Energy Considerations in Blockchain-Enabled Applications

Blockchain-powered smart systems deployed in different industrial applications promise operational efficiencies and improved yields, while mitigating significant cybersecurity risks pertaining to the main application. Associated tradeoffs between availability and security arise at implementation, however, triggered by the additional resources (e.g., memory, computation) required by each blockchain-enabled host. This thesis applies an energy-reducing algorithmic engineering technique for Merkle Tree root and Proof of Work calculations, two principal elements of blockchain computations, as a means to preserve the promised security benefits but with less compromise to system availability. Using pyRAPL, a python library to measure computational energy, we experiment with both the standard and energy-reduced implementations of the Merkle Tree for different input sizes (in bytes) and of the Proof of Work for different difficulty levels. Our results show up to 98\% reduction in energy consumption is possible within the blockchain\u27s Merkle Tree construction module, such reductions typically increasing with larger input sizes. For Proof-of-Work calculations, our results show an average energy reduction of 20\% across typical difficulty levels. The proposed energy-reducing technique is potentially applicable to other key elements of blockchain computations, potentially affording even greener blockchain-powered systems than implied by only the Merkle Tree and Proof of Work results obtained thus far

Merkle tree

U radu je opisan način rada kriptografske strukture podataka Merkleovog stabla te se teorijski obraĎuju pojmovi poput hashiranja, pojedinih svojstava Merkleovog stabla i blockchaina. TakoĎer se otkriva uloga hash funkcija u samom radu blockchaina, odnosno Merkleovog stabla gdje se algoritmima poput provjere podataka i provjere dosljednosti stvara sustav utvrĎivanja integriteta podataka. A to je točno što je tehnologiji blockchaina trebalo da se razvije u najpopularniji decentralizirani sustav. Blockchain je otporan na zlonamjerno mijenjanje i brisanje podataka jer je svaka njegova transakcija više puta hashirana s ostalim transakcijama i blokovima meĎusobno. Bitcoin, koji je i započeo revoluciju kriptovaluta, nije jedini koji koristi ovu tehnologiju. Ethereum i mnoge druge kriptovalute koriste sličan koncept s malim razlikama u setu pravila ponašanja u mreži.This paper describes how the cryptographic structure of Merkle tree data works, and theoretically addresses concepts such as hashing, individual properties of the Merkle tree, and blockchain. It also reveals the role of hash functions in the blockchain itself, that is, the Merkle tree, where algorithms such as audit proof and consistency proof create a system for determining data integrity. And that is exactly what blockchain technology needed to become the most popular decentralized system. The blockchain is tamper proof because each of its transactions has been hashed multiple times with other transactions and blocks to each other. Bitcoin, which started all of this, is not the only one using this technology. Ethereum and many other cryptocurrencies use a similar concept with small differences in the behavioral rules of the network

HEX-BLOOM: An Efficient Method for Authenticity and Integrity Verification in Privacy-preserving Computing

Merkle tree is applied in diverse applications, namely, Blockchain, smart grid, IoT, Biomedical, financial transactions, etc., to verify authenticity and integrity. Also, the Merkle tree is used in privacy-preserving computing. However, the Merkle tree is a computationally costly data structure. It uses cryptographic string hash functions to partially verify the data integrity and authenticity of a data block. However, the verification process creates unnecessary network traffic because it requires partial hash values to verify a particular block. Moreover, the performance of the Merkle tree also depends on the network latency. Therefore, it is not feasible for most of the applications. To address the above issue, we proposed an alternative model to replace the Merkle tree, called HEX-BLOOM, and it is implemented using hash, Exclusive-OR and Bloom Filter. Our proposed model does not depends on network latency for verification of data block\u27s authenticity and integrity. HEX-BLOOM uses an approximation model, Bloom Filter. Moreover, it employs a deterministic model for final verification of the correctness. In this article, we show that our proposed model outperforms the state-of-the-art Merkle tree in every aspect

Lightweight Selective Disclosure for Verifiable Documents on Blockchain

To achieve lightweight selective disclosure for protecting privacy of document holders, we propose an XML format for documents that can hide arbitrary elements using a cryptographic hash function and salts, which allows to be partially digitally signed and efficiently verified, as well as a JSON format that can be converted to such XML. The documents can be efficiently proven to exist by representing multiple such structures as a Merkle tree and storing its root in blockchain. We show that our proposal has advantages over known methods that represent the document itself as a Merkle tree and partially hide it.Comment: 8 pages, 3 figures, 1 table. Submitted to ICT Expres

Integrity Proofs for RDF Graphs

Representing open datasets with the RDF model is becoming increasingly popular. An important aspect of this data model is that it can utilize the methods of computing cryptographic hashes to verify the integrity of RDF graphs. In this paper, we first develop a number of metrics to compare the state-of-the-art integrity proof methods and then present two new approaches to generate an integrity proof of RDF datasets: (i) semantic-based and (ii) structure-based. The semantic-based approach leverages timestamps (or other inherent notions of ordering) as an indexing key to construct a sorted Merkle tree variation, where timestamps are semantically extractable from the dataset. The structure-based approach utilizes the redundant structure of large RDF datasets to compress the dataset statements prior to generating a variation of a Merkle tree. We provide a theoretical analysis and an experimental evaluation of our two proposed methods. Compared to the Merkle and sorted Merkle tree, the semantic-based approach achieves faster querying performance for large datasets. The structure-based approach is well suited when RDF datasets contain large amounts of semantic redundancies. We also evaluate our methods' resistance to adversarial threats

Compact Sparse Merkle Trees

A Sparse Merkle tree is based on the idea of a complete Merkle tree of an intractable size. The assumption here is that as the size of the tree is intractable, there would only be a few leaf nodes with valid data blocks relative to the tree size, rendering the tree as sparse. We present a novel approach called Minimum distance path algorithm to simulate this Merkle tree of intractable size which gives us efficient space-time trade-offs. We provide the algorithms for insertion, deletion and (non -) membership proof for a leaf in this Compact Sparse Merkle tree