📅 Original date posted:2023-05-10
🗒️ Summary of this message: Reputation systems in Lightning are susceptible to sudden behavioral changes and whitewashing attacks, making their usefulness questionable. Local-only reputation systems may work for large routing nodes, but edges may be more vulnerable.
📝 Original message:
Hi Antoine,
this is an intrinsic issue with reputation systems, and the main
reason I'm sceptical w.r.t. their usefulness in lightning.
Fundamentally any reputation system bases their expectations for the
future on experiences they made in the past, and they are thus always
susceptible to sudden behavioral changes (going rogue from a prior
clean record) and whitewashing attacks (switching identity, abusing
any builtin bootstrapping method for new users to gain a good or
neutral reputation before turning rogue repeatedly).
This gets compounded as soon as we start gossiping about reputations,
since now our decisions are no longer based just on information we can
witness ourselves, or at least verify its correctness, and as such an
attacker can most likely "earn" a positive reputation in some other
part of the world, and then turn around and attack the nodes that
trusted the reputation shared from those other parts.
I'd be very interested in how many repeat interactions nodes get from
individual senders, since that also tells us how much use we can get
out of local-only reputation based systems, and I wouldn't be
surprised if, for large routing nodes, we have sufficient data for
them to make an informed decision, while the edges may be more
vulnerable, but they'd also be used by way fewer senders, and the
impact of an attack would also be proportionally smaller.
Cheers,
Christian
On Mon, May 8, 2023 at 10:26 PM Antoine Riard <antoine.riard at gmail.com> wrote:
>
> Hi *,
>
> > Our suggestion is to start simple with a binary endorsement field. As
> > we learn more, we will be better equipped to understand whether a
> > more expressive value is required.
>
> I think the HTLC endorsement scheme as proposed is still suffering from a vulnerability as local reputation can be built up during periods of low routing fees, endorsement gained and then abused during periods of high routing fees. Therefore, it sounds to me this scheme should aim for some reputational transitivity between incoming traffic and outgoing traffic. Namely, the acquisition cost of the local reputation should be equal to the max timevalue damage that one can inflict on a routing node channel accessible from its local counterparty granting this high-level of reputation.
>
> I don't know if this can be fixed by ensuring permanent link-level "gossip" where counterparties along a payment path expose their reputation heuristics to guarantee this transitivity, or it's a fundamental issue with a point-to-point approach like HTLC endorsement.
>
> Opened an issue on the repository to converge on a threat model:
> https://github.com/ClaraShk/LNJamming/pull/13
>
> I still think building data gathering infrastructure for Lightning is valuable as ultimately any jamming mitigation will have to adapt its upfront fees or reputation acquisition cost in function of HTLC traffic and market forces.
>
> Looking forward to giving an update on Staking Credentials [0], an end-to-end approach to mitigate channel jamming.
>
> Best,
> Antoine
>
> [0] https://lists.linuxfoundation.org/pipermail/lightning-dev/2022-November/003754.html
>
> Le dim. 30 avr. 2023 à 03:57, Carla Kirk-Cohen <kirkcohenc at gmail.com> a écrit :
>>
>> Hi list,
>>
>> Some updates on channel jamming!
>>
>> # Next Call
>> - Monday 01 May @ 15:00 UTC
>> - https://meet.jit.si/UnjammingLN
>> - Agenda: https://github.com/ClaraShk/LNJamming/issues/12
>>
>> # Data Gathering
>> During these weekly calls, we've come to agreement that we would like
>> to gather data about the use of HTLC endorsement and local reputation
>> tracking for jamming mitigation. A reminder of the full scheme is
>> included at the end of this email, and covered more verbosely in [1].
>>
>> We have a few goals in mind:
>> - Observe the effect of endorsement in the steady state with
>> logging-only implementation.
>> - Gather real-world data for use in future simulation work.
>> - Experiment with different algorithms for tracking local reputation.
>>
>> The minimal changes required to add HTLC endorsement are outlined in [2].
>> Our suggestion is to start simple with a binary endorsement field. As
>> we learn more, we will be better equipped to understand whether a
>> more expressive value is required.
>>
>> With this infrastructure in place, we can start to experiment with
>> various local reputation schemes and data gathering, possibly even
>> externally to LN implementations in projects like circuitbreaker [3].
>> We'd be interested to hear whether there's any appetite to deploy using
>> an experimental TLV value?
>>
>> # Reputation Scheme
>> - Each node locally tracks the reputation of its direct neighbors.
>> - Each node allocates, per its risk tolerance:
>> - A number of slots reserved for endorsed HTLCs from high reputation
>> peers.
>> - A portion of liquidity reserved for endorsed HTLCs from high
>> reputation peers.
>> - Forwarding of HTLCs:
>> - If a HTLC is endorsed by a high reputation peer, it is forwarded
>> as usual with endorsed = 1.
>> - Otherwise, it is forwarded with endorsed = 0 if there are slots and
>> liquidity available for unknown HTLCs.
>>
>> Endorsement and reputation are proposed as the first step in a two part
>> scheme for mitigating channel jamming:
>> - Reputation for slow jams which are easily detected as misbehavior.
>> - Unconditional fees for quick jams that are difficult to detect, as
>> they can always fall under a target threshold.
>>
>> Looking forward to discussing further in the upcoming call!
>>
>> Best,
>> Carla and Clara
>>
>> [1] https://gist.github.com/carlaKC/be820bb638624253f3ae7b39dbd0e343
>> [2] https://github.com/lightning/bolts/pull/1071
>> [3] https://github.com/lightningequipment/circuitbreaker
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>
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