`
`___________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`___________
`
`CLOUDFLARE, INC. AND SONICWALL INC.
`Petitioners
`
`v.
`
`SABLE NETWORKS, INC.
`Patent Owner
`
`___________
`
`Case IPR2021-00909
`Patent No. 8,243,593
`___________
`
`
`
`PETITION FOR INTER PARTES REVIEW
`
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`TABLE OF CONTENTS
`
`V.
`
`B.
`
`C.
`
`List of Exhibits ....................................................................................................... vii
`Mandatory Notices Under 37 C.F.R. § 42.8 .......................................................... xii
`Real Party-in-Interest (37 C.F.R. § 42.8(b)(1)) ........................................... xii
`Related Matters (37 C.F.R. § 42.8(b)(2)) .................................................... xii
`Lead and Back-Up Counsel (37 C.F.R. § 42.8(b)(3)) ................................ xiii
`Service Information (37 C.F.R. § 42.8(b)(4)) ............................................ xiii
`Introduction ..................................................................................................... 1
`I.
`Grounds for Standing ...................................................................................... 1
`II.
`III. Technical Background .................................................................................... 1
`IV. The Challenged Patent .................................................................................... 6
`A. Overview of the ’593 Patent ................................................................. 6
`B.
`Prosecution History .............................................................................. 9
`C.
`Person of Ordinary Skill in the Art .................................................... 11
`Claim Construction ....................................................................................... 11
`A.
`“means for maintaining a set of behavioral statistics for the
`flow…” (claims 25 and 29) ................................................................ 12
`“means for determining…whether the flow is exhibiting
`undesirable behavior” (claim 25) ....................................................... 12
`“means for enforcing…[a/the] penalty on the flow” (claims 25
`and 32) ................................................................................................ 12
`“means for computing…a badness factor for the flow” (claim
`29) ....................................................................................................... 13
`“means for determining…a penalty to impose on the flow”
`(claim 31) ........................................................................................... 13
`“means for determining an increased drop rate to impose on one
`or more information packets belonging to the flow” (claim 37) ....... 13
`“means for imposing [an/the] increased drop rate on the flow”
`(claims 27 and 38) .............................................................................. 13
`
`D.
`
`E.
`
`F.
`
`G.
`
`
`
`i
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`I.
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`J.
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`d.
`e.
`f.
`g.
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`H.
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`“means for receiving a particular information packet belonging
`to the flow” (claims 43 and 44) .......................................................... 14
`“means for determining whether to forward the particular
`information packet to a destination” (claim 43) ................................. 14
`“means for updating […] the set of behavioral statistics to
`reflect processing of the particular information packet” (claims
`43 and 44) ........................................................................................... 14
`VI. Overview of the Prior Art ............................................................................. 15
`VII. Grounds of Unpatentability .......................................................................... 16
`A. Ground 1: Claims 1, 2, 4-7, 17, 18, 25-27, 37, and 38 Are
`Obvious over Yung ............................................................................ 17
`1. Overview: Yung Discloses a System for Classifying and
`Controlling Flows Using Behavioral Statistics ............................. 17
`2. Independent Claim 1 ..................................................................... 19
`a.
`Yung Discloses the Preamble of Claim 1 ...................... 19
`b.
`Yung Discloses the “Creating” Limitation .................... 21
`c.
`Yung Stores Payload-Content-Agnostic Behavioral
`Statistics Regardless of the Presence or Absence of
`Congestion ..................................................................... 25
`Yung Discloses the “Updating” Limitation ................... 28
`Yung Discloses the “Determining” Limitation ............. 30
`Yung Discloses the “Enforcing” Limitation.................. 33
`Yung Discloses Performing the Steps on a Router
`Without Requiring Use of Inter-Router Data ................ 34
`3. Independent Claim 2 ..................................................................... 36
`a.
`Yung Discloses the Preamble of Claim 2 ...................... 36
`b.
`Yung Discloses the Limitations of Claim 2 .................. 37
`4. Independent Claims 4 and 5 .......................................................... 37
`5. Independent Claim 25 ................................................................... 39
`a.
`Yung Discloses the Preamble of Claim 25 .................... 39
`b.
`Yung Discloses the “Means for Maintaining”
`Limitation ...................................................................... 39
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`
`
`ii
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`c.
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`d.
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`Yung Discloses the “Means for Determining”
`Limitation ...................................................................... 40
`Yung Discloses the “Means for Enforcing”
`Limitation. ..................................................................... 40
`6. Dependent Claims 6 and 26 .......................................................... 41
`7. Dependent Claims 7 and 27 .......................................................... 41
`8. Dependent Claims 17 and 37 ........................................................ 42
`9. Dependent Claims 18 and 38 ........................................................ 42
`Ground 2: Claims 9-13, 19-24, 29-33, and 39-44 Are Obvious
`over Yung and Copeland .................................................................... 43
`1. Overview: Yung Discloses a System for Classifying and
`Controlling Flows Using Behavioral Statistics, and
`Copeland Calculates a Flow-Based Concern Index ...................... 43
`2. Motivation to Combine ................................................................. 45
`3. Independent Claim 9 ..................................................................... 48
`a.
`Yung Discloses the Preamble of Claim 9 ...................... 48
`b.
`Yung Discloses the “Maintaining” Limitation .............. 48
`c.
`Yung in View of Copeland Discloses the
`“Computing” Limitation ................................................ 49
`4. Independent Claim 29 ................................................................... 51
`a.
`Yung Discloses the Preamble of Claim 29 .................... 51
`b.
`Yung Discloses the “Means for Maintaining”
`Limitation ...................................................................... 52
`Yung Discloses the “Means for Computing”
`Limitation ...................................................................... 52
`5. Dependent Claims 10 and 30 ........................................................ 53
`6. Dependent Claims 11 and 31 ........................................................ 53
`7. Dependent Claims 12 and 32 ........................................................ 54
`8. Dependent Claims 13 and 33 ........................................................ 54
`9. Dependent Claims 19 and 39 ........................................................ 55
`10. Dependent Claims 20 and 40 ........................................................ 55
`
`B.
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`c.
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`iii
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`C.
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`11. Dependent Claims 21 and 41 ........................................................ 56
`12. Dependent Claims 22 and 42 ........................................................ 57
`13. Dependent Claims 23 and 43 ........................................................ 58
`14. Dependent Claims 24 and 44 ........................................................ 59
`Ground 3: Claim 3 Is Obvious over Yung and Four-Steps
`Whitepaper ......................................................................................... 61
`1. Overview: Yung Discloses a System for Classifying and
`Controlling Flows Using Behavioral Statistics, and Four-
`Steps Whitepaper Discloses Tracking Dropped Packets .............. 61
`2. Motivation to Combine ................................................................. 62
`3. Independent Claim 3 ..................................................................... 64
`a.
`Yung Discloses the Preamble of Claim 3 ...................... 64
`b.
`Yung Discloses a Medium Storing a Data
`Structure ......................................................................... 64
`Yung Discloses the “First Field” ................................... 66
`Yung in View of Four-Steps Whitepaper Discloses
`the “Second Field” ......................................................... 66
`Yung Discloses the “Third Field” ................................. 67
`e.
`Yung Discloses the “Fourth Field” ................................ 67
`f.
`Yung Discloses the “Fifth Field” .................................. 68
`g.
`D. Ground 4: Claims 8, 14-16, 28, and 34-36 Are Obvious over
`Yung and Copeland in View of Ye .................................................... 69
`1. Overview: Yung-Copeland Discloses a System for
`Classifying Flows Using Behavioral Statistics, and Ye
`Describes a Congestion Condition ................................................ 69
`2. Motivation to Combine ................................................................. 70
`3. Dependent Claims 8, 14, 28, and 34 ............................................. 72
`4. Dependent Claims 15 and 35 ........................................................ 74
`5. Dependent Claims 16 and 36 ........................................................ 75
`VIII. Discretionary Denial Would Be Inappropriate and Inequitable ................... 75
`IX. Conclusion .................................................................................................... 80
`
`c.
`d.
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`iv
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`TABLE OF AUTHORITIES
`Federal Court Decisions
`Intri-Plex Technologies v. NHK International Corp.,
`3:17-cv-01097-EMC (N.D. Cal.) ........................................................................ 78
`Phillips v. AWH Corp.,
`415 F.3d 1303 (Fed. Cir. 2015) (en banc) .................................................... 11, 12
`Williamson v. Citrix Online, LLC,
`792 F.3d 1339 (Fed. Cir. 2015) .......................................................................... 11
`Patent Trial and Appeal Board Decisions
`Apple Inc. v. Fintiv, Inc.,
`IPR2020-00019, Paper 15 (PTAB May 13, 2020) ............................................. 77
`Apple Inc. v. Fintiv, Inc.,
`IPR2020-00019, Paper 11 (PTAB Mar. 20, 2020) ......................................passim
`Apple Inc. v. Parus Holdings, Inc.,
`IPR2020-00686, Paper 9 (PTAB Sept. 23, 2020) ............................................... 77
`HP, Inc. v. Neodron, Ltd.,
`IPR2020-00459, Paper 17 (PTAB Sept. 14, 2020)................................. 78, 79, 80
`Mylan Pharmaceuticals Inc. v. Sanofi-Aventis Deutschland GmbH,
`IPR2018-01680, Paper 22 (PTAB Apr. 3, 2019) ............................................... 78
`NHK Spring Co. v. Intri-Plex Techs., Inc.,
`IPR2018-00752, Paper 8 (PTAB Sept. 12, 2018) ................................... 76, 78, 79
`
`Sand Revolution II, LLC v. Continental Intermodal Group – Trucking
`LLC, IPR2019-01393, Paper 24 (PTAB June 16, 2020) .............................. 77, 78
`Valve Corp. v. Electronic Scripting Product, Inc.,
`IPR2019-00062, Paper 11 (PTAB Apr. 2, 2019) ......................................... 75, 76
`VMWare, Inc. v. Intellectual Ventures I LLC,
`IPR2020-00470, Paper 13 (PTAB Aug. 18, 2020) ................................. 77, 79, 80
`
`
`
`v
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`Patent No. 8,243,593—Petition for Inter Partes Review
`
`Federal Statutes
`
`35 U.S.C.
`§ 102 .............................................................................................................. 15, 16
`§ 112 .................................................................................................................... 11
`§ 315 .................................................................................................................... 78
`Federal Rules and Regulations
`37 C.F.R. § 42.100(b) .............................................................................................. 11
`
`
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`vi
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`Patent No. 8,243,593—Petition for Inter Partes Review
`
`LIST OF EXHIBITS
`
`Exhibit
`
`Description
`
`1001
`
`1002
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`1003
`
`1004
`
`1005
`
`1006
`
`1007
`
`1008
`
`1009
`
`1010
`
`1011
`
`1012
`
`1013
`
`1014
`
`1015
`
`1016
`
`U.S. Patent No. 8,243,593 (the “’593 Patent”)
`
`Prosecution history of U.S. Application No. 11/022,599, which led
`to the issuance of the ’593 Patent (“File History”)
`
`Declaration of Kevin Jeffay, Ph.D. in Support of Petition for Inter
`Partes Review of U.S. Patent No. 8,243,593
`
`Curriculum Vitae of Kevin Jeffay
`
`U.S. Patent No. 7,664,048 (“Yung”)
`
`“Four Steps to Application Performance Across the Network with
`Packeteer’s PacketShaper®,” archived by web.archive.org on
`March 17, 2003, with Affidavit of Elizabeth Rosenberg attached
`(“Four-Steps Whitepaper”)
`
`U.S. Patent No. 7,185,368 (“Copeland”)
`
`U.S. Patent No. 7,295,516 (“Ye”)
`
`U.S. Patent Publication No. 2004/0090923 (“Kan”)
`
`Gerber, A., et al., “P2P, the Gorilla in the Cable,” Proceedings of
`National Cable & Telecommunications Association, NCTA, 2003
`(“Gerber”)
`
`U.S. Patent No. 7,225,271 (“DiBiasio”)
`
`U.S. Patent No. 7,561,515 (“Ross”)
`
`Ben-Nun, M., “Taming the Peer to Peer Monster Using Service
`Control,” Fall Technical Forum (2003) (“Ben-Nun”)
`
`U.S. Patent No. 6,839,321 (“Chiruvolu”)
`
`U.S. Patent No. 7,088,678 (“Freed”)
`
`“NetEnforcerTM, QoS/SLA Enforcement for Service Providers,”
`
`
`
`vii
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`
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`Exhibit
`
`Description
`Allot Communications (2001)
`
`1017
`
`1018
`
`1019
`
`1020
`
`1021
`
`1022
`
`1023
`
`1024
`
`1025
`
`1026
`
`1027
`
`1028
`
`1029
`
`1030
`
`1031
`
`1032
`
`“PacketShaper® Features for PacketWise 5.2,” Packeteer, Inc.
`
`U.S. Patent No. 7,366,101 (“Varier”)
`
`Andrikopoulos, I., Pavlou, G., “Supporting Differentiated Services
`in MPLS Networks,” 1999 Seventh International Workshop on
`Quality of Service, including Declaration from Rachel J. Watters,
`Librarian and Director of Wisconsin TechSearch
`(“Andrikopoulos”)
`
`U.S. Patent No. 7,385,924 (“Riddle-924”)
`
`U.S. Patent No. 7,660,248 (“Duffield”)
`
`Sen, S., et al., “Accurate, Scalable In-Network Identification of
`P2P Traffic Using Application Signatures,” Proceedings of the
`13th International Conference on World Wide Web (2004) (“Sen”)
`
`U.S. Patent No. 7,313,100 (“Turner”)
`
`U.S. Patent Publication No. 2002/0186661 (“Santiago”)
`
`U.S. Patent Publication No. 2003/0118029 (“Maher”)
`
`U.S. Patent No. 7,296,288 (“Hill”)
`
`U.S. Patent No. 6,904,529 (“Swander”)
`
`U.S. Patent No. 6,385,170 (“Chiu”)
`
`U.S. Patent No. 6,934,256 (“Jacobson”)
`
`U.S. Patent No. 7,342,929 (“Bremler-Barr”)
`
`PacketShaper® System Datasheet
`
`Boniforti, C., “Securing a University’s Bandwidth with
`PacketShaper,” SANS Institute (2003) (“Boniforti”)
`
`
`
`viii
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`Exhibit
`
`1033
`
`1034
`
`Description
`
`Braden, R., Postel, J., “RFC 1009 – Requirements for Internet
`Gateways” (1987) (“Braden”)
`
`Roughan, M., et al., “Class-of-Service Mapping for QoS: A
`Statistical Signature-based Approach to IP Traffic Classification,”
`Proceedings of the 4th ACM SIGCOMM Conference on Internet
`Measurement (2004) (“Roughan”)
`
`1035
`
`1036
`
`1037
`
`1038
`
`1039
`
`1040
`
`1041
`
`1042
`
`1043
`
`1044
`
`1045
`
`1046
`
`1047
`
`U.S. Patent No. 7,027,393 (“Cheriton”)
`
`U.S. Patent No. 7,433,304 (“Galloway”)
`
`U.S. Patent No. 6,115,357 (“Packer”)
`
`Szigeti, T., “QoS Best Practices,” Cisco Systems (2004)
`(“Szigeti”)
`
`U.S. Patent No. 6,412,000 to Riddle et al. (“Riddle-000”)
`
`Long L., et al., “Differential Congestion Notification: Taming the
`Elephants,” Proceedings of the 12th IEEE International
`Conference on Network Protocols (Oct. 2004) (“Long”)
`
`Parris M., et al., “Lightweight Active Router-Queue Management
`for Multimedia Networking,” Multimedia Computing and
`Networking” (Jan. 1999) (“Parris”)
`
`U.S. Patent Publication No. 2002/0023168 (“Bass”)
`
`U.S. Application Publication No. 2002/0097719 (“Chaskar”)
`
`Bernaille, L., et al, “Traffic Classification on the Fly,” ACM
`SIGCOMM Computer Communication Review (2006)
`(“Bernaille”)
`
`U.S. Patent No. 7,782,793 (“Olesinski”)
`
`U.S. Patent No. 8,693,348 (“Wei”)
`
`Karagiannis, T., et al, “Transport Layer Identification of P2P
`Traffic,” IMC 04: Proceedings of the 4th ACM SIGCOMM
`
`
`
`ix
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`
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`Exhibit
`
`Description
`conference on Internet measurement, October 2004
`(“Karagiannis”)
`
`1048
`
`1049
`
`1050
`
`1051
`
`1052
`
`1053
`
`1054
`
`Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas
`dated May 8, 2020
`
`Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas
`dated June 18, 2020
`
`Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas
`dated July 2, 2020
`
`Seventh Supplemental Order Regarding Court Operations Under
`the Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas
`dated August 6, 2020
`
`Eighth Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas
`dated September 21, 2020
`
`Ninth Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas
`dated October 14, 2020
`
`Tenth Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas
`dated November 18, 2020
`
`1055
`
`Eleventh Supplemental Order Regarding Court Operations Under
`the Exigent Circumstances Created by the COVID-19 Pandemic,
`
`
`
`x
`
`
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`Patent No. 8,243,593—Petition for Inter Partes Review
`
`Exhibit
`
`Description
`United States District Court for the Western District of Texas
`dated December 10, 2020
`
`1056
`
`1057
`
`1058
`
`1059
`
`1060
`
`Twelfth Supplemental Order Regarding Court Operations Under
`the Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas
`dated January 7, 2021
`
`Thirteenth Supplemental Order Regarding Court Operations Under
`the Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas
`dated February 2, 2021
`
`Fourteenth Supplemental Order Regarding Court Operations
`Under the Exigent Circumstances Created by the COVID-19
`Pandemic, United States District Court for the Western District of
`Texas dated March 17, 2021
`
`U.S. Patent No. 6,038,216 (“Packer-216”)
`
`Declaration of Daniel C. Callaway in Support of Petition for Inter
`Partes Review
`
`
`
`xi
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`MANDATORY NOTICES UNDER 37 C.F.R. § 42.8
`
`Real Party-in-Interest (37 C.F.R. § 42.8(b)(1))
`
`The real parties-in-interest are petitioners Cloudflare, Inc. and SonicWall
`
`Inc. (collectively, “Petitioners”) and SonicWall US Holdings Inc., which is the
`
`parent corporation of SonicWall Inc. No unnamed entity is funding, controlling, or
`
`directing this petition or has the opportunity to control or direct this petition or
`
`Petitioners’ participation in any resulting inter partes review. Petitioners
`
`understand and believe that the ’593 Patent is owned by Sable Networks, Inc.
`
`(“Patent Owner”).
`
`Related Matters (37 C.F.R. § 42.8(b)(2))
`
`Petitioners are aware of the following pending district court matters
`
`involving the ’593 Patent: Sable Networks, Inc. and Sable IP, LLC v. Splunk, Inc.
`
`and Splunk Services LLC, Case No. 5:21-cv-00040 (E.D. Tex.); Sable Networks,
`
`Inc. and Sable IP, LLC v. Cloudflare, Inc., Case No. 6:21-cv-00261 (W.D. Tex.);
`
`Sable Networks, Inc. and Sable IP, LLC v. Forcepoint LLC, Case No. 6:21-cv-
`
`00241 (W.D. Tex.); Sable Networks, Inc. and Sable IP, LLC v. Check Point
`
`Software Technologies, Ltd. and Check Point Software Technologies, Inc., Case
`
`No. 1:21-cv-00201-LPS (D. Del.); Sable Networks, Inc. and Sable IP, LLC v.
`
`Riverbed Technology, Inc., Case No. 6:21-cv-00175 (W.D. Tex.); and Sable
`
`
`
`xii
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`Networks, Inc. and Sable IP, LLC v. SonicWall, Inc., Case No. 6:21-cv-00190
`
`(W.D. Tex.).
`
`Lead and Back-Up Counsel (37 C.F.R. § 42.8(b)(3))
`
`Petitioners appoint James L. Day (Reg. No. 72,681) of Farella Braun +
`
`Martel LLP as lead counsel and appoint Daniel Callaway (Reg. No. 74,267) and
`
`Winston Liaw (Reg. No. 78,766) of Farella Braun + Martel LLP and David C.
`
`Dotson (Reg. No. 59,472) of Duane Morris LLP as back-up counsel.
`
`Service Information (37 C.F.R. § 42.8(b)(4))
`
`Service of any documents to lead and back-up counsel can be made via
`
`hand-delivery to Farella Braun + Martel LLP, 235 Montgomery Street, 17th Floor,
`
`San Francisco, California, 94104. Petitioners consent to electronic service to the
`
`following email addresses: jday@fbm.com, dcallaway@fbm.com,
`
`wliaw@fbm.com, dcdotson@duanemorris.com, and calendar@fbm.com.
`
`
`
`
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`xiii
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`Patent No. 8,243,593—Petition for Inter Partes Review
`
`I.
`
`INTRODUCTION
`Cloudflare, Inc. and SonicWall Inc. (“Petitioners”) petition for inter partes
`
`review of claims 1-44 (“challenged claims”) of U.S. Patent No. 8,243,593 (the
`
`“ʼ593 Patent”) assigned to Sable Networks, Inc. (“Patent Owner”). The challenged
`
`claims are directed to identifying and controlling network traffic using behavioral
`
`statistics of packets in the flows, which was known in the art as evidenced by this
`
`petition and the supporting declaration of Kevin Jeffay, Ph.D. (EX1003). The
`
`challenged claims are unpatentable as obvious based on the following grounds:
`
`Ground
`
`Claims
`
`Prior Art
`
`1
`
`2
`
`3
`
`4
`
`1, 2, 4-7, 17, 18, 25-27, 37, 38 Yung (EX1005)
`
`9-13, 19-24, 29-33, 39-44
`
`Yung and Copeland (EX1007)
`
`3
`
`Yung and Four-Steps Whitepaper
`(EX1006)
`
`8, 14-16, 28, 34-36
`
`Yung, Copeland, and Ye (EX1008)
`
`II. GROUNDS FOR STANDING
`Petitioners certify that the ’593 Patent is available for inter partes review
`
`and that Petitioners are not barred or estopped from requesting review.
`
`III. TECHNICAL BACKGROUND
`
`By the early 2000s, the ever-increasing popularity of online applications and
`
`services brought significantly increased network traffic on the Internet and other
`
`
`
`1
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`Patent No. 8,243,593—Petition for Inter Partes Review
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`computer networks. The Internet provided an “exploding amount of remote
`
`information” to users worldwide and enabled a variety of new applications (e.g.,
`
`e-mail, e-commerce, file-transfer, remote database access, etc.) that added load to
`
`existing networks already strained by increasing levels of network traffic.
`
`EX1042, ¶¶[0019]-[0020]. The problem of quickly-growing demand for the
`
`limited existing bandwidth was exacerbated by the widespread emergence of peer-
`
`to-peer (P2P) applications (EX1010, 1-2; EX1013, 1-2), growing use of voice-
`
`over-IP (VOIP) systems (EX1011, 1:62-2:21), and increase in denial-of-service
`
`attacks against network infrastructures (EX1012, 1:12-18). See also EX1003,
`
`¶¶32-37.
`
`Because existing networks had finite capacity for ever-increasing network
`
`traffic, it became necessary to monitor network performance and to employ
`
`corrective measures when performance fell. EX1009, ¶[0004]. Various techniques
`
`were developed to identify network traffic and handle it appropriately in an effort
`
`to efficiently allocate existing bandwidth. EX1021, 2:43-3:6; EX1003, ¶¶38-40.
`
`For example, a network administrator might prioritize database transactions over
`
`external web-browsing or ensure low latency for interactive applications and high
`
`throughput for file downloads. EX1021, 1:9-29.
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`One way to understand network traffic was to identify (i.e., classify)
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`network “flows.” The concept of a flow would have been well-known to a person
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`of ordinary skill in the art. EX1003, ¶40. A flow is essentially a sequence of
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`related packets; for example, packets sent from the same application or packets
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`sent on the same network connection. Id.; see also EX1001, 5:15-19 (describing a
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`flow as “a series of packets that are related in some manner” and stating that
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`“packets are grouped into a flow if they share a sufficient amount of header
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`information”). Network elements, such as routers, track network flows using flow
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`tables to record the existence of the flow and to capture information about it.
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`EX1043, ¶¶[0002]-[0006], [0013].
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`By 2004, when the ’593 Patent was filed, various prior art approaches had
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`been developed for classifying flows. Given a flow classification, an administrator
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`could apply rules to take action on the packets of the flow to adhere to desired
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`policies (e.g., priority, security, rate control, etc.). EX1003, ¶45. For example,
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`network congestion and delays could be addressed by “shaping” network traffic,
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`which could include dropping packets or using other quality of service (QoS)
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`measures (e.g., prioritizing certain flows, re-routing flows, etc.). EX1014, 1:6-32;
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`EX1029, 2:21-40.
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`Industry participants offered various products (i.e., network appliances)
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`providing traffic management capabilities. EX1003, ¶¶41-43; EX1016; EX1017.
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`For example, Packeteer, Inc. was an industry leader and offered a network
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`appliance called PacketShaper® that allowed network administrators to “control
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`traffic to ensure that latency-sensitive, customer-critical applications get the
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`bandwidth they need to perform at their peak.” EX1031, 3; see also id., 1
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`(“Seventy-four percent of the world’s largest companies rely on Packeteer®
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`innovation to solve their WAN application performance problems.”); EX1032
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`(“Securing a University’s Bandwidth with PacketShaper”). For reasons of trust
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`and scalability of administration and management, however, traffic management
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`functionality was typically implemented in network routers. EX1021, 3:19-24; see
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`also EX1029, 2:21-40; EX1020, 16:37-40; EX1023, 2:41-54; EX1015, 1:58-2:3;
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`EX1018, Abstract; EX1028, Abstract; EX1030, 20:9-12; EX1036, 21:1-7;
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`EX1037, 5:3-6; EX1003, ¶44.
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`Network practitioners recognized, by the early 2000s, that better
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`classification techniques (i.e., improved mechanisms for identifying the type of
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`traffic represented by particular network flows) would lead to wider adoption of
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`QoS-based traffic shaping. EX1021, 2:31-39. It had become particularly
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`important to accurately identify peer-to-peer traffic because it had come to
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`monopolize a large portion of available network bandwidth. EX1022, 512; see
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`also EX1003, ¶45.
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`Some traffic classification techniques examined packet header information,
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`such as the port number, or scanned packet payloads (i.e., data carried by the
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`packet) in an effort to identify a “signature” for a particular type of network traffic.
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`EX1022, 512; EX1045, 1:31-42; EX1046, 1:42-50; EX1005, 4:51-55; EX1001,
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`1:19-45; EX1003, ¶46. Because some applications, such as peer-to-peer
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`applications, sought to avoid identification through encryption, dynamic port-
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`hopping, and other means, traffic classification techniques were developed that
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`focused on the flow’s behavioral statistics and empirically observable flow data.
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`EX1021, Abstract; EX1045, 2:51-3:30; EX1007, Abstract; EX1047, 121-122;
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`EX1034, 139-140 §4.2; EX1005, Abstract; EX1003, ¶47. For example, some prior
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`art techniques considered packet sizes, number of packets, inter-packet arrival
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`delay, and so forth in classifying network flows. EX1045, 6:29-35 (“Beside flow
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`duration, traffic flows can be characterized based on statistical traffic flow
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`parameters such as: average/median packet size, packet size variance, root-means-
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`square packet size, largest packet sampled so far, shortest packet sampled so far,
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`average/median inter-packet arrival delay, inter-packet arrival delay variance, bytes
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`per flow, packets per flow, etc.”); EX1021, 6:28-32, 7:18-20 (“A simple example
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`is the statistics of the inter-arrival times between packets in flows.”); EX1047, 134
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`(“We also want to consider additional heuristics that use knowledge of specific
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`packet sizes that may reflect control traffic of P2P protocols.”). These approaches
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`did not rely on packet headers or payload contents. EX1047, 121-122 (“We
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`develop a systematic methodology for P2P traffic profiling by identifying flow
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`patterns and characteristics of P2P behavior, without examination of user
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`payload.”). Instead, they applied heuristics to map measured statistics onto
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`established classes (e.g., P2P). Id., 125 (“These two simple heuristics efficiently
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`classify most pairs as P2P or nonP2P.”).
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`After classifying the flow as a particular type of traffic, network traffic
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`management devices could enforce policies on packets in the flow as appropriate.
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`EX1025, ¶¶[0008]-[0009], [0059]; EX1005, 24:27-25:8. For instance, packets
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`could be prioritized, delayed, or dropped depending on the type of traffic and the
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`particular rules adopted by network administrators. Flow identification and
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`management of this type could be implemented in various network devices
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`including IP routers, as noted above. EX1003, ¶48.
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`IV. THE CHALLENGED PATENT
`A. Overview of the ’593 Patent
`The ’593 Patent is entitled “Mechanism for Identifying and Penalizing
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`Misbehaving Flows in a Network.” EX1001. It describes identifying network data
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`flows based on behavioral statistics and penalizing “misbehaving” flows such as
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`peer-to-peer traffic. Id., Abstract, 1:53-2:51. As others in the industry had already
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`recognized (e.g., EX1021, 2:31-39; EX1045, 1-31:42), then-existing systems were
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`inadequate for classifying traffic as applications became more sophisticated and
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`elusive. EX1001, 1:7-49. The named-inventor addressed the problem—again as
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`others in the industry already had (e.g., EX1021, 6:23-7:40; EX1045, 6:18-35)—by
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`identifying flows based on their observed, empirical behavior. EX1001, 1:58-59,
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`2:4-5. The specification explains that “because their behavior cannot be hidden,
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`misbehaving flows cannot avoid detection…regardless of which protocols they
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`use, or how those protocols try to hide/obfuscate their nature….” Id., 1:61-66.
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`“Once identified/detected, they can be controlled and/or penalized.” Id., 1:66-67.
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`The ’593 Patent describes a “misbehaving flow manager (MFM) 210 for
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`keeping track of flows, determining whether the flows are exhibiting undesirable
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`behavior, and enforcing a penalty on the flows if they are exhibiting undesirable
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`behavior.” EX1001, 5:44-48. The misbehaving flow manager empirically tracks
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`behavioral statistics such as byte count, life duration, flow rate, average packet
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`size, etc. and stores these statistics in a “flow block.” Id., 2:4-5, 2:63-64, 6:5-20,
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`Fig. 4.
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`’593 Patent, Fig. 4
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`As each packet in