Rindex :: The Robustness Index

The 51% attack resistance-weighted Benchmark for Global PoW Blockchain and Crypto Market

In the H/Rindex: The Hashing Power and Robustness Index, Computational Power-weighted Benchmark for Global Blockchain and Crypto Market paper published last year, we studied several modalities on benchmarking the cryptocurrencies we tried to size each blockchain network by normalizing the hashrate across different hashing algorithms creating Hindex (The Hashing Power Index) and measuring the Robustness creating Rindex (The Robustness Index) which will introduce in simplified way here.

First I wish to shed light on other benchmarks /indexs, and some really has an interesting approach.. further all imported traditional financial models and try to fit it to crypto, from the market capitalization-weighted indexes such as CRIX, Bletchley, TaiFu30, Crypto30, LBI, Smith + Crown SCI, and capped capitalization-weighted such as CRYPTO20, CCX30, and BIT20, smoothed capitalization-weighted such as CCI30, and the cherry-picked ones like ICONOMI DAA(s). here with Rindex we will introduce a native to crypto approach

On the crypto universe, it all boils down to one word “Security”. So many factors are important for cryptocurrency adoption and price market value from the cryptographic algorithm, system features (total supply, speed, transaction cost, privacy, anonymity) to functionality (smart-contract, distributed applications), which could all add or subtract value in accordance with participant perception. The market value “Value-In-Exchange” is not determined by any inherent property in particular, nor by the amount of labor necessary to produce but rather by the importance a participant -an acting individual- places on it for the achievement of desired ends.

However, out of all internal and external factors Security remains at the core with substantially greater value, if not the greatest.

Arguably all other factors’ relative values (and subsequently the price) will diminish to approach zero if a cryptocurrency security is being jeopardized for an extended period. That being said, measuring the system robustness and how it’s secured against vulnerabilities such as the ‘double spending attack’ and others shall be the genesis block of any valuation framework.


Blockchain cryptoassets in general and cryptocurrencies in particular are secure-by-design, however, the question remains — how secure are they? And how would you measure it? And to do so we are going to discuss vulnerabilities and types of major attack vectors as factors for network robustness

A. Consensus 51% attacks resistance factor

The consensus mechanism is a vital feature of a blockchain as it ensures that the majority (if not all participants) of a distributed ledger are in agreement on the data being proposed to update the ledger and enable the network to keep functioning even if some of its members are failing.

Furthermore, this same consensus mechanism is vulnerable to attack by miners (pools, or cartel) If they control 51% or more of hashing power, and they attempt to use their hashing power for destructive ends. They could prevent transactions from being confirmed, reverse recent transactions sent, cause double-spending transactions or execute denial-of-service attacks against specific transactions or addresses including other miners or pools.

Undoubtedly, such a consensus attack would erode confidence in cryptocurrencies in the short term, possibly causing a significant price decline, since the cost of such an attack is significantly high. We assume miners would be working in their best financial interest and a decline in price is no good when you can use your hashing power to actually find blocks. This argument might made sense during the time of Satoshi Nakamoto, — and despite the fact that the attacker may not be motivated by profit-, such an attack is actually financially beneficial and profitable in today’s world with exchange increasingly allowing margin trading, short-selling, future contracts, and flexible order-fulfillment options. For example, the attacker could simply short-sell/put a crypto instrument across multiple major exchanges, and benefit substantially from a price decline.

Cost of 51% attack is a critical factor to be considered in robustness valuation: the higher the cost (barrier to entry), the safer and more robust the network is.

Definition: The 51% attack cost is what would cost to produce (or control) 51% of total hashing power of a cryptocurrency network, and that can be calculated as acquisition cost of the hardware needed to generate the current hashing power + running cost of electricity.

First we identify the most efficient mining equipment for that cryptocurrency hashing algorithm, then how much hashing power that unit produces, and how many units we need to produce the 51% of hashing power of the network (+ adding cost of electricity accordingly)

ex. Antminer S9 is the most efficient ASIC miner for bitcoin today, each unit costs $1265 and offers a hashrate of 13 500 GH/s.

Current bitcoin hashrate is 34,228,020,746.00 GH/s; It means tdhat we need 1,594,668 Unites of Antminer S9 (34,228,020,746.00 / 13,500 = 2,535,408) to produce the current hashrate of the network, and that would cost $5,087,551,587.33 = 2,535,408 Unites * $2000 Price (about ~5 billions dollars) + ~$14mm electricity per day to run a 51% attack on bitcoin network

— Table A1: Cost of 51% Attack across all major PoW cryptocurrencies —

  1. On the original paper of H/Rindex October 2017, we used as base of calculation the most efficient miner for each hash algorithm, using avrage market price per unit, without consideration to supply, for consistency and to price in the supply quantity on the current update we use the miners by Antminer (except for Monero which after Antminer X3, upgraded their protocol to become ASIC-resistant hashing algorithm is called ‘Cryptonight-Heavy’)
  2. Using Antminer S9i for Bitcoin and Bitcoin cash, Antminer E3, Batch 2 for Ehtereum and Ethereum Classic Antminer L3+ for Litecoin, Antminer D3 for DASH, Antminer Z9 mini for zCash and nVidia GTC 1080 for Monero
  3. The selected crypto and sample data of our research here is limited to Proof-of-Work (PoW) hashing algorithm cryptocurrencies, further it can be easily extended to Proof-of-Stake (PoS) cryptos like Lisk, Waves and to any other crypto with a verifiable blockchain consensus mechanism, though other robustness factors (and beside 51% attack cost) have to come in play then as 51% attack by design is way more expensive in PoS -and impractical- than it’s with PoW.

B. Cryptographic attack resistance factor

History has proven that cryptographic schemes can and will be broken, it’s just a matter of time, and developments in quantum computing may play a big role in this in the future, multiple forms of cryptographic attack from preimage attack, to collision attack to all the effect of broken hashing primitives.

The good news is that there is always a possibility of shifting to a stronger algorithm, a protocol upgrade -and forking- to evolve the cryptographic schemes used whenever they get broken. This is as long as there are a community and core developers behind to react swiftly and dynamically, not only for pure cryptographic vulnerabilities but code general security flows.


We calculate each cryptocurrency constituent robustness (currently the quantified factor is 51% attack cost, while other factors used binary for selection criteria); And each constituent will be represented by its 51% attack cost as a percentage of all index constituents 51% attack cost.

Traditional Cryptocurrency Marketcap-weigted Index Vs. Rindex: Robustness and 51% attack resistance-weighted Index
Rindex, Robustness Weighted Index, (constituent represented by its 51% attack cost as a percentage of all index constituents)


Classic Marketcap Weighted Index

To universe with new dimensions and its own nature

As Cryptoeconomics is a new emerging discipline it is understandable to see several tentative to apply traditional economical and financial models, trying to make sense of this new universe, while it’s true there is some similarities, and nothing fundamentally wrong with applying these models, we need to observe with caution the new dimensions of this universe, and develop models native to its true nature.

On The blockFrame Charting for Crypto I introduced blockFrame concept for graphic charting — blockframe instead of timeframe for crypto universe where objective time doesn’t exist in the distinctive sense, and the advance, progress, and succession; take place with the creation of new blocks, charting over block-height is native to crypto, as all events timed on block-height, from difficulty adjustment to halfing to protocol upgrade and forking.

And on H/Rindex paper and on this article here about Robustness Index we introduce Robustness & Computational Power-weighted benchmarks, as an alternative to traditional Market-Capitalization weighted modalities..

The thing that S&P, Nasdaq, Hang Seng Index and other benchmark stocks that has intrinsic value, McDonald’s own of 35,000 outlets worldwide, and Apple and Google has cash-flow and few hundred billion on revenue, Bitcoin and Ethereum has no intrinsic value on the traditional way (lucky us), but the closest to it or the transvaluation of intrinsic value in crypto universe is the computational power and the capacity of the decentralize nodes to maintain consensus and to be secured against vulnerabilities.


Today, like no other time before, there is a tremendous financial benefit for a malicious attacker, to perform the most obvious sort of attack, 51% consensus attack:

  1. Short-sell and future market, derivatives, and liquidity
  2. Margin trading 5x, 10x, 50x and even 100x
  3. Industrialization, ASIC and mass production of mining equipment

All together make the cost of entry lower (mass production and ASIC) and much more lucrative to execute (short-selling with margin to benefit from price decline)

For that we’re building Rindex.io; To benchmark the robustness, to educate, and raise awareness of blockchain networks security and attack vectors and toward preventing an actual large-scale profitable attack from becoming a reality.