Ethereum meanwhile has a different, albeit more high-class problem: Its developer community, some 250,000 strong according to Consensys, is large and ponderous—and that comes at the expense of innovation. On the other hand, the sheer number of developers may help them to wrap the issue up quickly.
Bitcoin’s mining hardware (hashrate) has tripled since December, as can be seen above, even while price has fallen by 3x since December.It is now therefore a lot more expensive to mine a bitcoin than in December, while at the same time one mined bitcoin is worth a lot less.At some point miners are unable to afford energy costs or to keep up with adding more and more hardware as their old one becomes useless due to the constant increase of hashrate difficulty. So they close shop.Some miners, however, like Bitman, have lower costs, presumably because they manufacture themselves the mining hardware.So as other miners struggle, like Bitfury which has now dropped to 2%, Bitmain starts gaining more and more hashrate to the point they are now nearing 51%.The above bitcoin hashrate chart, however, even in a common sense way, looks quite unusual because it rarely goes down, if ever.Rather than responding to the price action, the hashrate appears completely detached. A situation that can not go for much longer because that increased new hardware itself puts pressure on price as the new barely profitable miners need to sell everything to cover costs.
PoW 51% Attack CostThis is a collection of coins and the theoretical cost of a 51% attack on each network.
A few months ago, it was publicly exposed that ASICs had been developed in secret to mine Monero. My sources say that they had been mining on these secret ASICs since early 2017, and got almost a full year of secret mining in before discovery. The ROI on those secret ASICs was massive, and gave the group more than enough money to try again with other ASIC resistant coins.It’s estimated that Monero’s secret ASICs made up more than 50% of the hashrate for almost a full year before discovery, and during that time, nobody noticed. During that time, a huge fraction of the Monero issuance was centralizing into the hands of a small group, and a 51% attack could have been executed at any time.
Smart contracts are fundamentally bad software engineering, part 666 of a never-ending series — PeckShield have been running an automatic scanner on the public Ethereum blockchain:Built on our earlier efforts in analyzing EOS tokens, we have developed an automated system to scan and analyze Ethereum-based (ERC-20) token transfers. Specifically, our system will automatically send out alerts if any suspicious transactions (e.g., involving unreasonably large tokens) occur.They’ve found a couple of beauties, which they’ve branded “BatchOverflow” and “ProxyOverflow.” These affect multiple ERC-20 tokens — which are the basis for almost all ICOs.The root cause is that smart contract coders just copy each other’s code a lot, because who needs formal methods when you can cut’n’paste’n’bodge.
By allowing networks to split, decentralized blockchain platforms protect members against hold up, but hinder coordination, given that adaptation decisions are ultimately decentralized. The current solutions to improve coordination, based on “premining” cryptocoins, taxing members and incentivizing developers, are insufficient. For blockchain to fulfill its promise and outcompete centralized firms, it needs to develop new forms of “soft” decentralized governance (anarchic, aristocratic, democratic, and autocratic) that allow networks to avoid bad equilibria.
Keywords: blockchain, platforms, networks, hold-up, coordination, relational capital, incomplete contracts, decentralized governance
Limits to arbitrage can help explain why Bitcoin has been so bubble-prone. Until recently, it was easy enough to take a long position, but expensive and risky to bet against the cryptocurrency. Things really changed in December, when U.S. regulators allowed the trading of Bitcoin futures. That move came in the middle of a historic runup in the price of Bitcoin and other cryptocurrencies. But as soon as futures contracts began to trade, an interesting thing happened — futures prices suggested that Bitcoin’s growth would slow.What happened next is historic. Bitcoin’s price crashed from a high of about $19,000 to less than $7,000 as of the writing of this article:
Decentralization vs Incoordination – Tadge Dryja (MIT DCI)BPASE ’17, January 26th 2017, Stanford UniversityStanford Cyber Initiative
The conference will explore the use of formal methods, empirical analysis, and risk modeling to better understand security and systemic risk in blockchain protocols. The conference aims to foster multidisciplinary collaboration among practitioners and researchers in blockchain protocols, distributed systems, cryptography, computer security, and risk management.
What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid increase in exchange rates (price) followed by sharp decline; we hypothesise that these fluctuations are largely driven by the interplay between different social phenomena. We thus quantify four socio-economic signals about Bitcoin from large data sets: price on on-line exchanges, volume of word-of-mouth communication in on-line social media, volume of information search, and user base growth. By using vector autoregression, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin adopters. We also observe that spikes in information search, presumably linked to external events, precede drastic price declines. Understanding the interplay between the socio-economic signals we measured can lead to applications beyond cryptocurrencies to other phenomena which leave digital footprints, such as on-line social network usage.