Data Provenance at Internet Scale: Architecture, Experiences, and - - PowerPoint PPT Presentation

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Data Provenance at Internet Scale: Architecture, Experiences, and - - PowerPoint PPT Presentation

Data Provenance at Internet Scale: Architecture, Experiences, and the Road Ahead Ang Chen, Yang Wu, Andreas Haeberlen, Boon Thau Loo, Wenchao Zhou Motivation D E A foo.com Alice C B An example scenario: network routing System


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SLIDE 1

Ang Chen, Yang Wu, Andreas Haeberlen, Boon Thau Loo, Wenchao Zhou

Data Provenance at Internet Scale: Architecture, Experiences, and the Road Ahead

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SLIDE 2

Motivation

  • An example scenario: network routing

– System administrator observes strange behavior – Example: the route to foo.com has suddenly changed – Anomalies in distributed systems

  • Need a way to explain system behavior.

2

Alice foo.com A D E B C

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SLIDE 3

Motivation

  • An example scenario: network routing

– System administrator observes strange behavior – Example: the route to foo.com has suddenly changed – Anomalies in distributed systems

  • Need a way to explain system behavior.

2

Alice foo.com Route r1 A D E B C

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SLIDE 4

Motivation

  • An example scenario: network routing

– System administrator observes strange behavior – Example: the route to foo.com has suddenly changed – Anomalies in distributed systems

  • Need a way to explain system behavior.

2

Alice foo.com Route r2 A D E B C

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SLIDE 5

Motivation

  • An example scenario: network routing

– System administrator observes strange behavior – Example: the route to foo.com has suddenly changed – Anomalies in distributed systems

  • Need a way to explain system behavior.

2

Why did my route to foo.com change?!

Alice foo.com Route r2 A D E B C

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SLIDE 6

Motivation

  • An example scenario: network routing

– System administrator observes strange behavior – Example: the route to foo.com has suddenly changed – Anomalies in distributed systems

  • Need a way to explain system behavior.

2

Why did my route to foo.com change?!

Alice foo.com Route r2

Innocent Reason?

A D E B C

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SLIDE 7

Motivation

  • An example scenario: network routing

– System administrator observes strange behavior – Example: the route to foo.com has suddenly changed – Anomalies in distributed systems

  • Need a way to explain system behavior.

2

Why did my route to foo.com change?!

Alice foo.com Route r2

Innocent Reason?

A D E B C

Software Bugs?

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SLIDE 8

Motivation

  • An example scenario: network routing

– System administrator observes strange behavior – Example: the route to foo.com has suddenly changed – Anomalies in distributed systems

  • Need a way to explain system behavior.

2

Why did my route to foo.com change?!

Alice foo.com Route r2

Innocent Reason? Malicious Attack?

A D E B C

Software Bugs?

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SLIDE 9

Data-centric Perspective on Network Debugging

  • We assume a general distributed system

– Network consists of nodes (routers, middleboxes, ...) – The state of a node is a set of tuples (routes, config, ...)

3

Alice foo.com A B C D E

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SLIDE 10

Data-centric Perspective on Network Debugging

  • We assume a general distributed system

– Network consists of nodes (routers, middleboxes, ...) – The state of a node is a set of tuples (routes, config, ...)

3

Alice foo.com

route(A, B)

A B C D E

…… route(A, foo.com) route(A, D)

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SLIDE 11

Data-centric Perspective on Network Debugging

  • We assume a general distributed system

– Network consists of nodes (routers, middleboxes, ...) – The state of a node is a set of tuples (routes, config, ...)

3

Alice foo.com

route(A, B)

A B C D E

…… route(A, foo.com) route(A, D) link(A, B) link(A, D)

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SLIDE 12

Data-centric Perspective on Network Debugging

  • We assume a general distributed system

– Network consists of nodes (routers, middleboxes, ...) – The state of a node is a set of tuples (routes, config, ...) – Idea: Explanation as reasoning about distributed state dependencies

3

Alice foo.com A B C D E

route(A, foo.com)

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SLIDE 13

Data-centric Perspective on Network Debugging

  • We assume a general distributed system

– Network consists of nodes (routers, middleboxes, ...) – The state of a node is a set of tuples (routes, config, ...) – Idea: Explanation as reasoning about distributed state dependencies

3

Alice foo.com A B C D E

route(B, foo.com) route(A, foo.com) link(A, B)

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SLIDE 14

Data-centric Perspective on Network Debugging

  • We assume a general distributed system

– Network consists of nodes (routers, middleboxes, ...) – The state of a node is a set of tuples (routes, config, ...) – Idea: Explanation as reasoning about distributed state dependencies

3

Alice foo.com

route(C, foo.com) link(C, foo.com)

A B C D E

route(B, foo.com) link(B, C) route(A, foo.com) link(A, B)

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SLIDE 15

Network Provenance

4

Alice foo.com

route(C, foo.com) link(C, foo.com)

A B C D E

route(B, foo.com) link(B, C) route(A, foo.com) link(A, B) route(D, foo.com) link(D, E) route(E, foo.com) link(E, B)

[SIGMOD 2010]

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Network Provenance

  • Provenance for encoding distributed state dependencies

– Explains the derivation of tuples – Captures the dependencies between tuples as a graph

4

route(C, foo.com) link(C, foo.com) route(B, foo.com) link(B, C) route(A, foo.com) link(A, B) route(D, foo.com) link(D, E) route(E, foo.com) link(E, B)

[SIGMOD 2010]

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SLIDE 17

Network Provenance

  • Provenance for encoding distributed state dependencies

– Explains the derivation of tuples – Captures the dependencies between tuples as a graph – Explanation of a tuple is an acyclic graph rooted at the tuple

4

route(C, foo.com) link(C, foo.com) route(B, foo.com) link(B, C) route(A, foo.com) link(A, B)

[SIGMOD 2010]

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NetTrails: First Generation Network Provenance Tool

  • http://netdb.cis.upenn.edu/nettrails/ [SIGMOD 2011 demo]

5

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  • Network provenance [SIGMOD’10]
  • Secure network provenance [SOSP’11]
  • Provenance in dynamic environments [VLDB’13]
  • Negative provenance [SIGCOMM’14]
  • Distributed provenance compression [SIGMOD’17]
  • Differential provenance [SIGCOMM’16]
  • Meta-provenance [NSDI’17]

Ph.D. dissertation work of Ang Chen (2017), Chen Chen (2017), Yang Wu (2017), and Wenchao Zhou (2012).

Network Provenance Research (2010 – 2017)

Deeper diagnostics and repair Explanations

6

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Assumption #1: All nodes in the network can be trusted

Alice foo.com Route r2 A D E B C

Why did my route to foo.com change?!

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Assumption #1: All nodes in the network can be trusted

The Network Alice foo.com Route r2 A D E B C

Q: Explain why the route to foo.com changed to r2.

7

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Assumption #1: All nodes in the network can be trusted

The Network

A: Because someone accessed Router D and changed the configuration from X to Y.

Alice foo.com Route r2 A D E B C

Q: Explain why the route to foo.com changed to r2.

7

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Assumption #1: All nodes in the network can be trusted

The Network

A: Because someone accessed Router D and changed the configuration from X to Y.

Alice foo.com Route r2 A D E B C

Not realistic: adversary can tell lies

Q: Explain why the route to foo.com changed to r2.

7

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SLIDE 24

Challenge: Adversaries Can Lie

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The Network

Q: Explain why the route to foo.com changed to r2.

Alice foo.com Route r2 A D E B C

 Problem: adversary can …

 ... fabricate plausible (yet incorrect) response  … point accusation towards innocent nodes

I should cover up the intrusion.

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SLIDE 25

Challenge: Adversaries Can Lie

8

The Network

Q: Explain why the route to foo.com changed to r2.

Alice foo.com Route r2 A D E B C

 Problem: adversary can …

 ... fabricate plausible (yet incorrect) response  … point accusation towards innocent nodes

Everything is fine. Router E advertised a new route.

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Secure Network Provenance (SNP)

  • Step 1: Each node keeps vertices about local actions

– Split cross-node communications

9

route(C, foo.com) link(C, foo.com) route(B, foo.com) link(B, C) route(A, foo.com) link(A, B) route(D, foo.com) link(D, E) route(E, foo.com) link(E, B)

SOSP 2011

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Secure Network Provenance (SNP)

  • Step 1: Each node keeps vertices about local actions

– Split cross-node communications

9

SOSP 2011

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Secure Network Provenance (SNP)

  • Step 1: Each node keeps vertices about local actions

– Split cross-node communications

9

SOSP 2011

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Secure Network Provenance (SNP)

  • Step 1: Each node keeps vertices about local actions

– Split cross-node communications

9

SOSP 2011

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Secure Network Provenance (SNP)

  • Step 1: Each node keeps vertices about local actions

– Split cross-node communications

9

RECV SEND

SOSP 2011

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Secure Network Provenance (SNP)

  • Step 1: Each node keeps vertices about local actions

– Split cross-node communications

  • Step 2: Make the graph tamper-evident

9

RECV SEND

SOSP 2011

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SNP Guarantees

  • No faults: Explanation is complete and accurate
  • Byzantine fault: Explanation identifies at least one faulty node

10

The Network

Q: Why did my route to foo.com change to r2? A: Because someone accessed Router D and changed its router configuration from X to Y.

Alice foo.com Route r2 A D E B C

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SNP Guarantees

  • No faults: Explanation is complete and accurate
  • Byzantine fault: Explanation identifies at least one faulty node

10

The Network

Q: Why did my route to foo.com change to r2? A: Because someone accessed Router D and changed its router configuration from X to Y.

Alice foo.com Route r2 A D E B C

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SNP Guarantees

  • No faults: Explanation is complete and accurate
  • Byzantine fault: Explanation identifies at least one faulty node

10

The Network

Q: Why did my route to foo.com change to r2? A: Because someone accessed Router D and changed its router configuration from X to Y.

Alice foo.com Route r2 A D E B C

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SNP Guarantees

  • No faults: Explanation is complete and accurate
  • Byzantine fault: Explanation identifies at least one faulty node

10

The Network

Q: Why did my route to foo.com change to r2? A: Because someone accessed Router D and changed its router configuration from X to Y.

Alice foo.com Route r2 A D E B C

Aha, at least I know which node is compromised.

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Assumption #2: Operators react only to presence of anomaly events

11

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Assumption #2: Operators react only to presence of anomaly events

  • What if something expected is

not happening?

  • Missing events cannot be

handled by existing tools

11

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Assumption #2: Operators react only to presence of anomaly events

Internet HTTP Server Data Center Network Controller

  • What if something expected is

not happening?

  • Missing events cannot be

handled by existing tools

11

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Assumption #2: Operators react only to presence of anomaly events

Internet HTTP Server Data Center Network Controller

???

Why is the HTTP server

NOT getting requests?

  • What if something expected is

not happening?

  • Missing events cannot be

handled by existing tools

11

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17% 83%

Outages

48% 52%

NANOG-user

26% 74%

floodlight-dev

  • Missing events are consistently in the majority
  • Lengthier email threads for missing events

Missing events Positive events NANOG-user Floodlight-dev Outages

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How common are missing events?

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Negative Provenance

[SIGCOMM 2014]

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Negative Provenance

Internet HTTP Server Data Center Network Controller

[SIGCOMM 2014]

13

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Negative Provenance

Internet HTTP Server Data Center Network Controller

No HTTP Packet arrived at HTTP Server

???

Why is the HTTP server

NOT getting requests?

[SIGCOMM 2014]

13

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Negative Provenance

Internet HTTP Server Data Center Network Controller

No HTTP Packet arrived at HTTP Server No Forwarding-FlowEntry installed at Switch

???

???

Why is the HTTP server

NOT getting requests?

[SIGCOMM 2014]

13

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Negative Provenance

Internet HTTP Server Data Center Network Controller

No HTTP Packet arrived at HTTP Server No Forwarding-FlowEntry installed at Switch HTTP Packet received at Switch

???

??? HTTP Packet

Why is the HTTP server

NOT getting requests?

[SIGCOMM 2014]

13

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Negative Provenance

Internet HTTP Server Data Center Network Controller

No HTTP Packet arrived at HTTP Server No Forwarding-FlowEntry installed at Switch HTTP Packet received at Switch Dropping-FlowEntry existed at Switch

???

??? HTTP Packet Dropping- FlowEntry

Why is the HTTP server

NOT getting requests?

[SIGCOMM 2014]

13

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Negative Provenance

Internet HTTP Server Data Center Network Controller

No HTTP Packet arrived at HTTP Server No Forwarding-FlowEntry installed at Switch HTTP Packet received at Switch Dropping-FlowEntry existed at Switch … Program

???

??? HTTP Packet Dropping- FlowEntry

Why is the HTTP server

NOT getting requests?

[SIGCOMM 2014]

13

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Negative Provenance

Internet HTTP Server Data Center Network Controller

No HTTP Packet arrived at HTTP Server No Forwarding-FlowEntry installed at Switch HTTP Packet received at Switch Dropping-FlowEntry existed at Switch … … Program

???

??? HTTP Packet Dropping- FlowEntry

Why is the HTTP server

NOT getting requests?

[SIGCOMM 2014]

13

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Approach: Counter-factual reasoning

Find all the ways a missing event could have occurred, and show why each of them did not happen.

14

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Approach: Counter-factual reasoning

Find all the ways a missing event could have occurred, Philly and show why each of them did not happen.

14

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Approach: Counter-factual reasoning

Find all the ways a missing event could have occurred, Philly Santa Cruz and show why each of them did not happen.

14

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SLIDE 52

Approach: Counter-factual reasoning

Find all the ways a missing event could have occurred,

Why did Bob NOT arrive at CIDR?

Philly Santa Cruz and show why each of them did not happen.

14

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SLIDE 53

Approach: Counter-factual reasoning

Find all the ways a missing event could have occurred,

Why did Bob NOT arrive at CIDR?

Philly Santa Cruz and show why each of them did not happen.

14

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SLIDE 54

Approach: Counter-factual reasoning

Find all the ways a missing event could have occurred,

Why did Bob NOT arrive at CIDR?

Philly Santa Cruz and show why each of them did not happen.

14

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SLIDE 55

Approach: Counter-factual reasoning

Find all the ways a missing event could have occurred,

Why did Bob NOT arrive at CIDR?

Philly Santa Cruz and show why each of them did not happen.

14

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SLIDE 56

Approach: Counter-factual reasoning

Find all the ways a missing event could have occurred,

Why did Bob NOT arrive at CIDR?

Philly Santa Cruz and show why each of them did not happen.

14

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Assumption #3: Provenance trees alone are sufficient for diagnostics

15

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r

  • t

Assumption #3: Provenance trees alone are sufficient for diagnostics

Root cause Symptom

15

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r

  • t

Assumption #3: Provenance trees alone are sufficient for diagnostics

Root cause Symptom

C received packet B sent packet Rule match on B

… …

15

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r

  • t

Assumption #3: Provenance trees alone are sufficient for diagnostics

Root cause Symptom

15

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r

  • t

Assumption #3: Provenance trees alone are sufficient for diagnostics

Root cause Symptom Packet arrives at the wrong server

15

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r

  • t

Assumption #3: Provenance trees alone are sufficient for diagnostics

Root cause Symptom Packet arrives at the wrong server Rule 7: Next-hop=port2

15

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What can we do?

16

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What can we do?

From: alice@xyz.com To: Admin (bob@xyz.com) Title: Help! My server is receiving suspicious traffic from 4.3.2.0/24--it should have been sent to the low-security server. Packets from 4.3.3.0/24 are still being routed correctly. Can you help?

16

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What can we do?

From: alice@xyz.com To: Admin (bob@xyz.com) Title: Help! My server is receiving suspicious traffic from 4.3.2.0/24--it should have been sent to the low-security server. Packets from 4.3.3.0/24 are still being routed correctly. Can you help?

Working reference!

16

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What can we do?

From: alice@xyz.com To: Admin (bob@xyz.com) Title: Help! My server is receiving suspicious traffic from 4.3.2.0/24--it should have been sent to the low-security server. Packets from 4.3.3.0/24 are still being routed correctly. Can you help?

Outages mailing list Sept.—Dec. 2014: 66% have references! Working reference!

16

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What can we do?

Web server 1 DPI Web server 2

S1 S2 S3 S4 S5 S6

Bob

16

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What can we do?

  • Idea: Reason about the differences between the symptom

and the reference

Web server 1 DPI Web server 2

S1 S2 S3 S4 S5 S6

Bob

16

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4.3.3.1 fails 4.3.2.1 works

Differential provenance

  • Input: a bad symptom and a good reference

[SIGCOMM 2016]

17

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4.3.3.1 fails 4.3.2.1 works

Differential provenance

  • Input: a bad symptom and a good reference

Differential Provenance

[SIGCOMM 2016]

17

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4.3.3.1 fails 4.3.2.1 works

Differential provenance

  • Input: a bad symptom and a good reference
  • Debugger reasons about the differences

Differential Provenance

[SIGCOMM 2016]

17

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4.3.3.1 fails 4.3.2.1 works

Differential provenance

  • Input: a bad symptom and a good reference
  • Debugger reasons about the differences
  • Output: root cause

Differential Provenance Rule 7’s next hop is wrong!

[SIGCOMM 2016]

17

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Strawman solution

  • Strawman solution: Find vertexes that are different in the

two trees

faulty rule root root
  • =

Provenance (Symptom) Provenance (Reference)

?

18

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Strawman solution

  • Strawman solution: Find vertexes that are different in the

two trees

  • Problem: The diff can be larger than the individual trees!
faulty rule root root
  • =

Provenance (Symptom) Provenance (Reference)

18

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Overly Simplified Approach in a nutshell

Roll back the execution to a divergence point Change the faulty node to be like the correct node Roll forward the execution to align the trees

19

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  • Networks are software and can have bugs

Assumption #4: Software is correct and static

20

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  • Networks are software and can have bugs

Assumption #4: Software is correct and static

S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server

20

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  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server

20

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SLIDE 79
  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server HTTP traffic

20

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SLIDE 80
  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server Off-loading HTTP HTTP traffic

20

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else if (switch == S1 && protocol == HTTP) then action = output:3.

  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server Off-loading HTTP HTTP traffic

20

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else if (switch == S1 && protocol == HTTP) then action = output:3.

  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server Off-loading HTTP HTTP traffic

20

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else if (switch == S1 && protocol == HTTP) then action = output:3. else if (switch == S1 && protocol == HTTP) then action = output:5.

  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server Off-loading HTTP HTTP traffic

20

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else if (switch == S1 && protocol == HTTP) then action = output:3. else if (switch == S1 && protocol == HTTP) then action = output:5.

  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server Off-loading HTTP HTTP traffic

20

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else if (switch == S1 && protocol == HTTP) then action = output:3. else if (switch == S1 && protocol == HTTP) then action = output:5.

  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server

Copy-and-paste bug!!!

Off-loading HTTP HTTP traffic

20

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SLIDE 86

else if (switch == S1 && protocol == HTTP) then action = output:3. else if (switch == S1 && protocol == HTTP) then action = output:5.

  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server

Copy-and-paste bug!!!

Off-loading HTTP HTTP traffic

20

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SLIDE 87

else if (switch == S1 && protocol == HTTP) then action = output:3. else if (switch == S1 && protocol == HTTP) then action = output:5.

  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server Why is the backup web server not getting requests?

Copy-and-paste bug!!!

Off-loading HTTP HTTP traffic

20

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else if (switch == S1 && protocol == HTTP) then action = output:3. else if (switch == S1 && protocol == HTTP) then action = output:5.

  • Networks are software and can have bugs

Assumption #4: Software is correct and static

SDN Controller S0

5

S2

3 4

S1 Backup Web Server Main Web Server DNS Server

  • How can we find and fix bugs quickly?

Why is the backup web server not getting requests?

Copy-and-paste bug!!!

Off-loading HTTP HTTP traffic

20

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Approach: Meta provenance

  • Key idea: Treating program as data

HTTP Packet received at Main Web Server Matching Flow Entry installed at S1

  • Idea: Provenance can pinpoint the root cause

Executed If Clause in Controller Program

  • But previous provenance focus exclusively on data
  • Problem: Finding fixes is hard

PacketIn received at Controller

meta provenance

[NSDI 2017]

21

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Repairing Software-defined Networking Programs

Full support of Network Datalog (declarative) Uses Z3 SMT solver to enumerate repairs More details are in [HotNets’15, NSDI’17] Support a subset of Pyretic (Python + DSL) Support a subset of Trema (imperative Ruby)

22

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SLIDE 91
  • Network provenance model [SIGMOD’10]
  • Secure network provenance [SOSP’11]
  • Provenance in dynamic environments [VLDB’13]
  • Negative provenance [SIGCOMM’14]
  • Distributed provenance compression [SIGMOD’17]
  • Differential provenance [SIGCOMM’16]
  • Meta-provenance [NSDI’17]

Ph.D. dissertation work of Ang Chen (2017), Chen Chen (2017), Yang Wu (2017), and Wenchao Zhou (2012).

Network Provenance Research (2010 – 2017)

Deeper diagnostics and repair Explanations

23

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The Road Ahead

  • Network forensics meets data provenance is a

rich area of exploration!

  • Sampling of the problems we are working on:

– Network forensics on the data plane – Privacy-preserving provenance on sensitive networks – Probabilistic provenance – Automated repairs of complex events – Timing-based provenance – and more….

24

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Thank You!

  • Network provenance team at Penn/Georgetown:

– Ang Chen, Chen Chen, Ling Ding, Qiong Fei, Andreas Haeberlen, Zachary Ives, Yang Li, Boon Thau Loo, Suyog Mapara, Arjun Narayan, Yiqing Ren, Micah Sherr, Shengzhi Sun, Tao Tao, Yang Wu, Mingchen Zhao, Wenchao Zhou

25