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

10.36227/techrxiv.16532853.v1 ◽

2021 ◽

Author(s):

Debarnab Mitra ◽

Lev Tauz ◽

Lara Dolecek

Keyword(s):

Linear Programming ◽

Ldpc Codes ◽

Sampling Strategy ◽

Ldpc Code ◽

Probability Of Detection ◽

Data Availability ◽

Malicious Node ◽

Code Construction ◽

Stopping Sets ◽

Stopping Set

<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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A Novel Quasi-Cyclic LDPC Codes Construction Method for High-Speed Parallel Decoding

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.347-350.3702 ◽

2013 ◽

Vol 347-350 ◽

pp. 3702-3707

Author(s):

Ming Ke Dong ◽

Da Wang ◽

Ya Dan Zheng ◽

Shang Zhu Wu ◽

Hai Ge Xiang

Keyword(s):

High Speed ◽

Block Size ◽

Ldpc Codes ◽

Ldpc Code ◽

Data Access ◽

Construction Method ◽

Parity Check ◽

Code Construction ◽

Low Density Parity Check ◽

Efficient Decoding

The decoding parallelism of quasi-cyclic low density parity check (QC-LDPC) codes, an important realization factor of LDPC codes, is limited by the block size. Joint row-column (JRC) decoding algorithm, an efficient decoding technique having low computation cost and small iteration number, also suffers from the decoding parallelism limitation in QC-LDPC application. In this paper, a novel LDPC-code construction method is presented and validated. This method constructs the row sets to eliminate the data access conflicts, and it clearly enhances the decoding parallelism while avoids any degradation of bit error rate (BER) performance.

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Stopping-Set Assisted Reinforced Belief Propagation for Decoding Short LDPC Codes

IEEE Communications Letters ◽

10.1109/lcomm.2021.3137222 ◽

2021 ◽

pp. 1-1

Author(s):

Asif Ali Zamzami ◽

Kuan-Chuan Chao ◽

Shih-Chun Lin

Keyword(s):

Belief Propagation ◽

Ldpc Codes ◽

Stopping Set

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Stopping sets: Gamma-type results and hitting properties

Advances in Applied Probability ◽

10.1239/aap/1029955139 ◽

1999 ◽

Vol 31 (2) ◽

pp. 355-366 ◽

Cited By ~ 21

Author(s):

Sergei Zuyev

Keyword(s):

Point Process ◽

Sampling Theorem ◽

Random Sets ◽

Scaling Properties ◽

Stopping Sets ◽

Stopping Set ◽

Alternative Description ◽

Natural Filtration ◽

Random Figure ◽

Optional Sampling Theorem

Recently in the paper by Møller and Zuyev (1996), the following Gamma-type result was established. Given n points of a homogeneous Poisson process defining a random figure, its volume is Γ(n,λ) distributed, where λ is the intensity of the process. In this paper we give an alternative description of the class of random sets for which the Gamma-type results hold. We show that it corresponds to the class of stopping sets with respect to the natural filtration of the point process with certain scaling properties. The proof uses the martingale technique for directed processes, in particular, an analogue of Doob's optional sampling theorem proved in Kurtz (1980). As well as being compact, this approach provides a new insight into the nature of geometrical objects constructed with respect to a Poisson point process. We show, in particular, that in this framework the probability that a point is covered by a stopping set does not depend on whether it is a point of the process or not.

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Does Investment-Related Pressure Lead to Misreporting? An Analysis of Reporting Following M&A Transactions

The Accounting Review ◽

10.2308/accr-10210 ◽

2012 ◽

Vol 87 (3) ◽

pp. 839-865 ◽

Cited By ~ 34

Author(s):

Daniel A. Bens ◽

Theodore H. Goodman ◽

Monica Neamtiu

Keyword(s):

Financial Reporting ◽

Large Body ◽

Financial Statements ◽

Probability Of Detection ◽

Data Availability ◽

The Public ◽

Announcement Returns ◽

Reporting Decisions ◽

The Face ◽

Near Term

ABSTRACT This study examines whether managers alter their financial reporting decisions in the face of investment-related pressure. We define investment-related pressure as the increased pressure managers feel to retain their job following an M&A poorly received by the market. We hypothesize that managers attempt to assuage pressure by delivering strong performance post-merger, creating incentives for misreporting. Our findings indicate that acquirers with more negative M&A announcement returns are more likely to misstate financial statements in the post-investment period and the issuance of misstated financials mitigates this pressure, at least in the near term. Our study contributes to the literature on the relation between corporate investing and financial reporting by showing how investment-related pressure leads to misreporting, even in a setting where the costs (e.g., greater probability of detection) are high. Our study also has implications for the large body of research that evaluates various consequences of M&As using post-merger performance. Specifically, researchers should be careful to distinguish real from misstated financial performance in the post-investment period. Data Availability: Data are available from the public sources indicated in the text.

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