 ? ̙3380___PPT10.r$jt 0 JB0(  0R 0 3 P    pH 0 C ЃpP @  p^___PPTMac1180   |namdtTimes New Roman&Monotype Typography  <___PPT10R___PPT94, Use the employee review example and/or the newspaper correspondent and his sources. Also a requirement to compose provenance security with data security. &TEH 0 0޽h#6 ? ̙3380___PPT10.r2H(8s 0 8H(  ,>N^`< 8R 8 3 P    p 8 C XpP @  p ___PPTMac11     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography  ___PPT10ld    ___PPT9     $False provenance can happen in many systems. Let s say that we have a simulation program that takes a calibration file and some raw data. Great -- a workflow system OR a PASS might generate the dependencies shown. Now, let s say that we modify the simulation so that if the data is already calibrated, it ignores the calibration. This information is known ONLY inside the simulator. Both a workflow system and a PASS are going to create the dependency between calibration file and output, even though it may be spurious. We call this false provenance. An automatic system suffers more than other systems because we have no semantic knowledge. We are currently talking with folks who do dynamic flow analysis to see if we can improve our situation here. With the right dynamic Runtime system, we may be able to do better than you do in any kind of workflow system, because we can do even finer grain tracking.-]L t [$$((,,00H 8 0޽h#6 ? ̙3380___PPT10. r` p 0 vn<( ek,lD va <R < 3 P    pt < C X8pP @  p Granularity problems can exist in disclosed systems too: a workflow might update a database, but the provenance system may not know enough about tuples in the database to tag them individually (but there are projects that are dealing with this) Trio, SDB Talk about file system  not Database We do: record low-level; allow annotations to create higher-level labelsH < 0޽h#6 ? ̙3380___PPT10. rs q 0 ~ v @ (  @R @ 3 P    p|  @ C PpP @  p___PPTMac11   |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography     |namdtTimes New Roman&Monotype Typography  T___PPT104,___PPT9d\ PPASS: we function very explicitly in terms of versions. Versions are represented by new logical chunks of provenance called pnodes. In a perfect world, we capture every collection of semantically meaningful events into a new version. In practice, we don t *know* what events are semantically meaningful. We use open-> close as a first approximation. This works in most of the easy cases. In fact, I think it works in all the standard workflow cases. Versioning file systems struggle with the same challenges: Also  they are preserving data; we want to preserve causality Version pumping (big and inconvenient)Dhfv& }H @ 0޽h#6 ? ̙3380___PPT10.re 0 tlL( P0( LR L 3 P    cr L # |cP @  c  H L 0޽h#6 ? ̙3380___PPT10.rIa 0 E= P( \ #1 PR P 3 P    pC P C $pP @  p Key insight: the system observes the sequence of system calls and extracts provenance from them. In fact, this is an instance of a general class of provenance systems that we call Observed Provenance SystemsH P 0޽h#6 ? ̙3380___PPT10.rIi 0 tl0T( \ 2@? TR T 3 P    pr T # pP @  p  H T 0޽h#6 ? ̙3380___PPT10.rI5r 0 @XE( \ @I XR X 3 P    p X C papP @  p SGrab figure from USENIX paperH X 0޽h#6 ? ̙3380___PPT10.rIGu 0 P\W( \ IY \R \ 3 P    p \ C TpP @  p e/Ancestry is a DAG not a tree We know its broken)H \ 0޽h#6 ? ̙3380___PPT10.rIj 0 tl``( Pk `R ` 3 P    pr ` # pP @  p  H ` 0޽h#6 ? ̙3380___PPT10.rIo 0 tlh(  hR h 3 P    pr h # pP @  p  H h 0޽h#6 ? ̙3380___PPT10.rIr yҎ3+d 6 BӖPS.;=`U@)1,`_1INfk&xz}D@o<1Oh+'0T hp    $,(PASS: Provenance-Aware Storage SystemsMargo Seltzermargo100Microsoft PowerPoint@@@{@ oGSg  )'    """)))UUUMMMBBB999|PP3f333f3333f3ffffff3f̙3ff333f333333333f33333333f33f3ff3f3f3f3333f33̙33333f333333f3333f3ffffff3f33ff3f3f3f3fff3ffffffffff3ffff̙fff3fffff3fff333f3f3ff3ff33f̙̙3̙ff̙̙̙3f̙3f333f3333f3ffffff3f̙3f3f3f333f3333f3ffffff3f̙3f3ffffffffff!___www@4'A x(xKʦ 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՜.+,0`    On-screen Show  Times New Roman Arial BlackArialCourier Courier NewDefault Design*Issues in Automatic Provenance CollectionOutline Imagine )What is Automatic Provenance Collection?(Provenance-Aware Storage Systems (PASS)Collecting Provenance !Observed vs Disclosed Provenance"Challenges in Observed Provenance Granularity VersionsCycles Cycles (2) Cycles (3)False Provenance Security Conclusions Questions!  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