COPYRIGHT NOTICE:
I RONALD KEALA KUA MARIA ALSO KNOWN AS SATOSHI NAKAMOTO INVENTOR OF BITCOIN AND BLOCKCHAIN TECHNOLOGY HEREBY AFFIRM THAT ALL MY COPYRIGHTS INCLUDING AN EQUITY BASED ELECTRONIC RESERVE CURRENCY PEER TO PEER ELECTRONIC CASH SYSTEM
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Type of Work: |
Text |
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Registration Number / Date: |
TXu002037698 / 2016-08-17 |
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Application Title: |
AN EQUITY BASED ELECTRONIC RESERVE CURRENCY PEER TO PEER ELECTRONIC CASH SYSTEM. |
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Title: |
AN EQUITY BASED ELECTRONIC RESERVE CURRENCY PEER TO PEER ELECTRONIC CASH SYSTEM. |
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Description: |
Electronic file (eService) |
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Copyright Claimant: |
Ronald Keala Kua Maria, 1971- . Address: 89226A Farrington Hwy, lot A, 89226A Farrington Hwy, lot A, Waianae, HI, 96792, United States. |
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Date of Creation: |
2016 |
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Authorship on Application: |
Satoshi Nakamoto, pseud. of Ronald Keala Kua Maria, 1971- ; Citizenship: United States. Authorship: text, computer program, artwork. |
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Rights and Permissions: |
Ronald Keala Kua Maria, aikoin.org, 89226A Farrington Hwy, lot A, lot A, Waianae, HI, 96792, United States, (808) 554-1341, (808) 554-1341, [email protected] |
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Copyright Note: |
C.O. correspondence. |
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Names: |
Maria, Ronald Keala Kua, 1971- |
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Nakamoto, Satoshi, pseud., 1971- |
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Ronald Keaka Kua Maria 03/16/2018
Ronald Keala Kua Maria
Satoshi Nakamoto
89226A Farrington Hwy.
Waianae Hi 96792 USA
[email protected]
Thesatoshinakamoto.com
Bitcoincopyrights.com
BitcoinCashCopyright.com
BCHCopyright.com
“THE
COIN OF ALL COINS”
AN EQUITY BASED ELECTRONIC RESERVE CURRENCY
PEER TO PEER ELECTRONIC CASH
SYSTEM
Ronald
K. Maria
[email protected]
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. (Also, A peer to peer
personal electronic equity based reserve currency is created through a dollar
for dollar automatic fractional equity bonus reward commerce system. A buyer
buys a product or service using any currency from the seller. At the end of the transaction the buyer
receives fractional equity bonuses of the sellers equity held in the buyers
personal reserve account (bitstox.com). Based on the personal equity reserve
coins are created, secured and intrinsically valued by true electronic commerce
equity which is held as an electronic reserve currency to be used as a personal
anchor currency to base any other currency used to buy more products and
services and earn more coins (aikoin.com). The more you buy and sell the more equity
(bitcoin cash) and coins (bitcoin) you earn as personal reserves. The coins also carry
the dollar for dollar value of any currency used thus increasing the stability
of the coin as an electronic reserve currency. The equity remains in reserve
and transfers between other users personal reserve accounts according to each
transaction.
1. Introduction
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
weaknesses 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 nonreversible
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.
2. Transactions
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 ownerand 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.
3. Timestamp Server
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.
4. Proof-of-Work
To implement a distributed timestamp server on a
peer-to-peer basis, we will need to use a proofof-
work system similar to Adam Back's Hashcash [6], rather than
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.
5. Network
The steps to run the network are as follows:
1) New transactions are broadcast to all nodes.
2) Each node collects new transactions into a block.
3) Each node works on finding a difficult proof-of-work for
its block.
4) When a node finds a proof-of-work, it broadcasts the
block to all nodes.
5) Nodes accept the block only if all transactions in it are
valid and not already spent.
6) Nodes express their acceptance of the block by working on
creating the next block in the
chain, using the hash of the accepted block as the previous
hash.
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.
6. Incentive
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 of 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.
7. Reclaiming Disk Space
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 in 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.
8. Simplified Payment Verification
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.
9. Combining and Splitting Value
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.
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.
10. Privacy
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.
11. Calculations
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 alternate version of his
transaction.
The recipient waits until the 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
12. Conclusion
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 vote 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.
References
[1]
W. Dai, "b-money," http://www.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,"
InSequences 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
applications," 1957.
