AuditPCH: Auditable Payment Channel Hub with Privacy Protection

Off-chain payments in the Internet of Things (IoT) enhance the efficiency and scalabilityof blockchain transactions. However, existing privacy mechanisms face challenges, suchas the disclosure of payment channels and transaction traceability. Additionally, therise of quantum computing threatens traditional public key cryptography, making thedevelopment of post-quantum secure methods for privacy protection essential. This paperproposes a post-quantum ring signature scheme based on hash functions that can beapplied to off-chain payments, enhancing both anonymity and linkability. The schemeis designed to resist quantum attacks through the use of hash-based signatures and toprevent double spending via its linkable properties. Furthermore, the paper introduces animproved Hash Time-Locked Contract (HTLC) that incorporates a Signature of Knowledge(SOK) to conceal the payment path and strengthen privacy protection. Security analysisand experimental evaluations demonstrate that the system strikes a favorable balancebetween privacy, computational efficiency, and security. Notably, the efficiency benefitsof basic signature verification are particularly evident, offering new insights into privacyprotection for post-quantum secure blockchain.

The paper examines the foundations of user trust in digital payments, using quantitative analysis of data from 277 participants. The study focuses on the associations between perceived security, convenience, privacy protection, and user trust in digital payments. Our findings suggest that all three attributes, safety, security, and privacy, are powerful positive correlates of trust. Furthermore, past experience with digital payments (PEDP) modifies these relationships, suggesting that the impact of these attributes on trust can have significant implications for engaged user digital payments are greatly enhanced We can use persuasive design principles and advanced deep learning to enhance user trust. The study proposes a hybrid deep learning model combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory networks (LSTMs) for enhanced feature extraction and temporal sequence analysis of user interactions and preferences within digital payment environments. This model is complemented by a hybrid optimization algorithm merging the Zebra Optimization Algorithm (ZOA) and Seagull Optimization Algorithm (SOA), aimed at refining system performance and user engagement through iterative enhancement of persuasive elements. This paper lays the groundwork for further research on other factors affecting the use of trust and cultural diversity in digital payment channels. Combining mind-blowing technologies with sophisticated deep learning techniques, it seeks to develop digital payment systems that not only secure transactions but also provide lasting user trust, satisfaction planning and implementation improvements.

Payment channel networks (PCNs) are emerged as the most widely deployed solution to mitigate the scalability problem of permissionless cryptocurrencies, allowing vast payments to be carried out off-chain. Routing, which finds feasible paths between the senders and receivers, is critical for PCNs. However, existing solutions either fail to achieve high scalability that can maintain low storage/computation/network communication overhead, or they are susceptible to privacy disclosure. In this paper, we propose SorTEE, a service-oriented routing solution for PCNs, which adopts a set of service nodes to alleviate the per-user burden of routing and achieves more comprehensive privacy guarantees than the state-of-the-art by leveraging trusted execution environments (TEEs). SorTEE demands users communicate with the TEE by the secure channel to protect the privacy of transaction value. Then, an oblivious path mechanism is designed to construct redundant paths with the pseudo senders and receivers generated by TEEs to confuse its untrusted controller. Further, we report a novel attack that allows malicious service nodes to drop the valid paths for profit, and design a feedback mechanism to relieve it. Moreover, SorTEE hides the identities of the senders/receivers for the intermediate nodes of payment paths by introducing a novel identity information transfer scheme called encrypted identity chain. Based on security analysis and performance evaluation, our results demonstrate that SorTEE is able to achieve sufficient privacy-preserving payment and low per-user overhead.

Payment channels serve as an effective solution to the scalability problem of cryptocurrencies, which significantly increase transaction rates by allowing users to conduct large-scale offline transactions off-chain without posting everything to the blockchain. However, the existing payment channels lack privacy protection for the transaction amount and the linking relationship between the two parties to the transaction. Therefore, in order to address the scalability and privacy issues of cryptocurrencies such as Bitcoin, this paper proposes a zk-SNARKs-based anonymous payment channel (zk-APC), which supports an unlimited number of off-chain payments between the payer and the payee and protects the privacy of the participants. Specifically, the proposed scheme achieves relational anonymity and amount privacy for both on-chain and off-chain transactions in the payment channel through utilizing zero-knowledge proof (zk-SNARKs) and commitment schemes. This paper proves that the proposed method is more effective than similar schemes through a performance evaluation.

In today’s information technology age, the issue of cyber Security is a complicated and fascinating area of law. The phenomenal growth and development of e-commerce in India is astounding. However, with the rising dependence on internet commerce, the dangers of fraud and security and trust problems have become severe impediments. Creating robust legal and regulatory frameworks that meet the growing concerns about online fraud, data security, and intellectual property protection in both local and international business contexts is critical. The e-commerce sector, like any expanding business, confronts various obstacles, primarily due to an inadequate and inefficient legal and regulatory framework that fails to guarantee the rights and duties of all players engaged sufficiently. To protect user data, tackle cyber threats, and maintain customer trust, e-commerce enterprises must comply with legal regulations. In India, cybersecurity governance falls under the Information Technology Act of 2000, regulating e-commerce, electronic contracts, data protection, and cybercrimes. The imminent passage of the Personal Data Protection Bill, 2019, is expected after ongoing review. The Indian Penal Code addresses unauthorized access, hacking, identity theft, phishing, and computer virus dissemination. The Reserve Bank of India oversees online payment and financial security, mandating two-factor authentication, encryption, and secure payment channels. CERT-In coordinates national cybersecurity incidents, while electronic signatures and digital certificates hold legal recognition. Intellectual Property Laws regulate online violations of patents, copyrights, and trademarks. The Indian government also enforces cybersecurity standards for enterprises and organizations, covering IT infrastructure and incident response. Nonetheless, further steps must be taken to improve the efficiency of India’s cyber security regulations. This research study uses a doctrinal and analytical approach to examine India’s present Cyber Security Laws and Guidelines. It assesses their effectiveness in addressing legal concerns with Security, privacy, and data protection inside the country. It also evaluates the legal structure that governs the link between e-commerce and Cyber Laws in India. This research will provide a thorough overview of the present condition of cyber security regulations in India, setting the way for prospective reforms and progress in this critical area.

Mimblewimble, proposed by an anonymous author in 2016, combines several privacy protection technologies to enhance the Bitcoin blockchain. However, Mimblewimble does not support fast micropayments, and there are still problems such as high transaction fees and poor scalability. The payment channel allows all parties to perform transactions off-chain while maintaining the security of transactions on-chain to reduce the burden of the blockchain. It has been used in the Lightning Network to expand the blockchain. On the basis of Mimblewimble, our paper exploits a method of adding a random blinding factor to the amount of additively homomorphic commitments, and describes a scheme of using payment channels for fast off-chain transactions. The scheme can implement fast off-chain payments and improve scalability while protecting transaction privacy.

Payment channel networks (PCNs) are one of the most promising off‐chain solutions to the blockchain scalability problem. However, most current payment channel schemes suffer from overly ideal routing assumptions or fail to provide complete path privacy protection. To address the above problems, the multi‐hop anonymous and privacy‐preserving PCN scheme are analyzed and a multi‐hop anonymous PCN based on onion routing is proposed based on it. The scheme removes the routing assumptions of the original scheme, designs an onion routing‐based payment channel network, and modifies the way relay nodes construct elliptic curve discrete logarithmic problems to resist wormhole attacks. Finally, the security analysis shows that the scheme in this paper has atomicity, relational anonymity and resistance to wormhole attacks. The latest bilinear pairing anonymous multi‐hop payment (EAMHL+) scheme is used to compare communication and computing overhead. The results show that the scheme in this paper requires less communication overhead and is more efficient in terms of computational overhead when the average hop number of the payment channel network is 3 hops and the network diameter is 6 hops.

Payment Channel Network (PCN) is proposed as a promising layer-two solution to tackle the scalability problem of current blockchain systems, which allows the two transacting parties to perform off-chain transactions through their established payment channel. For the transacting parties who are not directly connected, PCN allows them to route the transaction through some intermediate nodes with sufficient balance. Designing an efficient routing protocol is one of the most important and challenging problems in improving the performance of PCN. To tackle this challenge, we propose Real-Time Recursive Routing (RTRR), an efficient routing algorithm that can achieve a short routing time with strong privacy protection and high flexibility in the dynamic scenario. In addition, we investigate the bidding process in RTRR and derive the equilibrium strategy, which implies that the proposed protocol prefers to route the transaction through the nodes with a higher success rate, contributing to a better performance. Both the theoretical analyses and the empirical experiment results demonstrate the high efficiency of RTRR.

Blockchain technology is widely applicable to modern payment systems but has inherent throughput limitations. Off-chain networks are proposed to solve scalability issues, which allows parties to efficiently perform micropayments without committing all of the payments to the blockchain. Off-chain payments with security and privacy protection requirements use the smart contract to ensure security and reduce the risk of sensitive information leakage. Although off-chain payments avoid expensive on-chain operations, it raises many concerns, such as the capacity limitation of payment channels and highly dynamic channel status, lowering the throughput of payment channel networks (PCNs). In our work, we explore the path overlap issues in PCNs and propose a decentralized payment routing scheme to improve the network throughput and reduce the redundant traffic overhead of PCNs, thereby guaranteeing efficient payments. The simulation results indicate that the proposed routing algorithm can achieve higher throughput than other routing schemes while guaranteeing short payment times.

Ethereum is a public blockchain platform with smart contract. However, it has transaction privacy issues due to the openness of the underlying ledger. Decentralized mixing schemes are presented to hide transaction relationship and transferred amount, but suffer from high transaction cost and long transaction latency. To overcome the two challenges, we propose the idea of batch accounting, adopting batch processing at the time of accounting. For further realization, we introduce payment channel technology into decentralized mixer. Since intermediate transactions between two parties do not need network consensus, our scheme can reduce both transaction cost and transaction latency. Moreover, we provide informal definitions and proofs of our scheme's security. Finally, our scheme is implemented based on zk-SNARKs and Ganache, and experimental results show that the higher number of transactions in batch, the better our scheme performs.

Payment channel networks (PCN) have demonstrated its significant advantages in improving the scalability of blockchain. However, the existing work of PCN leads to serious privacy leakage problem that intermediate nodes along a payment path can collude to obtain the payment amounts and payment receivers. To address this problem, we propose to move PCN-related modules into the Trusted Execution Environment (TEE) commonly available on modern CPUs, so that adversaries cannot access the critical payment information protected by TEE, even though they compromise the software (e.g., blockchain clients or operating system) outside of TEE. An additional challenge is that adversaries can still infer payment receivers by observing the pattern of message transmissions among nodes. To hide payment receivers, we further propose to send redundant transactions to pseudo receivers to confuse adversaries. A fast algorithm with provable approximation ratio has been proposed to maximize the level of privacy protection under the constraint of communication overhead. Both experiments on a small-scale testbed and large-scale simulations are conducted to evaluate our proposal. The results show that our proposed solution outperforms existing work significantly.

The application of blockchain cryptocurrency in the field of energy transactions has attracted wide attention because it supports complex communication interactions of a large number of distributed energy entities. Due to the high degree of autonomy of distributed systems, it is very important to use trusted encryption technology to ensure the security of user information in the network. In order to avoid the problem of user privacy leakage in the Peer-to-Peer (P2P) energy trading scheme in the Industrial Internet of Things (IIOT), this paper adopts the signature scheme based on Elliptic Curve Cryptography-based Threshold Cryptography (ECC-TC) to complete the anonymous process of energy nodes and ensure the traceability of pseudonyms. In addition, in order to solve the problem of transaction restrictions caused by high transaction costs and long confirmation time of energy block chain, we proposed a payment scheme based on payment channel network (PCN) to support fast and frequent small energy transactions. We conducted security analysis and feasibility assessment in the context of security and privacy protection requirements and the conclusion proves that proposed scheme enables peer to communicate anonymously in a P2P manner and quickly complete small energy transactions while using blockchain technology to protect basic transactions. In addition, the cost of communication and calculation of the scheme is much less than that of traditional transaction mode which proves that proposed scheme can be applied in practice.KeywordsIndustrial Internet of ThingsSecure energy tradingBlockchainPayment channel networkThreshold signature scheme