Whenever I read Vitalik's work, I find myself convinced that all of society and its various problems can be boiled down to incentives and their alignment or misalignment.
That's the basic premise that drives economic theory.
Trust Models
21–30 of 33 posts
Re: Trust Models
#22It seems odd to not discuss the more fundamental issues of trusting the infrastructure. All this virtual reality is on top of a physical reality controlled by governments and powerful interests. What happens when said powers declare cryptocurrencies illegal (app store removals, RST packets, etc.), or try to take them over with brute force?
> It seems odd to not discuss the more fundamental issues of trusting the infrastructure. It would be odd if the Blockchain / Crypto-currency market came crashing down. Like most nutritionists who do not understand the popularity of sugary drinks or fast food chains, I think, news.yc fails to understand the Crypto-currency / Blockchain market.
I am sure that nutritionists _understand_ the popularity of sugary drinks, as in, they know what human motivations are, and they know why people prefer them to better foods.
But nutritionists also _understand_ that sugary drinks are bad in the long run, and that is why they keep saying that one should drink less of them, over and over. If at least few people get convinced, stop drinking sugary drinks, and avoid diabetes and heart disease, they nutritionists succeeded.
The same logic applies to blockchain/crypto-currency warnings that HN commenters produce.
Re: Trust Models
#23It seems odd to not discuss the more fundamental issues of trusting the infrastructure. All this virtual reality is on top of a physical reality controlled by governments and powerful interests. What happens when said powers declare cryptocurrencies illegal (app store removals, RST packets, etc.), or try to take them over with brute force?
Some of them are censorship resistant
Re: Trust Models
#24His views are just simplistic, too simplistic. Additionally, he delves in topics that have been already looked at in a more abstract way.
yet he probably is more educated on the subject than you.
Re: Trust Models
#25It seems odd to not discuss the more fundamental issues of trusting the infrastructure. All this virtual reality is on top of a physical reality controlled by governments and powerful interests. What happens when said powers declare cryptocurrencies illegal (app store removals, RST packets, etc.), or try to take them over with brute force?
This tends to be a focus of the Bitcoin community a lot more than other cryptocurrency communities. Bitcoin has technologies such as ASN based sybil attack protections [1], satellite broadcasts that cover most of the land area of the earth [2], and setups that allow Bitcoin to be broadcast over Ham Radio [3]. Of course that's not to say the problem is ignored by other communities. Many people are well aware of the fu…
Good points.
Oh and FYI the idiom is "worse comes to worst" (analogous to "push comes to shove" -- an intensification past an activation threshold or tipping-point)
Re: Trust Models
#26Earlier quoted context omitted.
Not related to this topic, but I recently watched Lex Fridman's podcast episode with him and it was really interesting as well: https://www.youtube.com/watch?v=3x1b_S6Qp2Q .
Yes, also a good one. I'd recommend pretty much all of Lex Fridman's and Eric Weinstein's podcast episodes in general. Lots of insightful conversations with (in my opinion) some of the most interesting people in the world. Links for anyone curious: Eric Weinstein's The Portal Podcast - https://www.youtube.com/playlist?list=PLq9jO8fmlPee9ezOraOHA... Lex Fridman's Artificial Intelligence Podcast - https://www.youtube.c…
These are all great links, thank you!
Re: Trust Models
#27Earlier quoted context omitted.
This tends to be a focus of the Bitcoin community a lot more than other cryptocurrency communities. Bitcoin has technologies such as ASN based sybil attack protections [1], satellite broadcasts that cover most of the land area of the earth [2], and setups that allow Bitcoin to be broadcast over Ham Radio [3]. Of course that's not to say the problem is ignored by other communities. Many people are well aware of the fu…
These are all cool technologies which raise the bar an attacker must meet in order to disrupt Bitcoin, but it's worth noting that at very least America and China could absolutely overwhelm those defenses. The security of nakamoto consensus (Bitcoin and co) relies on a level of broadcast which is pretty incompatible with a world where the network is hostile and looking to disrupt your traffic.
> relies on a level of broadcast which is pretty incompatible with a world where the network is hostile and looking to disrupt your traffic.
It would be prohibitively expensive and difficult to disrupt point-to-point radio (e.g. ham) and satellite communications enough to cripple Bitcoin.
Re: Trust Models
#28Earlier quoted context omitted.
>If you invert the colours in the chart, you also get the consequences of their failure modes. Forgive me if I am misunderstanding what you are saying, but it sounds to me like you are suggesting that the consequences of a 1-of-N failure are inherently worse than the consequences of an N-of-N failure, which is not a fundamental truth in any way. It is entirely possible for a 1-of-N system to have better recovery mode…
The point I was making is that in the 1/N system, the failure of the one person or element brings the whole thing down, it's a single catastrophic failure mode, where when N/N at the other extreme, the failure is contained to that group. The partial ones mean that the number of people/parts that have to fail is greater to bring the whole system down. (the example case is storing a single shared secret, which if compr…
I think you misunderstand what a 1 of N system means here. It means out of N participants, any of them are sufficient to keep the network safe.
In any system, if N out of N participants are down, you are going to have a hard time resetting. Typically it is easiest to reset from this failure in a 1 of N system because you only need one person to recover, and it doesn't matter which person.
I'm oversimplifying a bit, but in most cases a 1 of N system is strictly more robust than a N/2 of N system. (Or any system that requires more than one honest participant).
Re: Trust Models
#29Whenever I read Vitalik's work, I find myself convinced that all of society and its various problems can be boiled down to incentives and their alignment or misalignment.
“Never, ever, think about something else when you should be thinking about the power of incentives.” — Charlie Munger, https://fs.blog/2017/10/bias-incentives-reinforcement/
Mechanism design is a subfield of game theory and economics called mechanism design that tackles this directly.
Instead of having a game and figuring out how it works and what is the outcome is when agents play it, the problem is to design a game that creates desired outcomes when selfish agents play it.
It's possible to design mechanisms where utilitarian social-choice function is the best choice even when players are selfish. The most famous result in the field is Vickrey–Clarke–Groves mechanism to achieve a socially-optimal solution in auctions. Quadratic voting and quadratic funding is another interesting mechanism that results good outcomes. Vitalik Buterin is involved with this too.
Re: Trust Models
#30Earlier quoted context omitted.
The point I was making is that in the 1/N system, the failure of the one person or element brings the whole thing down, it's a single catastrophic failure mode, where when N/N at the other extreme, the failure is contained to that group. The partial ones mean that the number of people/parts that have to fail is greater to bring the whole system down. (the example case is storing a single shared secret, which if compr…
I think you misunderstand what a 1 of N system means here. It means out of N participants, any of them are sufficient to keep the network safe. In any system, if N out of N participants are down, you are going to have a hard time resetting. Typically it is easiest to reset from this failure in a 1 of N system because you only need one person to recover, and it doesn't matter which person. I'm oversimplifying a bit, b…
I think I do get your point, however my emphasis is on when you replace "person," with "key," or "secret," it explains the consequences of the key distribution problem.
The system that requires only one honest participant seems stable, except when that one person has a small but non-zero likelihood of compromise. A system that requires N/2 honest people - each of whom have a probability of compromise, it depends on whether that probability is independent or dependent. In the dependent case, you are correct, the more people you need to trust, the higher the likelihood of one bringing whole thing down, but in the independent (e.g. federated) case, the consequences are contained.
I'm saying that the diagram as interpreted from the perspective of the consequences of failure shows that if you turn the 1/N section red instead of green, it indicates the level of catastrophe. We could be running up against the limits of the chart's heuristic analogy, but viewing trust as flowing downstream over time from the root node of a tree , and asking how many root nodes of trust you need for a robust system, shows that the fewer the roots of trust, the greater the impact of a compromise.
I'd considered whether replacing those node keys with multipart keys would change things, but the whole concept of a compromise is an exogenous phenomenon, that is, what this trust tree/graph is made of doesn't change the effect of some super force finding a way to compromise a node. If a trust model is just a graph, then it will be the properties of that graph that determine the qualities of the model - and not what the nodes and relationships themselves are made of.
That final point would be my big-leap conjecture.