StakeSure & @eigenlayer: Strong cryptoeconomic security
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Prior definitions of cryptoeconomic security were adversary-centric.
Cryptoeconomic security: For any attack & adversary,
Cost of corruption > Profit from corruption
where cost of corruption is the minimum amount slashable to the adversary and pfc is the total profit that can be extracted by the adversary.
To check whether the condition is satisifed, it requires modeling the adversaries fully. This is complex, if not outright impossible:
a) the adversary may have an extrinsic incentive like a short position to increase the profit from corruption.
b) the adversary may have extrinsic reasons to have lower cost of corruption - for example, the adversary is custodying someone else's funds (called the principal agent problem).
This foundational issue was memorialized in a paper titled "Rationality is Self-Defeating in Permissionless Systems" ().
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In our recent work StakeSure (), we redefined cryptoeconomic security.
We flipped the viewpoint from the adversary viewpoint to the *protocol* viewpoint or the protocol user viewpoint.
Strong cryptoeconomic security:
For any attack,
Redistributable stake > Harm from corruption to protocol (or protocol user)
The idea is that the slashed funds are redistributed to the protocol (or protocol users) and hence if the protocol ensures that the total funds that can be redistributed to users upon protocol failure is greater than the funds that can be harmed, then the protocol has strong cryptoeconomic security. Once this equation is satisfied, it is irrelevant to the protocol what the intention of the adversary is! No matter what the intention of the adverary, the protocol remains solvent!
This equation is fully calculable onchain. For example, in the case of a bridge, harm from corruption is the amount of money that can be stolen from the bridge within the fraud proof period (weekly transaction volume say). Redistributable stake is the amount of stake that is uniquely attributable for the fault - also an onchain measurable.
In the case of a bridge which is transacting in arbitrary quantities (like NFTs), the bridge can let each transaction specify how much redistributable-stake that particular transaction needs in terms of a failure. This ensures that protocol *users* can self-specify how much security they want. This is analogous to how when shipping a fedex parcel, you can self specify how much insurance is needed (by declaring the value and paying a premium).
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Adversary-lens
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The adversary can take a short position outside - yes - but it does not matter.
The adversary may be a CEX that is using customer funds to attack the system - yes - but it does not matter to the protocol. Of course, when a user deposits funds to a CEX they are trusting that the CEX handles the funds safely - otherwise they should not deposit to the CEX.
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How does it circumvent the "impossibility" result in
Assumption 3: The system S actually leverages in some fashion the behavioral assumption(s) it makes on participants, such as a rationality assumption.
StakeSure makes each participant make *an assumption* ONLY about themself - they specify how much insurance they themself want rather than having to imagine how other participants act (including other users)!!! Even if other users specify redistributable stake lesser than their true value and the system gets attack, the honest user who specified their redistributable stake correctly is ALWAYS solvent - it will be able to redistribute its portion of the stake.
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StakeSure transforms the cryptoeconomic landscape completely. 1) Exactly measure how much cryptoeconomic security is sufficient, rather than have random curves define it. 2) Self-scale the amount of security. If more redistributable security is needed, the protocol users become willing to pay more. 3) Isolation of safety. If a certain user holds a certain amount of redistributable stake, then they do not need to model any other users who they may be sharing the platform with. 4) Compensation: Users of the platform will be compensated if something goes wrong, completing the system of "karma". 5) Universality: Any application can self-specify the amount of harm-from-corruption so that many applications can share a common staking system.
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Tagging PoS builders and experts
@VitalikButerin @Tim_Roughgarden @zmanian @aeyakovenko @drakefjustin @JTremback @sunnya97 @valardragon @dankrad @zooko @muneeb @rphmeier @dntse @jneu_net @karl_dot_tech @phildaian @danrobinson @gakonst @buchmanster @musalbas @sgoldfed @EdFelten @toghrulmaharram @yilongl_megaeth @yangl1996 @yq_acc @gluk64 @sandeepnailwalarxiv.org/abs/1910.08820
In this thread, I will present the story of our journey to build EigenDA from a personal vantage point. This story will lay out our longstanding interest in scaling network bandwidth as well as offer some inside anecdotes.
My interest in “cooperative” p2p networks dates before blockchains. Here is a 2008 paper, where we designed new network “erasure” coding schemes for wireless networks:
I had moved on from p2p wireless in my PhD to work on computational genomics by 2013. For example, in this paper with @xiaojie_qiu, we design new methods for gene regulatory network inference using single cell RNA sequencing data: cell.com/cell-systems/p…
Definition: coprocessor is a stateless offchain system and rollup is a stateful offchain system.
When does a coprocessor suffice? When the computation inputs are fully specified onchain and the state change has to be actuated onchain.
Let’s start with a motivating example.
Imagine you want to build a @Uniswap LP strategy or v4 hook that adjusts the price or fees based on a AI model factoring the history of onchain transaction toxicity. (Cc @haydenzadams @danrobinson @0x94305).
Refined view: There are 5 properties that together make a *confirmation rule* secure. We colloquially talk about a chain being secure but really it is the confirmation rule to which the security property attaches.
This difference occurs because a single chain can admit multiple confirmation rules. For example, in Bitcoin, different nodes can use different depths in their confirmation rules and they will accordingly have different probabilities of safety violations.
A starker contrast occurs in Ethereum, in the gasper protocol, there are two distinct confirmation rules - an available rule (based on the heaviest chain) and a finalized rule (based on blocks confirmed by the gadget).
We welcome this excellent analysis of the different kinds of risks using restaking for different use cases a la @eigenlayer by @VitalikButerin. It is consistent with what we have been advocating with Eigenlayer. A brief summary here:
a) don’t build complex financial primitives on restaking - they can spiral out
b) don’t rely on Ethereum to fork for application layer errors - this is a super important principle
c) do not use subjective slashing - as it is subject to tyranny of the dishonest majority
Low risks
a) Use restaking for highly objective attributable misbehaviors such as double signing
b) Use restaking purely for getting the decentralization benefits of Ethereum without slashing
We recently announced the Series A for @eigenlayer led by @blockchaincap. In this thread I will highlight several key investors in the seed round, which was co-led by @polychaincap and @etherealvc.
The first investment offer for @eigenlayer came from @etherealvc, back in Sep 2021. It has been an absolutee privilege to work with @_MinTeo and @bees_neeth at Ethereal ventures. They have been a close working partner and a strong pillar of support from the very beginning!
P.S. Mycelia are fungi that help connect roots of trees in order to help them exchange nutrients. We think this is an apt metaphor for restaking!
I covered four different usecases: A1) event driven actions, A2) partial block auctions, A3) threshold cryptography, A4) long term block auctions, and their composibility A1234) in the talk.