Bitcoin Transaction Graph Analysis - MIT CSAIL

Bitcoin Transaction Graph Analysis: Challenging bitcoin anonymity

submitted by IsaacLean to Bitcoin [link] [comments]

Quantitative Analysis of the Full Bitcoin Transaction Graph

submitted by gasche to programming [link] [comments]

Quantitative Analysis of the Full Bitcoin Transaction Graph

submitted by 678 to spremnik [link] [comments]

Cracking Bitcoin’s Pseudo-Anonymity – Part II (Blockchain’s Transaction Graph Analysis)

Cracking Bitcoin’s Pseudo-Anonymity – Part II (Blockchain’s Transaction Graph Analysis) submitted by Cryptofortune to Bitcoin [link] [comments]

Quantitative Analysis of the Full Bitcoin Transaction Graph, Dorit Ron and Adi Shamir

submitted by Julian702 to crypto [link] [comments]

Cracking Bitcoin’s Pseudo-Anonymity – Part II (Blockchain’s Transaction Graph Analysis)

Cracking Bitcoin’s Pseudo-Anonymity – Part II (Blockchain’s Transaction Graph Analysis) submitted by Cryptofortune to btc [link] [comments]

Cracking Bitcoins Pseudo-Anonymity Part II (Blockchains Transaction Graph Analysis)

Cracking Bitcoins Pseudo-Anonymity Part II (Blockchains Transaction Graph Analysis) submitted by BitcoinAllBot to BitcoinAll [link] [comments]

Quantitative Analysis of the Full Bitcoin Transaction Graph (.pdf)

submitted by xoday to Bitcoin [link] [comments]

Quantitative Analysis of the Full Bitcoin Transaction Graph

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Quantitative Analysis of the Full Bitcoin Transaction Graph, Dorit Ron and Adi Shamir

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Quantitative Analysis of the Full Bitcoin Transaction Graph, Dorit Ron and Adi Shamir

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In Light of CipherTrace, Let's Talk Opsec

So I was very skeptical at first, but Dave maybe convinced me about 10% that they have some level of capability in the direction they're suggesting. The techniques are stuff we've known, and it would require large computational resources, combined with loads of offchain data, but maybe they have taken efforts to the next level. It's my belief that govts and banks really dislike Monero. So with that in mind lets give them some small benefit of the doubt and take some creative license:
Again, they would need some serious computational power and off-chain data feeds. I also imagine that their models suffer from time-decay, especially without a constant stream of hueristic data. Notice at the end he emphasized opsec. Here, I really do believe him. So finally, lets talk opsec.
I have mixed feelings on this. One of our selling points is default privacy made easy. A lot of what I wrote above doesn't exactly sound simple. On the other hand, crypto is about self responsibility and knowledge. Most people ought to have been adhering to at least the basics (ToVPN, new subaddresses, run your own node). But even if we give CT the benefit of the doubt, the following is still true:
Newb use of Monero is far more private than ninja use of Bitcoin.
submitted by bawdyanarchist to Monero [link] [comments]

Syscoin Platform’s Great Reddit Scaling Bake-off Proposal

Syscoin Platform’s Great Reddit Scaling Bake-off Proposal

https://preview.redd.it/rqt2dldyg8e51.jpg?width=1044&format=pjpg&auto=webp&s=777ae9d4fbbb54c3540682b72700fc4ba3de0a44
We are excited to participate and present Syscoin Platform's ideal characteristics and capabilities towards a well-rounded Reddit Community Points solution!
Our scaling solution for Reddit Community Points involves 2-way peg interoperability with Ethereum. This will provide a scalable token layer built specifically for speed and high volumes of simple value transfers at a very low cost, while providing sovereign ownership and onchain finality.
Token transfers scale by taking advantage of a globally sorting mempool that provides for probabilistically secure assumptions of “as good as settled”. The opportunity here for token receivers is to have an app-layer interactivity on the speed/security tradeoff (99.9999% assurance within 10 seconds). We call this Z-DAG, and it achieves high-throughput across a mesh network topology presently composed of about 2,000 geographically dispersed full-nodes. Similar to Bitcoin, however, these nodes are incentivized to run full-nodes for the benefit of network security, through a bonded validator scheme. These nodes do not participate in the consensus of transactions or block validation any differently than other nodes and therefore do not degrade the security model of Bitcoin’s validate first then trust, across every node. Each token transfer settles on-chain. The protocol follows Bitcoin core policies so it has adequate code coverage and protocol hardening to be qualified as production quality software. It shares a significant portion of Bitcoin’s own hashpower through merged-mining.
This platform as a whole can serve token microtransactions, larger settlements, and store-of-value in an ideal fashion, providing probabilistic scalability whilst remaining decentralized according to Bitcoin design. It is accessible to ERC-20 via a permissionless and trust-minimized bridge that works in both directions. The bridge and token platform are currently available on the Syscoin mainnet. This has been gaining recent attention for use by loyalty point programs and stablecoins such as Binance USD.

Solutions

Syscoin Foundation identified a few paths for Reddit to leverage this infrastructure, each with trade-offs. The first provides the most cost-savings and scaling benefits at some sacrifice of token autonomy. The second offers more preservation of autonomy with a more narrow scope of cost savings than the first option, but savings even so. The third introduces more complexity than the previous two yet provides the most overall benefits. We consider the third as most viable as it enables Reddit to benefit even while retaining existing smart contract functionality. We will focus on the third option, and include the first two for good measure.
  1. Distribution, burns and user-to-user transfers of Reddit Points are entirely carried out on the Syscoin network. This full-on approach to utilizing the Syscoin network provides the most scalability and transaction cost benefits of these scenarios. The tradeoff here is distribution and subscription handling likely migrating away from smart contracts into the application layer.
  2. The Reddit Community Points ecosystem can continue to use existing smart contracts as they are used today on the Ethereum mainchain. Users migrate a portion of their tokens to Syscoin, the scaling network, to gain much lower fees, scalability, and a proven base layer, without sacrificing sovereign ownership. They would use Syscoin for user-to-user transfers. Tips redeemable in ten seconds or less, a high-throughput relay network, and onchain settlement at a block target of 60 seconds.
  3. Integration between Matic Network and Syscoin Platform - similar to Syscoin’s current integration with Ethereum - will provide Reddit Community Points with EVM scalability (including the Memberships ERC777 operator) on the Matic side, and performant simple value transfers, robust decentralized security, and sovereign store-of-value on the Syscoin side. It’s “the best of both worlds”. The trade-off is more complex interoperability.

Syscoin + Matic Integration

Matic and Blockchain Foundry Inc, the public company formed by the founders of Syscoin, recently entered a partnership for joint research and business development initiatives. This is ideal for all parties as Matic Network and Syscoin Platform provide complementary utility. Syscoin offers characteristics for sovereign ownership and security based on Bitcoin’s time-tested model, and shares a significant portion of Bitcoin’s own hashpower. Syscoin’s focus is on secure and scalable simple value transfers, trust-minimized interoperability, and opt-in regulatory compliance for tokenized assets rather than scalability for smart contract execution. On the other hand, Matic Network can provide scalable EVM for smart contract execution. Reddit Community Points can benefit from both.
Syscoin + Matic integration is actively being explored by both teams, as it is helpful to Reddit, Ethereum, and the industry as a whole.

Proving Performance & Cost Savings

Our POC focuses on 100,000 on-chain settlements of token transfers on the Syscoin Core blockchain. Transfers and burns perform equally with Syscoin. For POCs related to smart contracts (subscriptions, etc), refer to the Matic Network proposal.
On-chain settlement of 100k transactions was accomplished within roughly twelve minutes, well-exceeding Reddit’s expectation of five days. This was performed using six full-nodes operating on compute-optimized AWS c4.2xlarge instances which were geographically distributed (Virginia, London, Sao Paulo Brazil, Oregon, Singapore, Germany). A higher quantity of settlements could be reached within the same time-frame with more broadcasting nodes involved, or using hosts with more resources for faster execution of the process.
Addresses used: 100,014
The demonstration was executed using this tool. The results can be seen in the following blocks:
612722: https://sys1.bcfn.ca/block/6d47796d043bb4c508d29123e6ae81b051f5e0aaef849f253c8f3a6942a022ce
612723: https://sys1.bcfn.ca/block/8e2077f743461b90f80b4bef502f564933a8e04de97972901f3d65cfadcf1faf
612724: https://sys1.bcfn.ca/block/205436d25b1b499fce44c29567c5c807beaca915b83cc9f3c35b0d76dbb11f6e
612725: https://sys1.bcfn.ca/block/776d1b1a0f90f655a6bbdf559ff5072459cbdc5682d7615ff4b78c00babdc237
612726: https://sys1.bcfn.ca/block/de4df0994253742a1ac8ac9eec8d2a8c8b0a6d72c53d6f3caa29bb6c171b0a6b
612727: https://sys1.bcfn.ca/block/e5e167c52a9decb313fbaadf49a5e34cb490f8084f642a850385476d4ef10d70
612728: https://sys1.bcfn.ca/block/ab64d989edc71890e7b5b8491c20e9a27520dc45a5f7c776d3dae79057f59fe7
612729: https://sys1.bcfn.ca/block/5e8b7ecd0e36f99d07e4ea6e135fc952bf7ec30164ab6f4d1e98b0f2d405df6d
612730: https://sys1.bcfn.ca/block/d395df3d31dde60bbb0bece6bd5b358297da878f0beb96be389e5f0e043580a3
It is important to note that this POC is not focused on Z-DAG. The performance of Z-DAG has been benchmarked within realistic network conditions: Whiteblock’s audit is publicly available. Network latency tests showed an average TPS around 15k with burst capacity up to 61k. Zero-latency control group exhibited ~150k TPS. Mainnet testing of the Z-DAG network is achievable and will require further coordination and additional resources.
Even further optimizations are expected in the upcoming Syscoin Core release which will implement a UTXO model for our token layer bringing further efficiency as well as open the door to additional scaling technology currently under research by our team and academic partners. At present our token layer is account-based, similar to Ethereum. Opt-in compliance structures will also be introduced soon which will offer some positive performance characteristics as well. It makes the most sense to implement these optimizations before performing another benchmark for Z-DAG, especially on the mainnet considering the resources required to stress-test this network.

Cost Savings

Total cost for these 100k transactions: $0.63 USD
See the live fee comparison for savings estimation between transactions on Ethereum and Syscoin. Below is a snapshot at time of writing:
ETH price: $318.55 ETH gas price: 55.00 Gwei ($0.37)
Syscoin price: $0.11
Snapshot of live fee comparison chart
Z-DAG provides a more efficient fee-market. A typical Z-DAG transaction costs 0.0000582 SYS. Tokens can be safely redeemed/re-spent within seconds or allowed to settle on-chain beforehand. The costs should remain about this low for microtransactions.
Syscoin will achieve further reduction of fees and even greater scalability with offchain payment channels for assets, with Z-DAG as a resilience fallback. New payment channel technology is one of the topics under research by the Syscoin development team with our academic partners at TU Delft. In line with the calculation in the Lightning Networks white paper, payment channels using assets with Syscoin Core will bring theoretical capacity for each person on Earth (7.8 billion) to have five on-chain transactions per year, per person, without requiring anyone to enter a fee market (aka “wait for a block”). This exceeds the minimum LN expectation of two transactions per person, per year; one to exist on-chain and one to settle aggregated value.

Tools, Infrastructure & Documentation

Syscoin Bridge

Mainnet Demonstration of Syscoin Bridge with the Basic Attention Token ERC-20
A two-way blockchain interoperability system that uses Simple Payment Verification to enable:
  • Any Standard ERC-20 token to be moved from Ethereum to the Syscoin blockchain as a Syscoin Platform Token (SPT), and back to Ethereum
  • Any SPT to be moved from Syscoin to the Ethereum blockchain as an ERC-20 token, and back to Syscoin

Benefits

  • Permissionless
  • No counterparties involved
  • No trading mechanisms involved
  • No third-party liquidity providers required
  • Cross-chain Fractional Supply - 2-way peg - Token supply maintained globally
  • ERC-20s gain vastly improved transactionality with the Syscoin Token Platform, along with the security of bitcoin-core-compliant PoW.
  • SPTs gain access to all the tooling, applications and capabilities of Ethereum for ERC-20, including smart contracts.
https://preview.redd.it/l8t2m8ldh8e51.png?width=1180&format=png&auto=webp&s=b0a955a0181746dc79aff718bd0bf607d3c3aa23
https://preview.redd.it/26htnxzfh8e51.png?width=1180&format=png&auto=webp&s=d0383d3c2ee836c9f60b57eca35542e9545f741d

Source code

https://github.com/syscoin/?q=sysethereum
Main Subprojects

API

Tools to simplify using Syscoin Bridge as a service with dapps and wallets will be released some time after implementation of Syscoin Core 4.2. These will be based upon the same processes which are automated in the current live Sysethereum Dapp that is functioning with the Syscoin mainnet.

Documentation

Syscoin Bridge & How it Works (description and process flow)
Superblock Validation Battles
HOWTO: Provision the Bridge for your ERC-20
HOWTO: Setup an Agent
Developer & User Diligence

Trade-off

The Syscoin Ethereum Bridge is secured by Agent nodes participating in a decentralized and incentivized model that involves roles of Superblock challengers and submitters. This model is open to participation. The benefits here are trust-minimization, permissionless-ness, and potentially less legal/regulatory red-tape than interop mechanisms that involve liquidity providers and/or trading mechanisms.
The trade-off is that due to the decentralized nature there are cross-chain settlement times of one hour to cross from Ethereum to Syscoin, and three hours to cross from Syscoin to Ethereum. We are exploring ways to reduce this time while maintaining decentralization via zkp. Even so, an “instant bridge” experience could be provided by means of a third-party liquidity mechanism. That option exists but is not required for bridge functionality today. Typically bridges are used with batch value, not with high frequencies of smaller values, and generally it is advantageous to keep some value on both chains for maximum availability of utility. Even so, the cross-chain settlement time is good to mention here.

Cost

Ethereum -> Syscoin: Matic or Ethereum transaction fee for bridge contract interaction, negligible Syscoin transaction fee for minting tokens
Syscoin -> Ethereum: Negligible Syscoin transaction fee for burning tokens, 0.01% transaction fee paid to Bridge Agent in the form of the ERC-20, Matic or Ethereum transaction fee for contract interaction.

Z-DAG

Zero-Confirmation Directed Acyclic Graph is an instant settlement protocol that is used as a complementary system to proof-of-work (PoW) in the confirmation of Syscoin service transactions. In essence, a Z-DAG is simply a directed acyclic graph (DAG) where validating nodes verify the sequential ordering of transactions that are received in their memory pools. Z-DAG is used by the validating nodes across the network to ensure that there is absolute consensus on the ordering of transactions and no balances are overflowed (no double-spends).

Benefits

  • Unique fee-market that is more efficient for microtransaction redemption and settlement
  • Uses decentralized means to enable tokens with value transfer scalability that is comparable or exceeds that of credit card networks
  • Provides high throughput and secure fulfillment even if blocks are full
  • Probabilistic and interactive
  • 99.9999% security assurance within 10 seconds
  • Can serve payment channels as a resilience fallback that is faster and lower-cost than falling-back directly to a blockchain
  • Each Z-DAG transaction also settles onchain through Syscoin Core at 60-second block target using SHA-256 Proof of Work consensus
https://preview.redd.it/pgbx84jih8e51.png?width=1614&format=png&auto=webp&s=5f631d42a33dc698365eb8dd184b6d442def6640

Source code

https://github.com/syscoin/syscoin

API

Syscoin-js provides tooling for all Syscoin Core RPCs including interactivity with Z-DAG.

Documentation

Z-DAG White Paper
Useful read: An in-depth Z-DAG discussion between Syscoin Core developer Jag Sidhu and Brave Software Research Engineer Gonçalo Pestana

Trade-off

Z-DAG enables the ideal speed/security tradeoff to be determined per use-case in the application layer. It minimizes the sacrifice required to accept and redeem fast transfers/payments while providing more-than-ample security for microtransactions. This is supported on the premise that a Reddit user receiving points does need security yet generally doesn’t want nor need to wait for the same level of security as a nation-state settling an international trade debt. In any case, each Z-DAG transaction settles onchain at a block target of 60 seconds.

Syscoin Specs

Syscoin 3.0 White Paper
(4.0 white paper is pending. For improved scalability and less blockchain bloat, some features of v3 no longer exist in current v4: Specifically Marketplace Offers, Aliases, Escrow, Certificates, Pruning, Encrypted Messaging)
  • 16MB block bandwidth per minute assuming segwit witness carrying transactions, and transactions ~200 bytes on average
  • SHA256 merge mined with Bitcoin
  • UTXO asset layer, with base Syscoin layer sharing identical security policies as Bitcoin Core
  • Z-DAG on asset layer, bridge to Ethereum on asset layer
  • On-chain scaling with prospect of enabling enterprise grade reliable trustless payment processing with on/offchain hybrid solution
  • Focus only on Simple Value Transfers. MVP of blockchain consensus footprint is balances and ownership of them. Everything else can reduce data availability in exchange for scale (Ethereum 2.0 model). We leave that to other designs, we focus on transfers.
  • Future integrations of MAST/Taproot to get more complex value transfers without trading off trustlessness or decentralization.
  • Zero-knowledge Proofs are a cryptographic new frontier. We are dabbling here to generalize the concept of bridging and also verify the state of a chain efficiently. We also apply it in our Digital Identity projects at Blockchain Foundry (a publicly traded company which develops Syscoin softwares for clients). We are also looking to integrate privacy preserving payment channels for off-chain payments through zkSNARK hub & spoke design which does not suffer from the HTLC attack vectors evident on LN. Much of the issues plaguing Lightning Network can be resolved using a zkSNARK design whilst also providing the ability to do a multi-asset payment channel system. Currently we found a showstopper attack (American Call Option) on LN if we were to use multiple-assets. This would not exist in a system such as this.

Wallets

Web3 and mobile wallets are under active development by Blockchain Foundry Inc as WebAssembly applications and expected for release not long after mainnet deployment of Syscoin Core 4.2. Both of these will be multi-coin wallets that support Syscoin, SPTs, Ethereum, and ERC-20 tokens. The Web3 wallet will provide functionality similar to Metamask.
Syscoin Platform and tokens are already integrated with Blockbook. Custom hardware wallet support currently exists via ElectrumSys. First-class HW wallet integration through apps such as Ledger Live will exist after 4.2.
Current supported wallets
Syscoin Spark Desktop
Syscoin-Qt

Explorers

Mainnet: https://sys1.bcfn.ca (Blockbook)
Testnet: https://explorer-testnet.blockchainfoundry.co

Thank you for close consideration of our proposal. We look forward to feedback, and to working with the Reddit community to implement an ideal solution using Syscoin Platform!

submitted by sidhujag to ethereum [link] [comments]

A new whitepaper analysing the performance and scalability of the Streamr pub/sub messaging Network is now available. Take a look at some of the fascinating key results in this introductory blog

A new whitepaper analysing the performance and scalability of the Streamr pub/sub messaging Network is now available. Take a look at some of the fascinating key results in this introductory blog

Streamr Network: Performance and Scalability Whitepaper


https://preview.redd.it/bstqyn43x4j51.png?width=2600&format=png&auto=webp&s=81683ca6303ab84ab898c096345464111d674ee5
The Corea milestone of the Streamr Network went live in late 2019. Since then a few people in the team have been working on an academic whitepaper to describe its design principles, position it with respect to prior art, and prove certain properties it has. The paper is now ready, and it has been submitted to the IEEE Access journal for peer review. It is also now published on the new Papers section on the project website. In this blog, I’ll introduce the paper and explain its key results. All the figures presented in this post are from the paper.
The reasons for doing this research and writing this paper were simple: many prospective users of the Network, especially more serious ones such as enterprises, ask questions like ‘how does it scale?’, ‘why does it scale?’, ‘what is the latency in the network?’, and ‘how much bandwidth is consumed?’. While some answers could be provided before, the Network in its currently deployed form is still small-scale and can’t really show a track record of scalability for example, so there was clearly a need to produce some in-depth material about the structure of the Network and its performance at large, global scale. The paper answers these questions.
Another reason is that decentralized peer-to-peer networks have experienced a new renaissance due to the rise in blockchain networks. Peer-to-peer pub/sub networks were a hot research topic in the early 2000s, but not many real-world implementations were ever created. Today, most blockchain networks use methods from that era under the hood to disseminate block headers, transactions, and other events important for them to function. Other megatrends like IoT and social media are also creating demand for new kinds of scalable message transport layers.

The latency vs. bandwidth tradeoff

The current Streamr Network uses regular random graphs as stream topologies. ‘Regular’ here means that nodes connect to a fixed number of other nodes that publish or subscribe to the same stream, and ‘random’ means that those nodes are selected randomly.
Random connections can of course mean that absurd routes get formed occasionally, for example a data point might travel from Germany to France via the US. But random graphs have been studied extensively in the academic literature, and their properties are not nearly as bad as the above example sounds — such graphs are actually quite good! Data always takes multiple routes in the network, and only the fastest route counts. The less-than-optimal routes are there for redundancy, and redundancy is good, because it improves security and churn tolerance.
There is an important parameter called node degree, which is the fixed number of nodes to which each node in a topology connects. A higher node degree means more duplication and thus more bandwidth consumption for each node, but it also means that fast routes are more likely to form. It’s a tradeoff; better latency can be traded for worse bandwidth consumption. In the following section, we’ll go deeper into analyzing this relationship.

Network diameter scales logarithmically

One useful metric to estimate the behavior of latency is the network diameter, which is the number of hops on the shortest path between the most distant pair of nodes in the network (i.e. the “longest shortest path”. The below plot shows how the network diameter behaves depending on node degree and number of nodes.

Network diameter
We can see that the network diameter increases logarithmically (very slowly), and a higher node degree ‘flattens the curve’. This is a property of random regular graphs, and this is very good — growing from 10,000 nodes to 100,000 nodes only increases the diameter by a few hops! To analyse the effect of the node degree further, we can plot the maximum network diameter using various node degrees:
Network diameter in network of 100 000 nodes
We can see that there are diminishing returns for increasing the node degree. On the other hand, the penalty (number of duplicates, i.e. bandwidth consumption), increases linearly with node degree:

Number of duplicates received by the non-publisher nodes
In the Streamr Network, each stream forms its own separate overlay network and can even have a custom node degree. This allows the owner of the stream to configure their preferred latency/bandwidth balance (imagine such a slider control in the Streamr Core UI). However, finding a good default value is important. From this analysis, we can conclude that:
  • The logarithmic behavior of network diameter leads us to hope that latency might behave logarithmically too, but since the number of hops is not the same as latency (in milliseconds), the scalability needs to be confirmed in the real world (see next section).
  • A node degree of 4 yields good latency/bandwidth balance, and we have selected this as the default value in the Streamr Network. This value is also used in all the real-world experiments described in the next section.
It’s worth noting that in such a network, the bandwidth requirement for publishers is determined by the node degree and not the number of subscribers. With a node degree 4 and a million subscribers, the publisher only uploads 4 copies of a data point, and the million subscribing nodes share the work of distributing the message among themselves. In contrast, a centralized data broker would need to push out a million copies.

Latency scales logarithmically

To see if actual latency scales logarithmically in real-world conditions, we ran large numbers of nodes in 16 different Amazon AWS data centers around the world. We ran experiments with network sizes between 32 to 2048 nodes. Each node published messages to the network, and we measured how long it took for the other nodes to get the message. The experiment was repeated 10 times for each network size.
The below image displays one of the key results of the paper. It shows a CDF (cumulative distribution function) of the measured latencies across all experiments. The y-axis runs from 0 to 1, i.e. 0% to 100%.
CDF of message propagation delay
From this graph we can easily read things like: in a 32 nodes network (blue line), 50% of message deliveries happened within 150 ms globally, and all messages were delivered in around 250 ms. In the largest network of 2048 nodes (pink line), 99% of deliveries happened within 362 ms globally.
To put these results in context, PubNub, a centralized message brokering service, promises to deliver messages within 250 ms — and that’s a centralized service! Decentralization comes with unquestionable benefits (no vendor lock-in, no trust required, network effects, etc.), but if such protocols are inferior in terms of performance or cost, they won’t get adopted. It’s pretty safe to say that the Streamr Network is on par with centralized services even when it comes to latency, which is usually the Achilles’ heel of P2P networks (think of how slow blockchains are!). And the Network will only get better with time.
Then we tackled the big question: does the latency behave logarithmically?
Mean message propagation delay in Amazon experiments
Above, the thick line is the average latency for each network size. From the graph, we can see that the latency grows logarithmically as the network size increases, which means excellent scalability.
The shaded area shows the difference between the best and worst average latencies in each repeat. Here we can see the element of chance at play; due to the randomness in which nodes become neighbours, some topologies are faster than others. Given enough repeats, some near-optimal topologies can be found. The difference between average topologies and the best topologies gives us a glimpse of how much room for optimisation there is, i.e. with a smarter-than-random topology construction, how much improvement is possible (while still staying in the realm of regular graphs)? Out of the observed topologies, the difference between the average and the best observed topology is between 5–13%, so not that much. Other subclasses of graphs, such as irregular graphs, trees, and so on, can of course unlock more room for improvement, but they are different beasts and come with their own disadvantages too.
It’s also worth asking: how much worse is the measured latency compared to the fastest possible latency, i.e. that of a direct connection? While having direct connections between a publisher and subscribers is definitely not scalable, secure, or often even feasible due to firewalls, NATs and such, it’s still worth asking what the latency penalty of peer-to-peer is.

Relative delay penalty in Amazon experiments
As you can see, this plot has the same shape as the previous one, but the y-axis is different. Here, we are showing the relative delay penalty (RDP). It’s the latency in the peer-to-peer network (shown in the previous plot), divided by the latency of a direct connection measured with the ping tool. So a direct connection equals an RDP value of 1, and the measured RDP in the peer-to-peer network is roughly between 2 and 3 in the observed topologies. It increases logarithmically with network size, just like absolute latency.
Again, given that latency is the Achilles’ heel of decentralized systems, that’s not bad at all. It shows that such a network delivers acceptable performance for the vast majority of use cases, only excluding the most latency-sensitive ones, such as online gaming or arbitrage trading. For most other use cases, it doesn’t matter whether it takes 25 or 75 milliseconds to deliver a data point.

Latency is predictable

It’s useful for a messaging system to have consistent and predictable latency. Imagine for example a smart traffic system, where cars can alert each other about dangers on the road. It would be pretty bad if, even minutes after publishing it, some cars still haven’t received the warning. However, such delays easily occur in peer-to-peer networks. Everyone in the crypto space has seen first-hand how plenty of Bitcoin or Ethereum nodes lag even minutes behind the latest chain state.
So we wanted to see whether it would be possible to estimate the latencies in the peer-to-peer network if the topology and the latencies between connected pairs of nodes are known. We applied Dijkstra’s algorithm to compute estimates for average latencies from the input topology data, and compared the estimates to the actual measured average latencies:
Mean message propagation delay in Amazon experiments
We can see that, at least in these experiments, the estimates seemed to provide a lower bound for the actual values, and the average estimation error was 3.5%. The measured value is higher than the estimated one because the estimation only considers network delays, while in reality there is also a little bit of a processing delay at each node.

Conclusion

The research has shown that the Streamr Network can be expected to deliver messages in roughly 150–350 milliseconds worldwide, even at a large scale with thousands of nodes subscribing to a stream. This is on par with centralized message brokers today, showing that the decentralized and peer-to-peer approach is a viable alternative for all but the most latency-sensitive applications.
It’s thrilling to think that by accepting a latency only 2–3 times longer than the latency of an unscalable and insecure direct connecion, applications can interconnect over an open fabric with global scalability, no single point of failure, no vendor lock-in, and no need to trust anyone — all that becomes available out of the box.
In the real-time data space, there are plenty of other aspects to explore, which we didn’t cover in this paper. For example, we did not measure throughput characteristics of network topologies. Different streams are independent, so clearly there’s scalability in the number of streams, and heavy streams can be partitioned, allowing each stream to scale too. Throughput is mainly limited, therefore, by the hardware and network connection used by the network nodes involved in a topology. Measuring the maximum throughput would basically be measuring the hardware as well as the performance of our implemented code. While interesting, this is not a high priority research target at this point in time. And thanks to the redundancy in the network, individual slow nodes do not slow down the whole topology; the data will arrive via faster nodes instead.
Also out of scope for this paper is analysing the costs of running such a network, including the OPEX for publishers and node operators. This is a topic of ongoing research, which we’re currently doing as part of designing the token incentive mechanisms of the Streamr Network, due to be implemented in a later milestone.
I hope that this blog has provided some insight into the fascinating results the team uncovered during this research. For a more in-depth look at the context of this work, and more detail about the research, we invite you to read the full paper.
If you have an interest in network performance and scalability from a developer or enterprise perspective, we will be hosting a talk about this research in the coming weeks, so keep an eye out for more details on the Streamr social media channels. In the meantime, feedback and comments are welcome. Please add a comment to this Reddit thread or email [[email protected]](mailto:[email protected]).
Originally published by. Henri at blog.streamr.network on August 24, 2020.
submitted by thamilton5 to streamr [link] [comments]

Warning: Blockchain difficulty adjustment affecting price movements

Below are notable difficulty adjustments when hash rate fell and block times become slower for Bitcoin.
  1. 26 Mar 2020 [difficulty adjustment -15.95%, avg block time 11min 54secs]. On the 28th price crashed from $6674 to $6138 ( -8%).
  2. 8 Nov 2019 [difficulty adjustment -7.1%, avg block time 10min 46secs]. On the same day price crashed from $9234 to $8783 ( -4.88%).
  3. The next big adjustment was around Nov to Dec 2018 and there were 3 big adjustments with high block times.

Current situation:
We are 1 day 10 hours from the next difficulty adjustment. Projected difficulty adjustment is -5.61% (https://fork.lol/pow/retarget), which could indicate a small dip. However, take note that the date of last adjustment was the 5th and the 3rd halving was on the 11th, between the 5th to the 11th there was increased hashrate from miners trying to mine the final week of 12.5btc that offset the really slow block times after the halving. Therefore it will be the next difficulty adjustment after the one on the 20th that will completely reflect the slower block times after the halving. Currently the median block time taken on the 17th was around 14min (-28.5% difficulty adjustment).
For people who do not understand blockchain, basically with the Bitcoin 3rd halving, mining profitability fell for a lot of miners and they probably turned off their miners therefore the blockchain mining time became considerably slower which is reflected with slow transaction speed and higher fees as seen currently. Bitcoin sellers moving their BTC from wallet to an exchange are faced with slow transaction speed and therefore the sell pressure of BTC fell considerably which will attribute to the current price increase. There is a correlation between sell pressure and blockchain congestion (the size of the correlation is undetermined).
There is going to be a race. A race between BTC price hiking high enough to attract more miners to reduce avg block times versus the closing window of roughly 2 weeks before the next difficulty adjustment. If the price does not jump high enough, the next difficulty adjustment in the first week of June could signal a huge dip.
I am not an expert. I just did some research on the above and wanted to share with fellow Bitcoin compatriots so that we can tread with caution and not lose our shirts. I do not plan to short BTC but I will exit my BTC positions if I expect double digit negative difficulty adjustment in early June.
Please visit the original post here https://www.reddit.com/Bitcoin/comments/gm23pe/warning_blockchain_difficulty_adjustment/
There are pictures in the original post as well as 2nd halving evidence with pics. I could not post pics here. If possible please upvote the original post, a lot of people downvote it. Not sure why people downvote it, maybe veterans attempting to hide information from newcomers to fleece them of their shirt.

Update 1:>! As of writing, I have opened a small short position on Bitcoin. Stop loss around 10k, estimated take profit around 8500. The reason is because the difficulty adjustment in the next 20 hours, even though is just -5% roughly is still significant. I direct you to look into all the difficulty adjustments in the last 2 years and you will know how rare it is. The ones I caught were all listed at the very top of the post. Since it is my first time shorting BTC, I take this as a learning opportunity so that I will have some experience to face the bigger difficulty adjustment in the first week of June. Analysis into execution, even in failure I am happy.!<
Update 2: The difficulty adjustment (DA) happened roughly 6 hours ago and the sell pressure from -6% DA did not seem to be affecting the market much. However, please take a look now at the estimation for the next DA.
On https://bitcoin.clarkmoody.com/dashboard/ it is estimated to be -25%.
On https://fork.lol/pow/retarget estimated to be -18%.
On https://www.blockchain.com/charts/median-confirmation-time the median block time for the last day was 16.8min.
My original proposition that the true DA of the halving can only be realized in the next DA stands and that it will be considerable. The increased sell pressure from that DA will be highly significant. That is why there is a race by current miners to get the BTC price up high enough to attract more miners to not have the DA drop too much.
Update 3: Current BTC price at $9100 ( ~39 hours after DA). Then again BTC could have dropped from all sorts of reason. However the coincidence with the DA and with all the past DA is just too high to simply shrug off as irrelevant. Anyways past result cannot predict future ones, stay safe with the trading. Will no longer check on this post.
References:
Difficulty adjustment dates taken from https://btc.com/stats/diff
Bitcoin graph history for price movement taken from coinmarketcap.
Median confirmation time (block time) taken from https://www.blockchain.com/charts/median-confirmation-time

Credits to people who assisted the analysis:
kairepaire for pointing out faster block times between 5th-11th.
babies_eater for https://fork.lol/pow/retarget
moes_tavern_wifi for https://bitcoin.clarkmoody.com/dashboard/
Pantamis for https://diff.cryptothis.com/
submitted by theforwardbrain to BitcoinMarkets [link] [comments]

When should you take out a crypto loan? QDAO DeFi Use Cases.

When should you take out a crypto loan? QDAO DeFi Use Cases.
Getting a bank loan can sometimes seem like an impossible task. There is a credit history to check, collateral to provide, and other complex little details. Now, in times of the global financial crisis, banks will likely be even more cautious about giving out money.
This is why DeFi-based crypto loans are booming. The sector is still relatively new – it emerged around two and a half years ago. And since then, it has experienced rapid growth. Take a look at this graph demonstrating the cumulative lending to institutions by Genesis Lending Originations – one of the major OTC-platforms.

https://preview.redd.it/zhyovy91dam51.png?width=1280&format=png&auto=webp&s=5721511496640c7e268ca2f0943fb8bb269614c2
By the end of the first quarter of 2020, the company gave out loans worth $1 billion. And that’s just Genesis Lending. Compound, the current leader among DeFi platforms currently has over $883 million in outstanding debt.
QDAO DeFi is launching a crypto loan feature as well. Users can deposit their crypto, borrow fiat and take their crypto assets back after paying the small interest rate – simple as that. The service is available to everyone with internet access and provides outstanding benefits to users.
We will demonstrate use cases for three different types of borrowers: private persons, traders and institutional investors. Most likely you’ll recognize at least one of these situations.
Disclaimer: the interest rates stated below serve only as examples and are subject to change. Always check the current rates on the QDAO DeFi Loans page.
Example 1. The borrower is a private person
This is the most basic use case in which the DeFi platform functions similar to a pawnshop.
Let’s assume that a person has already bought or is planning to buy 1 Bitcoin and is committed to holding on to it. The new rally is coming soon and this person is getting ready to cash out. However, due to some circumstances, they need fiat money now, preferably as fast as possible.
This person could sell Bitcoin. But if they don’t buy it back soon, they might lose the opportunity for profit.
Now, there is no need to choose between taking care of urgent issues and keeping the asset. Anyone can simply use crypto as collateral.
Let’s say that at the moment, Bitcoin costs $9,000. If the borrower puts it in QDAO DeFi, they can get up to 50% of crptocurrency’s value in fiat, i.e. $4,500. There is no credit check or extensive paperwork involved and all transactions are practically instant.
The borrower uses the cash however they see fit. Meanwhile, their collateral remains untouched in Custody Storage. The monthly interest is, for example, 2%. So if this person wants to get his Bitcoin back in three months, they will only need to pay $4,770. By this time, the price of their Bitcoin might have gone well above $10,000, so the deal is quite lucrative.
Example 2. The borrower is a crypto-trader
Let’s look at a serious crypto-trader who has 10 Bitcoins. The market is leaving the consolidation phase and is preparing for a rally.
They are serious about committing to a ‘HODL’ strategy and want to keep their Bitcoins. At the same time, this trader continues to make deals on exchanges to enhance future profits. After studying Ripple, they decide that it would make a nice addition to their portfolio and want to buy it. But this trader doesn’t have disposable funds to acquire enough XRP.
Since the Bitcoins are just sitting in a wallet, these assets can be used to acquire fiat resources. If the trader deposits all their Bitcoins (worth $90,000), they will get a significant boost of up to $45,000. And the best part is that the loan is in USDT, so it’s possible to just swap Tether for Ripple without extra transactions.
Let’s assume that the trader sells XRP in four months. They use part of the profit to cover the assumed interest of 2% ($3,600) then take the rest for themself and retrieve their Bitcoins.
Example 3. The borrower is an Institutional investor
There is a crypto fund or an asset management company with high net worth, long-term clients. This agency has a sizable portfolio that includes major stocks like Amazon and Apple as well as crypto assets like Bitcoin, Ripple and Ethereum.
10,000 Bitcoins are under the management of this company – so the combined asset worth is $90,000,000. According to the latest market analysis, BTC will stand at about $20,000 in 2021 and by 2025, it will stand at about $100,000. So obviously the agency should hold on to Bitcoin and the clients agree.
However, there is a very big IPO coming soon. The company has a unique opportunity to buy very promising stock. In several years, this investment will result in a very profitable exit.
But the current budget limits the volume of the possible investment. The agency is going to get more funds in two months, but the opportunity will be gone by then.
Since the company is going to be holding Bitcoin for some time anyway, it decides to use it as collateral. By depositing the assets in QDAO DeFi, it will receive a loan of up to $45,000,000. Investors use the money to buy shares. In two months, the company pays out the assumed interest ($1,800,000) and reclaims the Bitcoin.
The clients and the management are happy, because now the agency has even more great assets in the portfolio.
Example 4. The borrower does not repay the loan
Someone follows the usual process – puts 3 Bitcoins into QDAO DeFi and takes the $13,500 fiat loan.
For whatever reason, this person does not repay the debt for 7 months while the interest keeps growing. There is a sudden volatility spike and the Bitcoin price goes down to $5000 for a time, hitting the margin call mark. This is less than the original loan, so the borrower has no reason to repay it and cover the interest, since that would mean a complete loss for them. There is also no reason for QDAO DeFi to store this person’s Bitcoin.
The borrower is notified that the assets are now the property of QDAO DeFi and the loan is closed. No further legal action is taken and no penalties have been incurred for defaulting on the loan.
Conclusion
The ability to choose almost all the terms of a cash loan with QDAO DeFi provides unlimited opportunities to get money for any purpose. By planning ahead, all borrowers can get additional fiat assets to multiply their profits while still retaining everything they had before taking out the loan.
Want to be the first to hear QDAO DeFi news and updates? Visit our website and stay in touch with us on social media: Twitter, Facebook, Telegram and LINE (for the Japanese-speaking community).
submitted by QDAODeFi to u/QDAODeFi [link] [comments]

BCH faster than BTC

Sorry to be shrewd, but what makes BCH faster than BTC? Is it simply the fact that BCH has bigger blocks, so the mempool doesn't get clogged up so much?
Or am I missing something else?
Thanks.
submitted by SpuddyA7X to btc [link] [comments]

Is bitcoin really un-tethered? this paper looks at the btc / tether connection; it examines if tether is not back by dollars and is printed to pump prices mainly btc

here is the paper, its quite long but a good read. below ive added some quotes. If you read this paper it will likely just confirm want most who have been in this space for a while think about tether, its centralised with no accountability and is likely not backed 1:1 and is likely an instrument to pump / manipulate prices most noteably bitcoin.
Is Bitcoin Really un-tethered?
some snippets from the paper:
flow of tether between exchanges, the main players:
Figure 1 plots the aggregate flow of Tether among major market participants on the Tether blockchain from its conception in October 6, 2014 until March 31, 2018. The size of the nodes is proportional to the sum of coin inflow and outflow to each node, the thickness of the lines is proportional to the size of flows, and all flow movements are clockwise. Tether is authorized, moved to Bitfinex, and then slowly distributed to other Tether-based exchanges, mainly Poloniex and Bittrex. The graph shows that almost no Tether returns to the Tether issuer to be redeemed, and the major exchange where Tether can be exchanged for USD, Kraken, accounts for only a small proportion of transactions. Tether also flows out to other exchanges and entities and becomes more widespread over time as a medium of exchange.
A similar analysis of the flow of coins on the much larger Bitcoin blockchain shows that the three main Tether exchanges for most of 2017 (Bitfinex, Poloniex, and Bittrex) also facilitate considerable cross-exchange Bitcoin flows among themselves.6 Additionally, we find that the cross-exchange Bitcoin flows on Bitcoin blockchain closely matches the Tether flows on Tether blockchain.
a large player is likely responsiblle for a lot of this:
we find that one large player is associated with more than half of the exchange of Tether for Bitcoin at Bitfinex, suggesting that the distribution of Tether into the market is from a large player and not many different investors bringing cash to Bitfinex to purchase Tether
people who worked on the inside even admit tether isnt backed 1:1
in response to legal motions, on April 30, 2019, Bitfinex’s former General Counsel admitted that Tether does not have cash reserves equal to 100% of the outstanding Tethers. In a May 15, 2019 court hearing, a Bitfinex attorney also admitted that Tether did invest in instruments beyond cash, including Bitcoin, something clearly at odds with Tether’s longstanding claims.
submitted by Neophyte- to CryptoTechnology [link] [comments]

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submitted by jaylenholt to ebookleaksdownload [link] [comments]

Warning: Blockchain difficulty adjustment affecting price movement

Warning: Blockchain difficulty adjustment affecting price movement
Below are notable difficulty adjustments when hash rate fell and block times become slower for Bitcoin.
  1. 26 Mar 2020 [difficulty adjustment -15.95%, avg block time 11min 54secs]. On the 28th price crashed from $6674 to $6138 ( -8%).
  2. 8 Nov 2019 [difficulty adjustment -7.1%, avg block time 10min 46secs]. On the same day price crashed from $9234 to $8783 ( -4.88%).
  3. The next big adjustment was around Nov to Dec 2018 and there were 3 big adjustments with high block times.
  • 19 Dec 2018 [-9.56%, avg block time 11min 3secs]
  • 3 Dec 2018 [-15.13%, avg block time 11min 47secs]
  • 17 Nov 2018 [-7.39%, avg block time 10min 48secs]
  • There was huge drop off starting on 14th Nov all the way to a bottom on 14-15th Dec ($6351 to $3288 around -48%).

Current situation:
We are 1 day 10 hours from the next difficulty adjustment. Projected difficulty adjustment is -5.61% (https://fork.lol/pow/retarget), which could indicate a small dip. However, take note that the date of last adjustment was the 5th and the 3rd halving was on the 11th, between the 5th to the 11th there was increased hashrate from miners trying to mine the final week of 12.5btc that offset the really slow block times after the halving. Therefore it will be the next difficulty adjustment after the one on the 20th that will completely reflect the slower block times after the halving. Currently the median block time taken on the 17th was around 14min (-28.5% difficulty adjustment).

https://preview.redd.it/ysnv85wh0lz41.jpg?width=597&format=pjpg&auto=webp&s=e130b077f9dc2fc9d02666ef89e6f9249a05f535
For people who do not understand blockchain, basically with the Bitcoin 3rd halving, mining profitability fell for a lot of miners and they probably turned off their miners therefore the blockchain mining time became considerably slower which is reflected with slow transaction speed and higher fees as seen currently. Bitcoin sellers moving their BTC from wallet to an exchange are faced with slow transaction speed and therefore the sell pressure of BTC fell considerably which will attribute to the current price increase. There is a correlation between sell pressure and blockchain congestion (the size of the correlation is undetermined).
There is going to be a race. A race between BTC price hiking high enough to attract more miners to reduce avg block times versus the closing window of roughly 2 weeks before the next difficulty adjustment. If the price does not jump high enough, the next difficulty adjustment in the first week of June could signal a huge dip.
I am not an expert. I just did some research on the above and wanted to share with fellow Bitcoin compatriots so that we can tread with caution and not lose our shirts. I do not plan to short BTC but I will exit my BTC positions if I expect double digit negative difficulty adjustment in early June.

Bitcoin 2nd halving evidence:

2nd halving falls between the 5th and the 19th adjustment so it is only reflected on the 3rd of Aug difficulty adjustment ( -5.43%).

See the dip on the 3rd of August. Price fell from $600 to $533 about 11% drop.
Update 1:>! As of writing, I have opened a small short position on Bitcoin. Stop loss around 10k, estimated take profit around 8500. The reason is because the difficulty adjustment in the next 20 hours, even though is just -5% roughly is still significant. I direct you to look into all the difficulty adjustments in the last 2 years and you will know how rare it is. The ones I caught were all listed at the very top of the post. Since it is my first time shorting BTC, I take this as a learning opportunity so that I will have some experience to face the bigger difficulty adjustment in the first week of June. Analysis into execution, even in failure I am happy.!<
Update 2: The difficulty adjustment (DA) happened roughly 6 hours ago and the sell pressure from -6% DA did not seem to be affecting the market much. However, please take a look now at the estimation for the next DA.
On https://bitcoin.clarkmoody.com/dashboard/ it is estimated to be -25%.
On https://fork.lol/pow/retarget estimated to be -18%.
On https://www.blockchain.com/charts/median-confirmation-time the median block time for the last day was 16.8min.
My original proposition that the true DA of the halving can only be realized in the next DA stands and that it will be considerable. The increased sell pressure from that DA will be highly significant. That is why there is a race by current miners to get the BTC price up high enough to attract more miners to not have the DA drop too much.
References:
Difficulty adjustment dates taken from https://btc.com/stats/diff
Bitcoin graph history for price movement taken from coinmarketcap.
Median confirmation time (block time) taken from https://www.blockchain.com/charts/median-confirmation-time

Credits to people who assisted the analysis:
kairepaire for pointing out faster block times between 5th-11th.
babies_eater for https://fork.lol/pow/retarget
moes_tavern_wifi for https://bitcoin.clarkmoody.com/dashboard/
Pantamis for https://diff.cryptothis.com/
submitted by theforwardbrain to Bitcoin [link] [comments]

New 15 page whitepaper by Hush team about Zcash vulnerabilities

The developers of Hush coin have published a 15 page whitepaper on privacy vulnerabilities of the Zcash protocol
Abstract: This paper will outline, for the fi€rst time, exactly how the ITM Attack (a linkability attack against shielded transactions) works against Zcash Protocol and how Hush is the €first cryptocoin with a defensive mitigation against it, called ”Sietch”. Sietch is already running live in production and undergoing rounds of improvement from expert feedback. This is not an academic paper about pipedreams. It describes production code and networks. We begin with a literature review of all known metadata attack methods that can be used against Zcash Protocol blockchains. This includes their estimated attack costs and threat model. This paper then describes the ”ITM Attack” which is a specifi€c instance of a new class of metadata attacks against blockchains which the author describes as Metaverse Metadata Attacks. The paper then explains Sietch in detail, which was a response to these new attacks. We hope this new knowledge and theory helps cryptocoins increase their defenses against very well-funded adversaries including nation states and chain analysis companies. A few other new privacy issues and metadata attacks against Zcash Protocol coins will also be enumerated for the fi€rst time publicly. The ideas in this paper apply to all cryptocoins which utilize transaction graphs, which is to say just about all known coins. Speci€fically, the Metaverse Metadata class of attacks is applicable to all Bitcoin source code forks (including Dash, Verge, Zerocoin and their forks), CryptoNote Protocol coins (Monero and friends) and MimbleWimbleProtocol (Grin, Beam, etc) coins but these will not be addressed here other than a high-level description of how to apply these methods to those chains
It's available on the attackingzcash.com website
submitted by KomodoWorld to CryptoTechnology [link] [comments]

Is bitcoin really un-tethered? this paper looks at the btc / tether connection; it examines if tether is not back by dollars and is printed to pump prices mainly btc

here is the paper, its quite long but a good read. below ive added some quotes. If you read this paper it will likely just confirm want most who have been in this space for a while think about tether, its centralised with no accountability and is likely not backed 1:1 and is likely an instrument to pump prices.
Is Bitcoin Really un-tethered?
some snippets from the paper:
flow of tether between exchanges, the main players:
Figure 1 plots the aggregate flow of Tether among major market participants on the Tether blockchain from its conception in October 6, 2014 until March 31, 2018. The size of the nodes is proportional to the sum of coin inflow and outflow to each node, the thickness of the lines is proportional to the size of flows, and all flow movements are clockwise. Tether is authorized, moved to Bitfinex, and then slowly distributed to other Tether-based exchanges, mainly Poloniex and Bittrex. The graph shows that almost no Tether returns to the Tether issuer to be redeemed, and the major exchange where Tether can be exchanged for USD, Kraken, accounts for only a small proportion of transactions. Tether also flows out to other exchanges and entities and becomes more widespread over time as a medium of exchange.
A similar analysis of the flow of coins on the much larger Bitcoin blockchain shows that the three main Tether exchanges for most of 2017 (Bitfinex, Poloniex, and Bittrex) also facilitate considerable cross-exchange Bitcoin flows among themselves.6 Additionally, we find that the cross-exchange Bitcoin flows on Bitcoin blockchain closely matches the Tether flows on Tether blockchain.
a large player is likely responsiblle for a lot of this:
we find that one large player is associated with more than half of the exchange of Tether for Bitcoin at Bitfinex, suggesting that the distribution of Tether into the market is from a large player and not many different investors bringing cash to Bitfinex to purchase Tether
people who worked on the inside even admit tether isnt backed 1:1
in response to legal motions, on April 30, 2019, Bitfinex’s former General Counsel admitted that Tether does not have cash reserves equal to 100% of the outstanding Tethers. In a May 15, 2019 court hearing, a Bitfinex attorney also admitted that Tether did invest in instruments beyond cash, including Bitcoin, something clearly at odds with Tether’s longstanding claims.
submitted by Neophyte- to btc [link] [comments]

YIKES!! BITCOIN CRASH & DUMPING CONFIRMED?!! Crypto Analysis TA & BTC Cryptocurrency Price News Now Bitcoin transaction demo - YouTube Bitcoin Halving 2020 Price Prediction (Analysis + Explained) IS BITCOIN TOPPED OUT!?! BTC trading charts analysis price prediction news crypto currency EASY Way To Read Bitcoin Charts - BTC Technical Analysis ...

Figure 1: On the left: Annotated Transaction Graph. On the right: Silk Road owner Dread Pirate Roberts unintentionally reveals his public key in an online forum bitcointalk.org - "Bitcoin Transaction Graph Analysis" Bitcoin Fog in particular, as shown by our analysis of withdrawals. Graph Analysis. We found lists of transactions in Bitcoin Fog by tracing our withdrawal transaction to a high-value “slush fund,” from which many withdrawals are directly made, until its value reaches 0 and it is re-funded from deposits (usually ~3 months old) Bitcoin Transaction Graph Analysis Michael Fleder [email protected] Michael S. Kester [email protected] Sudeep Pillai [email protected] January 3, 2014 1 Introduction Bitcoins have recently become an increasingly popular cryptocurrency through which users trade electroni-cally and more anonymously than via traditional electronic transfers. Bitcoin’s design keeps all transactions in a ... Another analysis of the Bitcoin transaction graph was presented at the Chaos Computer Club Conference in Germany in December 2011 [6]. Again, they were primarily interested in how to defeat the anonymity of the network (based on the same idea of collapsing addresses belonging to a common owner), but also included some interesting comments about the economic principles behind the scheme, the e ... Bitcoin Transaction Graph Analysis. February 2015; Source; arXiv; Authors: Michael Fleder. Michael S. Kester . Sudeep Pillai. Massachusetts Institute of Technology; Download full-text PDF Read ...

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YIKES!! BITCOIN CRASH & DUMPING CONFIRMED?!! Crypto Analysis TA & BTC Cryptocurrency Price News Now

Bitcoin halving 2020 price prediction analysis + bitcoin halving explained on btc charts technicals. Follow Me On Twitter: https://twitter.com/TheRightTrade... Bitcoin transaction demo Visit our website: https://altcoinbuzz.io Bitcoin tried to make a small rally today. Does that change the price prediction in the short term? How do you even... HAS BITCOIN TOPPED MAKING A MACRO LOWER HIGH? Is there too much BULLISH sentiment? Or have the BEARS lost this one, lets talk about it and let me know your thoughts in the comments below. Don't ... BITCOIN 💥Altcoin Market CRASH -75% in 2020? 💥 ️LIVE Crypto Analysis TA & Cryptocurrency Price News - Duration: 36:09. Crypto Kirby Trading 16,538 views 36:09

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