ACeD: Scalable Data Availability Oracle

Sheng, Peiyao; Xue, Bowen; Kannan, Sreeram; Viswanath, Pramod

doi:10.48550/arxiv.2011.00102

Cited by 3 publications

(29 citation statements)

References 18 publications

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“…consists of a data symbol and parity symbol from each layer of the PCMT above L j similar to [11], [23]. Precisely, it is given by the following:…”

Section: Polar Coded Merkle Tree (Pcmt)mentioning

confidence: 99%

“…2. The data symbols from each layer in Proof(C j [k][i]) lie on the path of C j [k][i] to the PCMT root; this path is used to check the integrity of C j [k][i] in a manner similar to checking the proofs for regular Merkle trees [1], and LCMT [9], [23].…”

Section: Polar Coded Merkle Tree (Pcmt)mentioning

confidence: 99%

“…2) Single sample download size: For an LCMT, as described in [9], [11], [23], each sample request consists of a base layer symbol of the CMT and the Merkle proof of the base layer symbol. Moreover, the Merkle proof of the base layer symbol consists of a data symbol and a parity symbol from each layer above the base layer (i.e., layers L j , j ∈ [l−1] ).…”

Section: Appendix C Performance Analysis and Comparisonmentioning

confidence: 99%

“…Thus, we provide the IC proof size when the d symbols are base layer symbols. Also note that, in IC proofs, the Merkle proof of a symbol only consists on the data symbols from each layer above the base layer (the parity symbols included in the Merkle proofs of the light node samples are only to get additional samples of the intermediate layers) [9], [23]. Thus, in an LCMT, for a failed parity check equation with d symbols, the size of the IC proof + d c y(q − 1)(l − 1).…”

Section: Appendix C Performance Analysis and Comparisonmentioning

confidence: 99%

See 3 more Smart Citations

Polar Coded Merkle Tree: Improved Detection of Data Availability Attacks in Blockchain Systems

Mitra¹,

Tauz²,

Dolecek³

2022

Preprint

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Lights nodes are commonly used in blockchain systems to combat the storage burden. However, light nodes are known to be vulnerable to data availability (DA) attacks where they accept an invalid block with unavailable portions. Previous works have used LDPC codes with Merkle Trees to mitigate DA attacks. However, LDPC codes have issues in the finite length due to the NP-hardness of ascertaining the minimum stopping set size, and in the asymptotic regime due to probabilistic guarantees on code performance. We circumvent both issues by proposing the novel Polar Coded Merkle Tree (PCMT) which is a Merkle Tree built from the encoding graphs of polar codes. We provide a specialized polar code construction called Sampling-Efficient Freezing that efficiently calculates the minimum stopping set size, thus simplifying design. PCMT performs well in detecting DA attacks for large transaction block sizes.

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“…consists of a data symbol and parity symbol from each layer of the PCMT above L j similar to [11], [23]. Precisely, it is given by the following:…”

Section: Polar Coded Merkle Tree (Pcmt)mentioning

confidence: 99%

Section: Polar Coded Merkle Tree (Pcmt)mentioning

confidence: 99%

Section: Appendix C Performance Analysis and Comparisonmentioning

confidence: 99%

Section: Appendix C Performance Analysis and Comparisonmentioning

confidence: 99%

See 2 more Smart Citations

Polar Coded Merkle Tree: Improved Detection of Data Availability Attacks in Blockchain Systems

Mitra¹,

Tauz²,

Dolecek³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Side blockchains, e.g., [5]- [8], are a popular method of improving the transaction throughput of blockchain systems where a single trusted blockchain supports a large number of side blockchains (smaller blockchain systems) by storing the block hashes of the side blockchains in their ledger [1]. Systems that run side blockchains are vulnerable to a form of data availability attack [3], [4] called a stalling attack, where a side blockchain node commits the hash of a block to the trusted blockchain but makes the block itself unavailable to other side blockchain nodes.…”

Section: Introductionmentioning

confidence: 99%

Communication-Efficient LDPC Code Design for Data Availability Oracle in Side Blockchains

Mitra¹,

Tauz²,

Dolecek³

2021

Preprint

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A popular method of improving the throughput of blockchain systems is by running smaller side blockchains that push the hashes of their blocks onto a trusted blockchain. Side blockchains are vulnerable to stalling attacks where a side blockchain node pushes the hash of a block to the trusted blockchain but makes the block unavailable to other nodes in the side blockchain. Recently, Sheng et al. proposed a data availability oracle based on LDPC codes and a data dispersal protocol as a solution to the above problem. While showing great improvements, the codes and the dispersal protocol were designed disjointly from each other which may not be optimal in terms of the communication cost associated with the oracle. In this paper, we provide a tailored dispersal protocol and a specialized LDPC code construction based on the Progressive Edge Growth (PEG) algorithm called the dispersal-efficient PEG (DE-PEG) algorithm aimed to reduce the communication cost associated with the new dispersal protocol. Our new code construction reduces the communication cost, and additionally, is less restrictive in terms of system design.

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Overcoming Data Availability Attacks in Blockchain Systems: LDPC Code Design for Coded Merkle Tree

Mitra

Tauz

Dolecek

2021

Preprint

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<div>In blockchain systems, full nodes store the entire blockchain ledger and validate all transactions in the system by operating on the entire ledger. However, for better scalability and decentralization of the system, blockchains also run light nodes that only store a small portion of the ledger. In blockchain systems having a majority of malicious full nodes, light nodes are vulnerable to a data availability (DA) attack. In this attack, a malicious node makes the light nodes accept an invalid block by hiding the invalid portion of the block from the nodes in the system. Recently, a technique based on LDPC codes called Coded Merkle Tree (CMT) was proposed by Yu et al. that enables light nodes to detect a DA attack by randomly requesting/sampling portions of the block from the malicious node. However, light nodes fail to detect a DA attack with high probability if a malicious node hides a small stopping set of the LDPC code. To mitigate this problem, Yu et al. used well-studied techniques to design random LDPC codes with high minimum stopping set size. Although effective, these codes are not necessarily optimal for this application. In this paper, we demonstrate that a suitable co-design of specialized LDPC codes and the light node sampling strategy can improve the probability of detection of DA attacks. We consider different adversary models based on their computational capabilities of finding stopping sets in LDPC codes. For a weak adversary model, we devise a new LDPC code construction termed as the entropy-constrained PEG (EC-PEG) algorithm which concentrates stopping sets to a small group of variable nodes. We demonstrate that the EC-PEG algorithm coupled with a greedy sampling strategy improves the probability of detection of DA attacks. For stronger adversary models, we provide a co-design of a sampling strategy called linear-programming-sampling (LP-sampling) and an LDPC code construction called linear-programming-constrained PEG (LC-PEG) algorithm. The new co-design demonstrates a higher probability of detection of DA attacks compared to approaches proposed in earlier literature.</div>

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ACeD: Scalable Data Availability Oracle

Cited by 3 publications

References 18 publications

Polar Coded Merkle Tree: Improved Detection of Data Availability Attacks in Blockchain Systems

Polar Coded Merkle Tree: Improved Detection of Data Availability Attacks in Blockchain Systems

Communication-Efficient LDPC Code Design for Data Availability Oracle in Side Blockchains

Overcoming Data Availability Attacks in Blockchain Systems: LDPC Code Design for Coded Merkle Tree

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