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scheme. svn:r6008
302 lines
14 KiB
Plaintext
302 lines
14 KiB
Plaintext
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Tor Incentives Design Brainstorms
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1. Goals: what do we want to achieve with an incentive scheme?
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1.1. Encourage users to provide good relay service (throughput, latency).
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1.2. Encourage users to allow traffic to exit the Tor network from
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their node.
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2. Approaches to learning who should get priority.
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2.1. "Hard" or quantitative reputation tracking.
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In this design, we track the number of bytes and throughput in and
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out of nodes we interact with. When a node asks to send or receive
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bytes, we provide service proportional to our current record of the
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node's value. One approach is to let each circuit be either a normal
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circuit or a premium circuit, and nodes can "spend" their value by
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sending and receiving bytes on premium circuits: see section 4.1 for
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details of this design. Another approach (section 4.2) would treat
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all traffic from the node with the same priority class, and so nodes
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that provide resources will get and provide better service on average.
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This approach could be complemented with an anonymous e-cash
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implementation to let people spend reputations gained in one context
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in another context.
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2.2. "Soft" or qualitative reputation tracking.
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Rather than accounting for every byte (if I owe you a byte, I don't
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owe it anymore once you've spent it), instead I keep a general opinion
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about each server: my opinion increases when they do good work for me,
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and it decays with time, but it does not decrease as they send traffic.
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Therefore we reward servers who provide value to the system without
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nickle and diming them at each step. We also let them benefit from
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relaying traffic for others without having to "reserve" some of the
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payment for their own use. See section 4.3 for a possible design.
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2.3. Centralized opinions from the reputation servers.
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The above approaches are complex and we don't have all the answers
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for them yet. A simpler approach is just to let some central set
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of trusted servers (say, the Tor directory servers) measure whether
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people are contributing to the network, and provide a signal about
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which servers should be rewarded. They can even do the measurements
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via Tor so servers can't easily perform only when they're being
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tested. See section 4.4.
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2.4. Reputation servers that aggregate opinions.
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The option above has the directory servers doing all of the
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measurements. This doesn't scale. We can set it up so we have "deputy
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testers" -- trusted other nodes that do performance testing and report
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their results. If we want to be really adventurous, we could even
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accept claims from every Tor user and build a complex weighting /
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reputation system to decide which claims are "probably" right.
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3. Related issues we need to keep in mind.
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3.1. Relay and exit configuration needs to be easy and usable.
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Implicit in all of the above designs is the need to make it easy to
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run a Tor server out of the box. We need to make it stable on all
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common platforms (including XP), it needs to detect its available
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bandwidth and not overreach that, and it needs to help the operator
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through opening up ports on his firewall. Then we need a slick GUI
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that lets people click a button or two rather than editing text files.
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Once we've done all this, we'll hit our first big question: is
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most of the barrier to growth caused by the unusability of the current
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software? If so, are the rest of these incentive schemes superfluous?
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3.2. The network effect: how many nodes will you interact with?
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One of the concerns with pairwise reputation systems is that as the
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network gets thousands of servers, the chance that you're going to
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interact with a given server decreases. So if 90% of interactions
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don't have any prior information, the "local" incentive schemes above
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are going to degrade. This doesn't mean they're pointless -- it just
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means we need to be aware that this is a limitation, and plan in the
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background for what step to take next. (It seems that e-cash solutions
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would scale better, though they have issues of their own.)
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3.3. Guard nodes
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As of Tor 0.1.1.11, Tor users pick from a small set of semi-permanent
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"guard nodes" for their first hop of each circuit. This seems to have
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a big impact on pairwise reputation systems since you will only be
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cashing in on your reputation to a few people, and it is unlikely
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that a given pair of nodes will use each other as guard nodes.
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What does this imply? For one, it means that we don't care at all
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about the opinions of most of the servers out there -- we should
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focus on keeping our guard nodes happy with us.
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One conclusion from that is that our design needs to judge performance
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not just through direct interaction (beginning of the circuit) but
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also through indirect interaction (middle of the circuit). That way
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you can never be sure when your guards are measuring you.
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3.4. Restricted topology: benefits and roadmap.
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As the Tor network continues to grow, we will need to make design
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changes to the network topology so that each node does not need
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to maintain connections to an unbounded number of other nodes. For
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anonymity's sake, we may partition the network such that all
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the nodes have the same belief about the divisions and each node is
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in only one partition. (The alternative is that every user fetches
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his own random subset of the overall node list -- this is bad because
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of intersection attacks.)
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Therefore the "network horizon" for each user will stay bounded,
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which helps against the above issues in 3.2 and 3.3.
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It could be that the core of long-lived servers will all get to know
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each other, and so the critical point that decides whether you get
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good service is whether the core likes you. Or perhaps it will turn
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out to work some other way.
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A special case here is the social network, where the network isn't
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partitioned randomly but instead based on some external properties.
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Social network topologies can provide incentives in other ways, because
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people may be more inclined to help out their friends, and more willing
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to relay traffic if only their friends are relaying through them. It
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also opens the door for out-of-band incentive schemes because of the
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out-of-band links in the graph.
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3.5. Profit-maximizing vs. Altruism.
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There are some interesting game theory questions here.
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First, in a volunteer culture, success is measured in public utility
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or in public esteem. If we add a reward mechanism, there's a risk that
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reward-maximizing behavior will surpass utility- or esteem-maximizing
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behavior.
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Specifically, if most of our servers right now are relaying traffic
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for the good of the community, we may actually *lose* those volunteers
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if we turn the act of relaying traffic into a selfish act.
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I am not too worried about this issue for now, since we're aiming
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for an incentive scheme so effective that it produces thousands of
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new servers.
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3.6. What part of the node's performance do you measure?
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We keep referring to having a node measure how well the other nodes
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receive bytes. But don't leeching clients receive bytes just as well
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as servers?
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Further, many transactions in Tor involve fetching lots of
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bytes and not sending very many. So it seems that we want to turn
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things around: we need to measure how quickly a node can _send_
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us bytes, and then only send it bytes in proportion to that.
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However, a sneaky user could simply connect to a node and send some
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traffic through it, and voila, he has performed for the network. This
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is no good. The first fix is that we only count if you're receiving
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bytes "backwards" in the circuit. Now the sneaky user needs to
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construct a circuit such that his node appears later in the circuit,
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and then send some bytes back quickly.
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Maybe that complexity is sufficient to deter most lazy users. Or
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maybe it's an argument in favor of a more penny-counting reputation
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approach.
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3.7. What is the appropriate resource balance for servers vs. clients?
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If we build a good incentive system, we'll still need to tune it
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to provide the right bandwidth allocation -- if we reserve too much
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bandwidth for fast servers, then we're wasting some potential, but we
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if we reserve too little, then fewer people will opt to become servers.
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In fact, finding an optimum balance is especially hard because it's
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a moving target: the better our incentive mechanism (and the lower
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the barrier to setup), the more servers there will be. How do we find
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the right balance?
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One answer is that it doesn't have to be perfect: we can err on the
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side of providing extra resources to servers. Then we will achieve our
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desired goal -- when people complain about speed, we can tell them to
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run a server, and they will in fact get better performance.
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3.8. Anonymity attack: fast connections probably come from good servers.
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If only fast servers can consistently get good performance in the
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network, they will stand out. "Oh, that connection probably came from
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one of the top ten servers in the network." Intersection attacks over
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time can improve the certainty of the attack.
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I'm not too worried about this. First, in periods of low activity,
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many different people might be getting good performance. This dirties
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the intersection attack. Second, with many of these schemes, we will
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still be uncertain whether the fast node originated the traffic, or
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was the entry node for some other lucky user -- and we already accept
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this level of attack in other cases such as the Murdoch-Danezis attack
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(http://freehaven.net/anonbib/#torta05).
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3.9. How do we allocate bandwidth over the course of a second?
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This may be a simple matter of engineering, but it still needs to be
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addressed. Our current token bucket design refills each bucket once a
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second. If we have N tokens in our bucket, and we don't know ahead of
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time how many connections are going to want to send how many bytes,
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how do we balance providing quick service to the traffic that is
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already here compared to providing service to potential high-importance
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future traffic?
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If we have only two classes of service, here is a simple design:
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At each point, when we are 1/t through the second, the total number
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of non-priority bytes we are willing to accept is N/t. Thus if N
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priority bytes arrive at the beginning of the second, we drain our
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whole bucket then, and otherwise we provide some delayed service to
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the non-priority bytes.
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Does this design expand to cover the case of three priority classes?
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Ideally we'd give each remote server its own priority number. Or
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hopefully there's an easy design in the literature to point to --
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this is clearly not my field.
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4. Sample designs.
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4.1. Two classes of service for circuits.
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4.2. Treat all the traffic from the node with the same service;
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hard reputation system.
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4.3. Treat all the traffic from the node with the same service;
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soft reputation system.
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Rather than a guaranteed system with accounting (as 4.1 and 4.2),
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we instead try for a best-effort system. All bytes are in the same
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class of service. You keep track of other Tors by key, and give them
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service proportional to the service they have given you. That is, in
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the past when you have tried to push bytes through them, you track the
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number of bytes and the average bandwidth, and use that to weight the
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priority of their connections if they try to push bytes through you.
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Now you're going to get minimum service if you don't ever push bytes
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for other people, and you get increasingly improved service the more
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active you are. We should have memories fade over time (we'll have
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to tune that, which could be quite hard).
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Pro: Sybil attacks are pointless because new identities get lowest
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priority.
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Pro: Smoothly handles periods of both low and high network load. Rather
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than keeping track of the ratio/difference between what he's done for
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you and what you've done for him, simply keep track of what he's done
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for you, and give him priority based on that.
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Based on 3.3 above, it seems we should reward all the nodes in our
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path, not just the first one -- otherwise the node can provide good
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service only to its guards. On the other hand, there might be a
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second-order effect where you want nodes to like you so that *when*
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your guards choose you for a circuit, they'll be able to get good
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performance. This tradeoff needs more simulation/analysis.
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This approach focuses on incenting people to relay traffic, but it
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doesn't do much for incenting them to allow exits. It may help in
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one way through: if there are few exits, then they will attract a
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lot of use, so lots of people will like them, so when they try to
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use the network they will find their first hop to be particularly
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pleasant. After that they're like the rest of the world though.
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Pro: this is a pretty easy design to add; and it can be phased in
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incrementally simply by having new nodes behave differently.
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4.4. Centralized opinions from the reputation servers.
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Have a set of official measurers who spot-check servers from the
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directory to see if they really do offer roughly the bandwidth
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they advertise. Include these observations in the directory. (For
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simplicity, the directory servers could be the measurers.) Then Tor
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servers give priority to other servers. We'd like to weight the
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priority by advertised bandwidth to encourage people to donate more,
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but it seems hard to distinguish between a slow server and a busy
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server.
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The spot-checking can be done anonymously to prevent selectively
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performing only for the measurers, because hey, we have an anonymity
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network.
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We could also reward exit nodes by giving them better priority, but
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like above this only will affect their first hop. Another problem
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is that it's darn hard to spot-check whether a server allows exits
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to all the pieces of the Internet that it claims to. If necessary,
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perhaps this can be solved by a distributed reporting mechanism,
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where clients that can reach a site from one exit but not another
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anonymously submit that site to the measurers, who verify.
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A last problem is that since directory servers will be doing their
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tests directly (easy to detect) or indirectly (through other Tor
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servers), then we know that we can get away with poor performance for
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people that aren't listed in the directory. Maybe we can turn this
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around and call it a feature though -- another reason to get listed
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in the directory.
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5. Recommendations and next steps.
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