Payment channels are auspicious candidates in layer-2 solutions to reduce the number of on-chain transactions on traditional blockchains and increase transaction throughput. To construct payment channels, peers lock funds on 2-of-2 multisig addresses and open channels between one another to transact via instant peer-to-peer transactions. Transactions between peers without a direct channel are made possible by routing the payment over a series of adjacent channels. In certain cases, this can lead to relatively low transaction success rates and high transaction fees. In this work, we introduce pliability to constructing payment channels and graft edges with more than two endpoints into the payment graph. We refer to these constructions as hyperedges. We present hyperedge-based topologies to form hypergraphs and compare them to Bitcoin’s Lightning network and other state-of-the-art solutions. The results demonstrate that hyperedge-based implementations can both increase transaction success rate, in addition to decreasing the network cost by more than 50% compared to that of the Lightning Network.

Non-fungible tokens (NFTs) are digital assets representing ownership or proof of authenticity of a unique item. NFTs are blockchain-based and rely on smart contracts. The increase in duplicate NFTs in recent years brings the need for discovery tools for forged NFTs, some of which include using image hash functions. Though the problem of image duplication is widely discussed, detecting NFT duplications requires using fast detection methods as a new NFT image needs to be compared with the entire NFT history on the blockchain. In this paper, we analyze the performance of several image-hash functions, examine the cases where each function performs well, and evaluate multiple image-hash-functions-based NFT duplication detectors. Our approach achieves high accuracy in detecting NFT duplications and demonstrates that using several hash functions rather than one increases the ability to detect duplications.

Blockchain networks suffer from a critical scalability problem that is often expressed in two dimensions: the size of the network state and the computational overhead in processing transactions as part of the network update. This paper surveys two major families of solutions known as sketches and rollups that both rely on aggregation methods. Sketches are popular hash-based data structures used to represent a large amount of data while supporting particular queries such as on set membership, cardinality estimation and identification of large elements. Rollups play in a different form and refer to aggregation of the execution of multiple transactions to allow high transaction rates and low fees. The design of popular blockchain networks such as Bitcoin and Ethereum makes use of sketches for various tasks such as summarization of transaction blocks or declaring the interests of light nodes. In addition, rollups are implemented in several forms to allow high transaction rates through offloading parts of the execution out of the blockchain while keeping its security. This paper overviews the basics of sketches and rollups and provides a comprehensive survey on the wide range of existing applications of the two families in blockchains.

Payment channel networks (PCNs), also known as off-chain networks, implement a common approach to deal with the scalability problem of blockchain networks. They enable users to execute payments without committing them to the blockchain by relying on predefined payment channels. A pair of users can employ a payment even without a direct channel between them, by routing the payment via payment channels involving other intermediate users. Users, together with the channels, form a graph known as the off-chain network topology. The off-chain topology and the payment characteristics affect network performance such as the average number of intermediate users a payment is routed through or the values of transaction fees. In this paper, we study two basic problems in payment channel network design. First, efficiently mapping users to an off-chain topology with a known structure. Second, constructing a topology with a bounded number of channels that can serve users well with associated payments. We design algorithms for both problems while considering several fundamental topologies. We study topology-related real data statistics of Raiden, the off-chain extension for Ethereum as well as of Lightning, the equivalent off-chain layer of Bitcoin. We conduct experiments to demonstrate the effectiveness of the algorithms for these networks.

Layer-2 is a popular approach to deal with the scalability limitation of blockchain networks. It allows users to execute transactions without committing them to the blockchain by relying on predefined payment channels. Users together with the payment channels form a graph, known as the offchain network topology. Transactions between pairs of users without a connecting channel are also supported through a path of multiple channels. Serving such transactions involves fees paid to intermediate users. In this paper we uncover the potential existence of the Braess paradox in payment networks: Sometimes establishing a new payment channel can increase the fees paid for serving some fixed transactions. We study conditions for the paradox to appear and provide indications for the appearance of the paradox based on real data of Bitcoin's Lightning, a popular layer-2 network. Last, we discuss methods to mitigate the paradox upon establishing a new payment channel.