Suyash Bagad, Saravanan Vijayakumaran
Indian Institute of Technology, Bombay
Crypto Valley Conference on Blockchain Technology, 2020
No addresses, No amounts!
Provides Privacy, Scalability and Fungibility
First implementation by
A Blockchain protocol relying on Homomorphic Commitments
Hides amounts using Pedersen Commitments
Each output on Grin blockchain is a Pedersen Commitment
Pedersen Commitments are homomorphic, perfectly hiding and computationally binding
For an amount a∈{0,1,…,264−1} and blinding factor k∈Fq
where G,H∈G such that DL relation between them is unknown
Given an output P∈G it is infeasible to find the amount it commits to
Each output comes with a range proof proving a∈{0,1,…,264−1}
Block height Kernel offset |
Inputs | Outputs |
Reg. Transaction #2 |
Inputs | Outputs |
Reg. Transaction #1 |
Inputs | Outputs |
- |
Coinbase Transaction |
Dandelion
Block height Kernel offset |
Inputs | Outputs |
|
Cut-through
Block height Kernel offset |
Inputs | Outputs |
|
Block added to Blockchain!
Block height Kernel offset |
Inputs | Outputs |
|
Fees |
Kernel Excesses |
RTO
i=1,2,4∑Oi+(i=1,2∑fi)H−i=1∑4Ii=i=1,2∑Xi+koffG
A block contains n kernels, n= #Transactions
Each kernel contains fee and a kernel excess
Coinbase fee fcb=0, mining reward r=60 grin
Each kernel also contains a Schnorr signature proving that Xi=xiG for some xi∈Fq
Block validation check:
Block height |
Inputs | Outputs |
|
Fees |
Block height |
Inputs | Outputs |
|
Fees |
Block height |
Inputs | Outputs |
|
Fees |
General strategy: Compute number of donor coinbase outputs!
We define a directed graph G=(V,E) such that
Nodes V=Vbl∪Vcb, where Vbl are blocks and Vcb are coinbase outputs
Edges E=E1∪E2 where
E1=(v1,v2)∈Vcb×Vbl if coinbase output v1 is spent in block v2
E2=(v1,v2)∈Vbl2 if at least one RTO in block v1 is spent in block v2
16
1493
18
1489
1514
1504
h1
h1
h2
h2
h3
h3
A vertex c∈Vcb in G is called a donor of a block b∈Vbl if there is a directed path from c to b in G.
1499
16
1482
1469
1458
1481
1489
1495
1493
18
1479
38
33
9
5
7
Subgraph for h=1499, G(h)=(V(h),E(h)) where V(h)=Vbl(h)∪Vcb(h)
∴ A(Oh)≤ 7r+b∈Vcb(h)∑fb−b∈Vbl(h)∑fb
Analysis for RTOs in 612,102 blocks (till March 17th, 2020)
Flow ratio of RTO (FR)=Trivial upper bound of RTOFlow upper bound of RTO
For gauging effectiveness of flow upper bounds, we compute and plot
Block height
Flow ratio
88% blocks have FR>0.9,
6.6% blocks with h>105 have FR<0.5
Unspent RTOs depict the current state of the Blockchain (Fig. 2)
Block height
Flow ratio
Jagged pattern in Flow ratio is observed in Fig. 1, Why?
983 URTOs have upper bound less that 1800
Flow ratio
% of URTO set
95% of 110,149 URTOs have FR>0.9
Figure 1
Figure 2
Amounts in very few RTOs found to be in a narrow range
Confidentiality of most URTOs is preserved, however...
Transaction structure could reveal some information about amounts inspite of perfectly hiding commitments
Transaction volume increase might strengthen amount confidentiality
Linkability in inputs and outputs could be leveraged for tighter bounds
Would be interesting to design such analysis for Beam, Monero,...
Listening to ~600 peer nodes, transactions could be traced to their origin before they are aggregated
Ivan Bogatty claimed to have traced 96% of all Grin transactions
Image credits: https://github.com/bogatyy/grin-linkability
A. Kumar et al. demonstrated 3 attacks on traceability of inputs in Monero transactions, showing that In 87% of cases, the real output being redeemed can be identified!
Idea#1: 65% transactions have 0 mix-ins as of Feb, 2017!
Idea#2: An input being spent in a ring is the one with the highest block height, where it appeared as a TXO.
Image credits: https://eprint.iacr.org/2017/338.pdf
Mo¨ser et al. presented traceability analysis of Monero similar and concurrent to that of Kumar et al's work
Proposed a novel Binned Mixin Sampling strategy as a counter-measure
Characterised Monero usage based on user-behaviour
https://arxiv.org/pdf/1704.04299.pdf
A. Poelstra, "MimbleWimble" [Online], Available:
T. P. Pedersen, "Non-Interactive and Information-Theoretic Secure Verifiable Secret Sharing", in Advances in Cryptology - CRYPTO '91, Springer, 1992, pp. 129-140.
M. Möser, et al. “An Empirical Analysis of Traceability in the Monero Blockchain”. Proceedings on Privacy Enhancing Technologies (2018)
"Linking 96% of Grin transactions" [Online], Available:
A. Kumar, C. Fischer, S. Tople and P. Saxena, "A traceability analysis of Monero’s blockchain", European Symposium on Research in Computer Security – ESORICS 2017, pp. 153-173, 2017.
Happy to answer any questions!