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SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

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Page 1: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

SRG

PeerReview: Practical Accountability for Distributed Systems

Andreas Heaberlen, Petr Kouznetsov, and Peter DruschelSOSP’07

Page 2: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Problems

How to:Detect Byzantine faults whose effects are

observed by a correct node.Link faults to faulty nodes.Defend correct nodes against false

accusations.

Page 3: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Accountability

Use accountability to detect and expose node faults.Maintain a tamper-evident record that

captures all actions of each node.Detect a faulty node when it’s behavior

deviates from that of a correct node.

Page 4: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Limitations of current systems

Designed for a specific type of faults or for a specific application.

Based on many strong assumptions.Not provide verifiable evidence of

misbehavior.Use formal specification of a system to

check for misbehavior.Can only detect faulty nodes that

misbehave repeatedly.

Page 5: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Overview

Model a node as a deterministic state machine.

Each node keeps a secure log that records all sent and received messages, all inputs and outputs.

To check a node j, node i will:Get j’s log.Replay j’s log using a reference

implementation.Compare the results.

Page 6: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

The problem of detection

Ideal completeness: a faulty node should be exposed by all correct nodes.

Ideal accuracy: no correct node is ever exposed by a correct node (no false positives).

Page 7: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Types of faults can be detected

Available data: messages sent and received among nodes.

Can only detect faults that manifest themselves through messages.

Can only detect faults that are observed by a correct nodes.

Need to consider:Verifiability of outputs.Missing and long delayed messages.

Page 8: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Problem statementTerms:

Detectably fault, detectably ignorant.Accomplices (of i): nodes that send

messages caused by an incorrect message sent by i

Completeness: Eventually, every detectably ignorant node

is suspected forever by every correct node. If node i is detectably faulty, then eventually,

some faulty accomplice is exposed or suspected forever by every correct node.

Page 9: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Problem statement (cont)

Accuracy:No correct node is forever suspected by a

correct node.No correct node is ever exposed by a

correct node.

Page 10: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

System model

Failure indications:exposed(j)suspected(j) trusted(j)

Page 11: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Assumptions

The state machines Si are deterministic.

A message sent from a correct node to another is eventually received.

Use a hash function H() that is: pre-image resistant, second pre-image resistant, and collision resistant.

Each node has a unique identifier. Nodes can sign messages, and faulty nodes can node forge the signature.

Page 12: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Assumptions (cont)

Each node has access to a reference implementation of all Si. The implementation can take a snapshot and can be initialized from a snapshot.

Function ω that maps each node to a set of witnesses. The set {i} U ω(i) contains at least one correct node.

Page 13: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Tamper-evident logs Log entry Hash value

Authenticator

If a prefix of a node’s log does not match the hash value then that node is faulty

),,( kkkk ctse

))(||||||( 1 kkkkk cHtshHh

),( kkjjk hs

Page 14: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Tamper-evident logs

αkj can be used to check if j’s log

contains ek

To inspect x entries of j: i challenge j to return ek-(x-1),… ek and hk-x.

i calculate hk and compare with the value in the authenicator.

Page 15: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Commitment protocol To ensure that a node can not add an entry for

a message it has never received and that a node’s log is complete.

When i send a message to j: i creates (sk,SEND,{j,m}), attach hk-1, sk and σi(sk||hk)

to m and send m. j calculate the signature, if valid then j creates

(sl, RECV,{i,m}) and retusn ACK to i with hl-1, sl and σj(sl||hl).

i verify the signature and send a challenge to j’s witnesses if the signature is not valid.

Page 16: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Consistency protocolA faulty node can hide itself by keeping

more than one log or a log with multiple branches

Page 17: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Consistency protocol

If i receives authenticators from j, it must eventually forward those authenticators to j’s witnesses.

Periodically, each ω of j’s witnesses will challenge j to return a list of entries (from k to l) then ω check for consistency.

Finally, ω extracts all authenticators j receives from other nodes and send them to corresponding witness sets.

Page 18: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Audit protocol To check if the node’s behavior consistent with

it’s reference implementation. Each witness of i will:

Look up the most recent authenticator of i. Challenge to get all log entries since the last audit

and add them to λωi. Create an instance of i’s reference implementation,

initialize the most recent snapshot. Replay all the inputs and compare the outputs. Expose i if the outputs are not equal.

Page 19: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Challenge/response protocol

Audit challenge:Consists two authenticators αk

i and αli (k < l)

i’s log must contains ek – el, otherwise faulty If i is correct, returns the corresponding log

segment.

Page 20: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Challenge/response protocol

Send challenge:Consists the message m with all needed

information attached. i must acknowledge m, otherwise faulty. If i has not yet received m, accepts m and

returns an ACK. If i has already received m, just resends the

ACK.

Page 21: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Evidence transfer protocol To ensure that all correct nodes eventually

collect the same evidence against faulty nodes.

Every node i periodically fetches challenges collected by witnesses of every other node j.

If a correct node i obtains a challenge for j, i indicates suspected(j). When I receives a message from j, i challenges j.

If i receives valid answers to all pending challenges of j, i indicates trusted(j).

If i obtains a misbehavior from j, i indicates exposed(j).

Page 22: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Overhead

Signing messages.Extra messages to implement the

protocols.Taking snapshots of nodes.Replay nodes’ execution

Page 23: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Extension

Pf : probability that an all-faulty witness set exists.

Pm: probability that a given instance of misbehavior remains undetected.

The message complexity grows with O(logN).

Page 24: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Applications

Overlay multicast.NFSP2P email (ePOST)

Page 25: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Evaluation

Strategy of the freeloader in Overlay Multicast.

Page 26: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Evaluation (cont)

Message latency in NFS

Page 27: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Evaluation (cont)

Throughput of NFS

Page 28: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Evaluation (cont)

Average traffic in ePOST

Page 29: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Evaluation (cont)

Scalability

Page 30: SRG PeerReview: Practical Accountability for Distributed Systems Andreas Heaberlen, Petr Kouznetsov, and Peter Druschel SOSP’07

Evaluation (cont)

Scalability