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Security and Trust in P2P systems

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Trust and Security

Peer-to-Peer systems require different entities to decide how to interact or whether to interact with others Security decisions

I need to know whether I can “trust” another entity within this system

Should I trust “Alice” because my friend, Bob, trusts her?

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Trust and Security

The “perfect” P2P system A system with perfectly flat hierarchy, and with

each entity allowing other entities to use local resources

How can we provide security without a centralized entity? Infrastructure The model of interaction between entities!

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What is trust

When thinking about security in a system, various entities need to “trust” others to varying degrees We say “trusted hardware”, or “trust

administrators

So… what is trust Trust is a bet about the future contingent

actions of others

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Malicious node

A malicious node might give erroneous responses to a request Application level

Returning false data Network level

Returning false routes

May work together, acting in concert, to attack the remainder of the nodes

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Outline

IdentificationRouting table risk

Victim Data Victim Peer

Content verificationPunishment

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Identification

Identity Undesirable to know the identity of other

entities Privacy Anonymity

However, If you wish to trust entity A, you need to be able

to identify it

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Identification

Public key infrastructures (PKI) Should be run with somebody! For a PKI to work in this sort of situation, you

need to have a trusted third party

Recommendation systems Chains of trust

Transitive trust Trust should be granted directly.

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Identification

When trust must be transitive, it creates brittleness

In most P2P system, transitive trust is a key component

How to measure “reputation” Roles Time related

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Secure Routing in p2p systems

Security routing primitive ensures that when a non-faulty nodes sends a message to a key k, the message reaches all non-faulty members in the set of replica roots Rk with very high probability

Security routing guarantees that a replicas are initially placed on legitimate replica roots, and that a lookup message reaches a replica if one exists

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Three problems

Securely assigning nodeIds to nodes Ensure attackers cannot choose the value of nodeIDs

Securely maintaining the routing tables Ensure that the fraction of faulty nodes that appear in th

e routing tables of correct nodes does not exceed the fraction of faulty nodes in the entire overlay

Securely forwarding messages Ensure that at least one copy of a message sent to a ke

y reaches each correct replica root for the key with high probability

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System model

N nodes f (0<f<1) : fraction of faulty nodes

Faulty nodes can behave arbitrarily and they may not all necessarily be operating as a single conspiracy

The set of faulty nodes is partitioned into independent coalitions, which are disjoint sets with size bounded by cN (1/N<= c <= f) Consider the case: c < f

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Secure nodeId assignment

A node might choose its identifier maliciously Allocate itself a collection of nodeIds closer to t

hat document’s key than any existing nodes in the system

Censor a specific document Choose nodeIds to maximize its chances of app

earing in a victim node’s routing tables

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Secure nodeId assignment

Centralized authority The server is only consulted when new nodes join and i

s otherwise uninvolved in the actions of the p2p system Sybil attacks

Coalition nodes might try to get a large number of nodeIds

Even if those nodeIds are random, a large enough collection of them would still give the attackers disproportionate control over the network

Moderate the rate at which nodeIds are given out Charging money? By solving little problem?

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Admission control system (ACS) Property

Security Provide resiliency against attacks that work by creating shadow

nodes Efficiency

Should be simple and does not require a lot of overhead on participating nodes

Fairness Nodes should do an equal amount of work to join the network

Response to attack Make the attack more difficult while not affecting other legitimate

nodes Scalability Verifiability

Allow any node in the system to verify that it is communicating with a node that was legitimately admitted to the network

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It is important that the upper layer nodes are both static and trustworthy

A must gain admission from a sequence of nodes, starting with leaf node B and ending with root X

At each stage, A is required to solve a puzzle presented by B

Decentralized, multi-puzzle scheme

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Join protocol Get token

A wishes to join the network, it must first discover a leaf node B

To gain admission from B by solving B’s puzzle After solving the puzzle, it is given a token and is used to

prove to B’s parent admission by B At each stage, A is given a token to be used as proof of

previous puzzle solution. When reach the root, a final token format is issued by X

• A’s signature

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Connect to the network A must prove to its prospective neighbors that it has

been admitted by the root node X Signature verification is cost The neighboring nodes each require A to solve one

more puzzle challenges protect neighbors from a DoS attack

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Node Upgrade A must prove its stability before inclusion in the

ACS Initially, A joins the ACS as a leaf node, and

evaluated by its parent node To maintain a balanced tree

A node only upgrades nodes when its number of children has reached the degree of the tree

When it is sufficiently deep to support the join load and achieve the proper security guarantees, no node will be added in the ACS

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Node departure Not a member of ACS A member of ACS

Leave gracefully• The oldest child is chosen to replace the departing node

Due to a failure• Children must rejoin the network by

Contact its grandparent Or, find another node in the ACS

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Security The ACS is designed to limit Sybil attacks, not

to prevent them! Attacker is a member of ACS

Easily detected by the parent of the attacker by observing the rate of the token requests

Attacker is not a member of ACS Control a significant fraction of nodes Attack is limited by ensuring only a small number of

tokens are released during a period of time

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How about patient attackers?

If an attacker is patient enough, it can achieve the required number of IDs to launch a massive attack

Cut-off window Define a token expiration time, W How to determine the value of W

Limit the number of good users that must execute the rejoin process to a small percentage

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Analysis

Models Legitimate nodes arrive according to a Poisson

distribution with an arrival rate of g

Life time is exponentially distributed with mean of g

Assume an attacker is equal in computational power to the average user

l: Joining difficulty (measured in maximum time)

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Analysis

Puzzles and fairness The distribution of the time to solve the puzzle is uniform Single puzzle of average time l / 2

n puzzles of difficulty l/2n

Example 5 mins to solve with a maximum standard deviation of 30

seconds• 9 puzzles and each takes max 33.3 seconds.

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Analysis

Steady state The number of nodes in the network, N

N= g * g

To control fraction f of nodes, an attacker will be required to obtain (f*N)/(1-f) IDs

Assume there are n attackers Arrival rate of attacker nodes will be a = 2*n / l The time to launch a successful attack

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Analysis

Example If λg = 1 node/sec, and µg = 2.3 hours, the stead

y state number of nodes is 8280 For the attacker to control 10% of the total node

s in the network it is required to obtain 920 IDs If the joining process takes on average 5 minute

s, a successful attack would take 76 hours which is more than 3 days.

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Analysis

Cut-off windows (legitimate nodes) P : the percentage of legitimate nodes that will

be required to reacquire fresh tokens

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Analysis

Example If µg = 2.3 hours and W = 4 hours, The percentage of Legitimate nodes that will be

cut off the network and asked to rejoin is 17.5%.

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Analysis

Cut-off window (attackers) The combined number of nodes of n attackers

can accumulate is 2*n*W / l Example

If the maximum join time is 10 minutes and W = 4 hours

The maximum number of nodes an attacker can accumulate is 48 nodes

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Robust routing primitives

If an attacker controls a fraction f of the nodes in the p2p network, we would expect that each entry in every routing table would have a probability of f of pointing to a malicious node.

If a desired route consumes h hops The probability being free of malicious nodes is

(1-f)h

How about Chord with 2m nodes?`

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Robust routing primitives

Locality-based attacks The adversary could take advantage of its locality to

a given victim node to get more entries in that node’s routing table

Increase its odds of controlling any given route that uses the victim node

Attempt multiple, redundant routes from the source to the destination Costly How to determine “Not found”

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Content verification

Adversary may spoof the resultsVerification can be done if we have verifica

tion codesSolve by Google’s PageRank technology

Pages that are linked from “popular” pages are themselves more popular

How to add such a notion of popularity into a p2p system

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Punishment

Remove malicious nodes when they are detected

Can we have a global view, who can punish the misbehave nodes?

Unstructured p2p Do it by yourself

Structured p2p Should convince other nodes Or by yourself!

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Conclusions and Discussions

What we learn Topologies

Centralized p2p system• Search cost is bounded• Single point of failure

Decentralized p2p system• Unstructured p2p system

Flexible Unbounded search

• Structured p2p system Scalibility, bounded search Only support keyword query

• Super peer architecture

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Conclusions and Discussions Search

Constraint of hash Dimension reduction and Document retrieval

• Absolute angle• Rolling index• Locality preserving hashing• idistance

Application BT

• For efficiency downloading • Tit for tat

Skype• Super peer architecture

Security Identification Secure nodeId assignment and routing

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Conclusions and Discussions

A better topologies? Robustness Scalibility Flexible Bounded search Fairness Etc.

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Conclusions and Discussions

Support general query? The constraint of hash Similarity search Range query Content-based retrieval

Trust without a third party? nodeId assignment Routing table management Content management

How to decide the score?