RoboSats is an easy way to privately exchange Bitcoin for national currencies using Tor browser. It simplifies the peer-to-peer experience and uses lightning hold invoices to minimize custody and trust requirements. Bitcoin Tips:
To start using RoboSats you only need a Lightning Wallet and a TOR enabled browser.
Ready? Let's Go
The process is pretty straightforward, but I will still suggest to start with a very small amount you can afford to lose.
This document has two complete walkthroughs:
1) as a buyer that takes an order and;
2) as a seller that makes an order
RoboSats help users preserve their privacy by using newly generated avatars in every trade. Avatars are super easy and very cool to generate!
The robot is deterministically generated based on the token you see below it. This token is all you need to recover the avatar in the future, so make sure to back it up safely! It is best to write it down in paper… but that’s a lot of work!! Most often it is good enough to simply copy it to clipboard and save it somewhere else. If your browser crashes, your phone battery dies, or you lose connection during trading, you will need the token to log in again and continue with the trade!
Recovering a robotPermalink To recover a backed-up token, simply replace the token in the textbox and tap “Generate Robot”. The site will greet you with “We found your Robot avatar. Welcome back!”
TradePermalink In RoboSats you can make new orders or take orders made by others. To be an order maker simply click on “Create Order” in the homepage. To take an order, click on “View Book” so you can explore the orders created by other robots.
Exploring the Order BookPermalink We click on “View book” and have a look at the orders in the book page.
On a desktop browser, you can see at a glance all of the relevant information about the orders so you can decide which one to take. By default, the book will show “ANY” type of order (buy and sell) and “ANY” currency. Use the drop down menus at the top to select your preferences.
On a smartphone, however, not all of the columns fit on the screen. The nicknames, the type of order, the payment method and the exchange rate are hidden by default. You can tap on any column and tap “Show columns” to select what columns to make visible.
Every order has an expiration counter. By default, in RoboSats v0.1.0 new orders will stay public in the book for 24 hours.
Walkthrough-1: Taking an order as a buyerPermalink When you are decided for an order to take simply tap the “Take Order” button. You will see the contract box. Follow the contract box indications until you complete the trade! :)
First thing is to lock a small fidelity bond (just 3% of the trade amount by default), so the seller knows you can be trusted. The satoshis in this bond will just freeze in your wallet. If you try to cheat or cancel unilaterally, you will lose the satoshis locked in the bond.
Scan or copy the invoice into your lightning wallet. It might show as a payment that is on transit, freeze or even seemingly break your wallet. You should always check on the RoboSats website whether the bond has been locked (your wallet will probably not tell you! Check wallet compatibility list)
As soon as our bond is locked, RoboSats will ask you to provide a lightning invoice to send you the satoshis. Generate an invoice with the exact amount in your lightning wallet and submit it.
While you are submitting your payout invoice, the seller is asked to lock the trade escrow hold invoice. If you are faster than him, you would have to wait. Otherwise, you would already be able to chat with him.
There is a time limit of 3 hours to submit the invoice (buyer) and lock the trade escrow (seller). If the time runs out, the order will expire and the robot who did not follow with the contract obligations will lose the bond. This is a mechanism that helps prevent fake order spamming, wasting time of counterparts and DDOSing the order book.
As soon as the seller locks the satoshis, it is safe to send the fiat currency! As a buyer, you will have to ask the seller for the details to send fiat. Only share the strictly needed information about yourself to not compromise your privacy. Remember, in RoboSats v0.1.0 this chat is memoryless, so the conversation will be lost if you refresh the browser.
There is a time limit of 24 hours to complete the fiat exchange. If the time runs out, the order will expire and a dispute will be opened automatically. To avoid order expiration, use always instant fiat payment methods. For example, sending cash by ordinary mail is slow and will always trigger a dispute in v0.1.0. In the future longer expiry times will be possible.
As soon as you have sent the fiat, you should tap on “Confirm fiat sent” button. After that, the seller will have to confirm the fiat was received. As soon as he confirms the trade is finished and you will be paid out to your lightning wallet. You might see that it is “sending satoshis to buyer” but usually it is so fast you will simply see this screen. Enjoy your sats!
Rating the platform and leaving tips for improvement in our Telegram group or Github Issues is super appreciated!
Walkthrough-2: Making an order as a sellerPermalink It might happen that there are no active orders for the positioning and currency you want. In this case, there is no orders to SELL bitcoin for GBP.
We can create the order exactly has we want it. But mind that you need to publish an order that others want to take too!
In the maker page you are only required to enter the currency, order type (buy/sell) and amount. However, it is best practice to specify the payment methods you allow. It might be also helpful to set a premium/discount for your order to be taken faster. Remember that as a seller you can incentivze buyers to take your order by lowering the premium. If there are too many buyers, however, you can increase the premium to have a trading profit. Alternatively, you can set a fixed amount of Satoshis.
Limits: in Robosats v0.1.0 an order cannot be smaller than 20,000 Satoshis. It cannot be larger than 4,000,000 Satoshis in order to avoid lightning routing failures. This limit will be increased in the future.
You have to copy or scan the invoice with your lightning wallet in order to lock your fidelity maker bond (just 1% of the trade amount)). By locking this bond, the takers know you can be trusted and are committed to follow with this trade. In your wallet it might show as a payment that is on transit, freeze or even seemingly break your wallet. You should always check on the RoboSats website whether the bond has been locked (your wallet will probably not tell you! Check wallet compatibility list)
Your order will be public for 24 hours. You can check the time left to expiration by checking the “Order” tab. It can be canceled at any time without penalty before it is taken by another robot. Keep the contract tab open to be notified with this sound. It might be best to do this on a desktop computer and turn on the volume, so you do not miss when your order is taken. It might take long! Maybe you even forget! You can also enable telegram notifications by pressing “Enable Telegram Notification” and then pressing “Start” in the chat. You will receive a welcome message as confirmation of the enabled notifications. Another message will be sent once a taker for your order is found.
Note: If you forget your order and a robot takes it and locks his fidelity bond, you risk losing your own fidelity bond by not fulfilling the next contract steps.
In the contract tab you can also see how many other orders are public for the same currency. You can also see how well does your premium ranks among all other orders for the same currency.
Hurray, someone took the order! They have 4 minutes to lock a taker fidelity bond, if they do not proceed, your order will be made public again automatically.
As soon as the taker locks the bond, you will have to lock the trade escrow. This is a lightning hold invoice and will also freeze in your wallet. It will be released only when you confirm you received the fiat payment or if there is a dispute between you and the taker.
Once you lock the trade escrow and the buyer submit the payout invoice it is safe to send fiat! Share with the buyer the minimal information needed to send you fiat. Remember, in RoboSats v0.1.0 this chat is memoryless, so the conversation will be lost if you refresh the browser.
The buyer has just confirmed he did his part! Now check until the fiat is in your account.
By confirming that you received the fiat, the escrow will be charged and sent to the buyer. So only do this once you are 100% sure the fiat is with you!
All done!! :D
Collaborative cancellationPermalink After the trade escrow has been posted and before the buyer confirms he sent the fiat it is possible to cancel the order. It might just happen that you both do not have a common way to send and receive fiat after all. You can agree to tap on the “Collaborative cancel” button. After the “Fiat sent” button is pressed by the buyer, the only way to cancel an order is by opening a dispute and involving the staff.
This is totally not recommended, one of the two traders would lose his fidelity bond except in exceptional cases (up to the discretion of the staff)
In Conclusion, Robosats is an amazing platform to stack sats KYC free and it is a good step away from financial surveillance. This was a good detailed explanation in written but I to watch a couple video tutorials as well. Thank you!
It's Friday after a long week of hard work, I fall on this old video song by Madonna - called "Ray Of Light". I have no idea what she is saying in the song but the images remind me of something that I have been thinking of for years now, something that I could never explain to a five-year-old at a straight face.
The video starts with the beautiful sun rising in the sky while she has to rush on getting ready for work, you see everybody running like crazy ants to get on the cars, trains, busses, airplanes, taxies to go do some sorts of activity to generate income which is a must if you want to survive in this world, meanwhile I saw two dogs sit back relaxing, They must be thinking the same thing as I am "These people are really crazy, working for fiat fake money". She showed the time clock running so fast people are running out of time to even take their time to sit and eat properly, the rat has to keep on running with no ending sight with fake hope of getting out one day, the cycle repeats over and over again, and the tragedy of it all is that no one is noticing that this is a fake set-up made up by a small group of overlords controlling the supply of the money.
But what is the solution? Or what is a real way to skip this trap? Well the solution may never be in the same fiat "fake money" setup everyone is running for, but in a money that is outside the system "Bitcoin". Bitcoin is the only money they cannot print more of no matter how are hard they try. The Bitcoin supply is maxed at 21 Million till the end of times, you need a lot of work and energy to mine it in thime which makes it absolute scarcity. Bitcoin is as scarce as our limited time on earth. If you plan on spending a lifetime rate racing at least convert some of that income into something as scarce as your life time "bitcoin".
But should you stop working and just move everything to Bitcoin and call it a day? No, in my opinion you should keep on providing good value to society, keep doing what you do but even better now since you are working to convert your saving in perfect money, and you should upgrade your skills if you can to stack more Sats(bitcoins). The more you accumulate Sats(bitcoin) the closer you are to your freedom, because Bitcoin is the freedom money.
In conclusion, I could be completely misinterpreting the song and I am sorry if I do but I was glad to find a visual way to explain my observation of this tragedy that we are all experiencing. But fortunately enough to every problem there is a solution thus "Thank you Satoshi for Bitcoin!"
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Step 2. Download Umbrel OS.
New to Bitcoin/Crypto? As a Newbie, when I first got into Bitcoin I thought it was about outsmarting the market and getting rich quick on ''promising'' crypto projects. After properly get rekt I quickly learned my lesson and realized that this was never the way to go and that Bitcoin is the only thing that matters. Unfortunately I am not the only one who is going to get stuck with this interesting story to tell, so I am writing this article to minimize the pain for future newcomers who want to avoid these expensive mistakes and learn from them. At the end of this article I plan on revealing the most effective strategy to accumulate bitcoin. So it’s probably a good idea to read till the end.
Now, let's see how to invest in bitcoin safely to avoid
getting rekt
I understand how humans love learning from their own mistakes, but some
mistakes are so expensive it worthwhile learning them from somebody else
and avoid making them. Bitcoin is a hard concept to understand. It requires
a lot of time and motivations but it is obtainable with the right mindset.
I hope I made a good case for the best strategy which is DCA, the simplest
and provably the most successful one. But you may find a strategy that works
best for you, in that case you should keep using it and tell us about it in the
comment section below. But no matter what strategy you are using make sure
you have control over your keys.
How Does It Feel To Lose Everything In Hyperinflation?
My goal is to help as many people as I can crossing the bridge of understanding the Bitcoin saving
technology so they can protect themselves. If this post helped you in any shape or form and you would like
to support me you are welcome to contribute with as little as $0.5 to this bitcoin address below. But
most importantly please share this with your family and friends to help them out in understanding the
Bitcoin potential to save their lives.
* Stream me some sats on Fountain with my Fountain Lightning Address - theunthinkable@fountain.fm
Bitcoin: A Peer-to-Peer Electronic Cash System
Satoshi Nakamoto
satoshi@gmx.com
www.bitcoin.org
Abstract. A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they’ll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.
Commerce on the Internet has come to rely almost exclusively on financial institutions serving as trusted third parties to process electronic payments. While the system works well enough for most transactions, it still suffers from the inherent weakness of the trust based model. Completely non-reversible transactions are not really possible, since financial institutions cannot avoid mediating disputes. The cost of mediation increases transaction costs, limiting the minimum practical transaction size and cutting off the possibility for small casual transactions, and there is a broader cost in the loss of ability to make non-reversible payments for non-reversible services. With the possibility of reversal, the need for trust spreads. Merchants must be wary of their customers, hassling them for more information than they would otherwise need. A certain percentage of fraud is accepted as unavoidable. These costs and payment uncertainties can be avoided in person by using physical currency, but no mechanism exists to make payments over a communications channel without a trusted party.
What is needed is an electronic payment system based on cryptographic proof instead of trust, allowing any two willing parties to transact directly with each other without the need for a trusted third party. Transactions that are computationally impractical to reverse would protect sellers from fraud, and routine escrow mechanisms could easily be implemented to protect buyers. In this paper, we propose a solution to the double-spending problem using a peer-to-peer distributed timestamp server to generate computational proof of the chronological order of transactions. The system is secure as long as honest nodes collectively control more CPU power than any cooperating group of attacker nodes.
We define an electronic coin as a chain of digital signatures. Each owner transfers the coin to the next by digitally signing a hash of the previous transaction and the public key of the next owner and adding these to the end of the coin. A payee can verify the signatures to verify the chain of ownership.
The problem of course is the payee can’t verify that one of the owners did not double-spend the coin. A common solution is to introduce a trusted central authority, or mint, that checks every transaction for double spending. After each transaction, the coin must be returned to the mint to issue a new coin, and only coins issued directly from the mint are trusted not to be double-spent. The problem with this solution is that the fate of the entire money system depends on the company running the mint, with every transaction having to go through them, just like a bank.
We need a way for the payee to know that the previous owners did not sign any earlier transactions. For our purposes, the earliest transaction is the one that counts, so we don’t care about later attempts to double-spend. The only way to confirm the absence of a transaction is to be aware of all transactions. In the mint based model, the mint was aware of all transactions and decided which arrived first. To accomplish this without a trusted party, transactions must be publicly announced [1], and we need a system for participants to agree on a single history of the order in which they were received. The payee needs proof that at the time of each transaction, the majority of nodes agreed it was the first received.
The solution we propose begins with a timestamp server. A timestamp server works by taking a hash of a block of items to be timestamped and widely publishing the hash, such as in a newspaper or Usenet post [2-5]. The timestamp proves that the data must have existed at the time, obviously, in order to get into the hash. Each timestamp includes the previous timestamp in its hash, forming a chain, with each additional timestamp reinforcing the ones before it.
To implement a distributed timestamp server on a peer-to-peer basis, we will need to use a proof-of-work system similar to Adam Back’s Hashcash [6], rather than a newspaper or Usenet posts. The proof-of-work involves scanning for a value that when hashed, such as with SHA-256, the hash begins with a number of zero bits. The average work required is exponential in the number of zero bits required and can be verified by executing a single hash.
For our timestamp network, we implement the proof-of-work by incrementing a nonce in the block until a value is found that gives the block’s hash the required zero bits. Once the CPU effort has been expended to make it satisfy the proof-of-work, the block cannot be changed without redoing the work. As later blocks are chained after it, the work to change the block would include redoing all the blocks after it.
The proof-of-work also solves the problem of determining representation in majority decision making. If the majority were based on one-IP-address-one-vote, it could be subverted by anyone able to allocate many IPs. Proof-of-work is essentially one-CPU-one-vote. The majority decision is represented by the longest chain, which has the greatest proof-of-work effort invested in it. If a majority of CPU power is controlled by honest nodes, the honest chain will grow the fastest and outpace any competing chains. To modify a past block, an attacker would have to redo the proof-of-work of the block and all blocks after it and then catch up with and surpass the work of the honest nodes. We will show later that the probability of a slower attacker catching up diminishes exponentially as subsequent blocks are added.
To compensate for increasing hardware speed and varying interest in running nodes over time, the proof-of-work difficulty is determined by a moving average targeting an average number of blocks per hour. If they’re generated too fast, the difficulty increases.
The steps to run the network are as follows:
Nodes always consider the longest chain to be the correct one and will keep working on extending it. If two nodes broadcast different versions of the next block simultaneously, some nodes may receive one or the other first. In that case, they work on the first one they received, but save the other branch in case it becomes longer. The tie will be broken when the next proof-of-work is found and one branch becomes longer; the nodes that were working on the other branch will then switch to the longer one.
New transaction broadcasts do not necessarily need to reach all nodes. As long as they reach many nodes, they will get into a block before long. Block broadcasts are also tolerant of dropped messages. If a node does not receive a block, it will request it when it receives the next block and realizes it missed one.
By convention, the first transaction in a block is a special transaction that starts a new coin owned by the creator of the block. This adds an incentive for nodes to support the network, and provides a way to initially distribute coins into circulation, since there is no central authority to issue them. The steady addition of a constant amount of new coins is analogous to gold miners expending resources to add gold to circulation. In our case, it is CPU time and electricity that is expended.
The incentive can also be funded with transaction fees. If the output value of a transaction is less than its input value, the difference is a transaction fee that is added to the incentive value of the block containing the transaction. Once a predetermined number of coins have entered circulation, the incentive can transition entirely to transaction fees and be completely inflation free.
The incentive may help encourage nodes to stay honest. If a greedy attacker is able to assemble more CPU power than all the honest nodes, he would have to choose between using it to defraud people by stealing back his payments, or using it to generate new coins. He ought to find it more profitable to play by the rules, such rules that favour him with more new coins than everyone else combined, than to undermine the system and the validity of his own wealth.
Once the latest transaction in a coin is buried under enough blocks, the spent transactions before it can be discarded to save disk space. To facilitate this without breaking the block’s hash, transactions are hashed in a Merkle Tree [7][2][5], with only the root included the block’s hash. Old blocks can then be compacted by stubbing off branches of the tree. The interior hashes do not need to be stored.
A block header with no transactions would be about 80 bytes. If we suppose blocks are generated every 10 minutes, 80 bytes * 6 * 24 * 365 = 4.2MB per year. With computer systems typically selling with 2GB of RAM as of 2008, and Moore’s Law predicting current growth of 1.2GB per year, storage should not be a problem even if the block headers must be kept in memory.
It is possible to verify payments without running a full network node. A user only needs to keep a copy of the block headers of the longest proof-of-work chain, which he can get by querying network nodes until he’s convinced he has the longest chain, and obtain the Merkle branch linking the transaction to the block it’s timestamped in. He can’t check the transaction for himself, but by linking it to a place in the chain, he can see that a network node has accepted it, and blocks added after it further confirm the network has accepted it.
As such, the verification is reliable as long as honest nodes control the network, but is more vulnerable if the network is overpowered by an attacker. While network nodes can verify transactions for themselves, the simplified method can be fooled by an attacker’s fabricated transactions for as long as the attacker can continue to overpower the network. One strategy to protect against this would be to accept alerts from network nodes when they detect an invalid block, prompting the user’s software to download the full block and alerted transactions to confirm the inconsistency. Businesses that receive frequent payments will probably still want to run their own nodes for more independent security and quicker verification.
Although it would be possible to handle coins individually, it would be unwieldy to make a separate transaction for every cent in a transfer. To allow value to be split and combined, transactions contain multiple inputs and outputs. Normally there will be either a single input from a larger previous transaction or multiple inputs combining smaller amounts, and at most two outputs: one for the payment, and one returning the change, if any, back to the sender.
It should be noted that fan-out, where a transaction depends on several transactions, and those transactions depend on many more, is not a problem here. There is never the need to extract a complete standalone copy of a transaction’s history.
The traditional banking model achieves a level of privacy by limiting access to information to the parties involved and the trusted third party. The necessity to announce all transactions publicly precludes this method, but privacy can still be maintained by breaking the flow of information in another place: by keeping public keys anonymous. The public can see that someone is sending an amount to someone else, but without information linking the transaction to anyone. This is similar to the level of information released by stock exchanges, where the time and size of individual trades, the “tape”, is made public, but without telling who the parties were.
As an additional firewall, a new key pair should be used for each transaction to keep them from being linked to a common owner. Some linking is still unavoidable with multi-input transactions, which necessarily reveal that their inputs were owned by the same owner. The risk is that if the owner of a key is revealed, linking could reveal other transactions that belonged to the same owner.
We consider the scenario of an attacker trying to generate an alternate chain faster than the honest chain. Even if this is accomplished, it does not throw the system open to arbitrary changes, such as creating value out of thin air or taking money that never belonged to the attacker. Nodes are not going to accept an invalid transaction as payment, and honest nodes will never accept a block containing them. An attacker can only try to change one of his own transactions to take back money he recently spent.
The race between the honest chain and an attacker chain can be characterized as a Binomial Random Walk. The success event is the honest chain being extended by one block, increasing its lead by +1, and the failure event is the attacker’s chain being extended by one block, reducing the gap by -1.
The probability of an attacker catching up from a given deficit is analogous to a Gambler’s Ruin problem. Suppose a gambler with unlimited credit starts at a deficit and plays potentially an infinite number of trials to try to reach breakeven. We can calculate the probability he ever reaches breakeven, or that an attacker ever catches up with the honest chain, as follows [8]:
p = probability an honest node finds the next block
q = probability the attacker finds the next block
qz = probability the attacker will ever catch up from z blocks behind
Given our assumption that p > q, the probability drops exponentially as the number of blocks the attacker has to catch up with increases. With the odds against him, if he doesn’t make a lucky lunge forward early on, his chances become vanishingly small as he falls further behind.
We now consider how long the recipient of a new transaction needs to wait before being sufficiently certain the sender can’t change the transaction. We assume the sender is an attacker who wants to make the recipient believe he paid him for a while, then switch it to pay back to himself after some time has passed. The receiver will be alerted when that happens, but the sender hopes it will be too late.
The receiver generates a new key pair and gives the public key to the sender shortly before signing. This prevents the sender from preparing a chain of blocks ahead of time by working on it continuously until he is lucky enough to get far enough ahead, then executing the transaction at that moment. Once the transaction is sent, the dishonest sender starts working in secret on a parallel chain containing an alternative version of his transaction.
The recipient waits until his transaction has been added to a block and z blocks have been linked after it. He doesn’t know the exact amount of progress the attacker has made, but assuming the honest blocks took the average expected time per block, the attacker’s potential progress will be a Poisson distribution with expected value:
To get the probability the attacker could still catch up now, we multiply the Poisson density for each amount of progress he could have made by the probability he could catch up from that point:
Rearranging to avoid summing the infinite tail of the distribution…
Converting to C code…
#include <math.h> double AttackerSuccessProbability (double q, int z) { double p = 1.0 - q; double lambda = z * (q / p); double sum = 1.0; int i, k; for (k = 0; k <= z; k++) { double poisson = exp(-lambda); for (i = 1; i <= k; i++) poisson *= lambda / i; sum -= poisson * (1 - pow(q / p, z - k)); } return sum; }
Running some results, we can see the probability drop off exponentially with z.
q=0.1 z=0 P=1.0000000 z=1 P=0.2045873 z=2 P=0.0509779 z=3 P=0.0131722 z=4 P=0.0034552 z=5 P=0.0009137 z=6 P=0.0002428 z=7 P=0.0000647 z=8 P=0.0000173 z=9 P=0.0000046 z=10 P=0.0000012 q=0.3 z=0 P=1.0000000 z=5 P=0.1773523 z=10 P=0.0416605 z=15 P=0.0101008 z=20 P=0.0024804 z=25 P=0.0006132 z=30 P=0.0001522 z=35 P=0.0000379 z=40 P=0.0000095 z=45 P=0.0000024 z=50 P=0.0000006
Solving for P less than 0.1%
P < 0.001 q=0.10 z=5 q=0.15 z=8 q=0.20 z=11 q=0.25 z=15 q=0.30 z=24 q=0.35 z=41 q=0.40 z=89 q=0.45 z=340
We have proposed a system for electronic transactions without relying on trust. We started with the usual framework of coins made from digital signatures, which provides strong control of ownership, but is incomplete without a way to prevent double-spending. To solve this, we proposed a peer-to-peer network using proof-of-work to record a public history of transactions that quickly becomes computationally impractical for an attacker to change if honest nodes control a majority of CPU power. The network is robust in its unstructured simplicity. Nodes work all at once with little coordination. They do not need to be identified, since messages are not routed to any particular place and only need to be delivered on a best effort basis. Nodes can leave and rejoin the network at will, accepting the proof-of-work chain as proof of what happened while they were gone. They cote with their CPU power, expressing their acceptance of valid blocks by working on extending them and rejecting invalid blocks by refusing to work on them. Any needed rules and incentives can be enforced with this consensus mechanism.
[1] W. Dai, “b-money,” http://weidai.com/bmoney.txt, 1998
[2] H. Massias, X.S. Avila, and J.-J. Quisquater, “Design of a secure timestamping service with minimal trust requirements,” In 20th Symposium on Information Theory in the Benelux, May 1999.
[3] S. Haber, W.S. Stornetta, “How to time-stamp a digital document,” In Journal of Cryptology, vol 3, no 2, pages 99-111, 1991.
[4] D. Bayer, S. Haber, W.S. Stornetta, “Improving the efficiency and reliability of digital time-stamping,” In Sequences II: Methods in Communication, Security and Computer Science, pages 329-334, 1993.
[5] S. Haber, W.S. Stornetta, “Secure names for bit-strings,” In Proceedings of the 4th ACM Conference on Computer and Communications Security, pages 28-35, April 1997.
[6] A. Back, “Hashcash – a denial of service counter-measure,” http://www.hashcash.org/papers/hashcash.pdf, 2002.
[7] R.C. Merkle, “Protocols for public key cryptosystems,” In Proc. 1980 Symposium on Security and Privacy, IEEE Computer Society, pages 122-133, April 1980.
[8] W. Feller, “An introduction to probability theory and its implications,” 1957.