The data from decentralized finance services is openly available once they operate in public blockchains. Although data encryption techniques for transaction exist, they are challenging, increase costs and decrease trust. Therefore, everyone can use the DeFi data. Natively, the data is stored as a transaction log, where we have a byte code of contracts and history of their method calls with parameters. So the problem is to represent it conveniently for analysis. In the paper, we consider a decentralized exchange called UniSwap, overview its operation principles, create a database with the related data and share scripts with the elementary examples. The results help overcome the entering threshold for further data analysis.
In recent years, there has been an increasing interest in incorporating blockchain for the Internet of Things (IoT) to address the inherent issues of IoT, such as single point of failure and data silos. However, blockchain alone cannot ascertain the authenticity and veracity of the data coming from IoT devices. The append-only nature of blockchain exacerbates this issue, as it would not be possible to alter the data once recorded on-chain. Trust and Reputation Management (TRM) is an effective approach to overcome the aforementioned trust issues. However, designing TRM frameworks for blockchain-enabled IoT applications is a non-trivial task, as each application has its unique trust challenges with their unique features and requirements. In this paper, we present our experiences in designing TRM framework for various blockchain-enabled IoT applications to provide insights and highlight open research challenges for future opportunities.
Internet of Things (IoT) is a network of smart devices that can communicate with each other without or with little human interaction. Maintaining security and trust among these millions of smart devices is a big concern because the transportation of their information generally takes place over the Internet. Limited resources available in IoT devices makes it more difficult to apply conventional security protocols. Moreover, IoT devices are generally located in such remote areas where unethical means can easily not only access them and inject false data but also completely replace them. This physical access can make other devices vulnerable to different attacks, so trust among these IoT devices is a critical factor. Trust management can be considered an important factor for a successful IoT system in which smart devices can communicate with one other without worry of security and integrity of data. Trust management is the process of identifying malicious and unwanted nodes or devices and removing them from any communication process. Key parameters of trust management in IoT systems are authentication, authorization/access control, integrity, privacy, and adaptability that depend on some direct measurable and non-measurable factors. However, despite numerous security solutions in IoT systems, there are some attacks specially designed by unethical means to manipulate the trust values in trust management systems. These attacks need to be addressed for the proper functioning of trust management systems in the IoT. Blockchain, which is mainly known for cryptocurrencies such as Bitcoin and Ethereum, has proven its effectiveness in data immutability, integrity, and decentralized ledgers and can be a perfect solution for many security and trust-related problems of the IoT. Additionally, advancement in blockchain technology can improve its applicability in securing and managing trust in the IoT. For instance, smart contracts that enable programmability in blockchain can make processing of data conditional and automated. Security features of blockchain, such as authentication, integrity, access control, etc., can be used for managing trust among IoT devices by protecting them from security attacks. Initially, blockchain was designed to be public in nature, where anyone can join and send transactions, and the same data are transparently distributed among all the participants. But in real-world scenarios, we need more control over accessing services. Permissioned blockchain such as Hyperledger Fabric, which is specially designed for business needs can provide more control over the functioning of available services. In Hyperledger Fabric, data are distributed among authorized entities only and all activities are controlled by the admin entity. For authentication, every entity in Hyperledger Fabric has a unique identity provided by some Certification Authority (CA) using X.509 protocols. It also supports smart contracts or chaincodes that provide more control over invoking transactions in its network. This chapter will introduce trust management in IoT systems with its issues and all possible trust-related security attacks on it. It will also discuss important trust parameters that need to be addressed for a successful trust management system. After it, an introduction to blockchain technology with its supported protocols will be explained in this chapter. The evolution of blockchain, its various variants, and applications will also be discussed in the book chapter. The chapter will mainly focus on Hyperledger Fabric, which is a permissioned blockchain, and will define its architecture, security features, and working mechanisms. The chapter will also explain blockchain and IoT integration issues in detail and then expose their solutions with multiple strategies such as the Inter IoT model, IoT blockchain, and the cloud-based IoT blockchain model. Finally, the chapter will describe six important trust management issues in IoT such as “Trust in Authentication,” “Trust in Identity Management,” “Trust in Integrity of Data,” “Trust in Authorization,” “Trust in Interoperabilty,” and “Trust in Privacy.” Thereafter, the chapter will expose their possible solutions using Hyperledger Fabric Blockchain. These solutions will be useful for managing trust in IoT scenarios, as well as for industrial IoT, blockchain, and IoT enthusiasts, students, Ph.D. scholars, and researchers.
Identity management is the process of setting and organizing the roles and access privileges of a user’s identity. The current identity management system is centralized and is controlled by a single entity. Users’ privacy concerns are not in their best interest. Users have very little to no control over their data. The centralized system becomes a single point of failure which is prone to attack that leads to users losing their data privacy if these centralized systems are breached. Therefore we propose a Blockchain-based decentralized Identity Management System that makes use of self-sovereign identity, decentralized identifiers, and verifiable credentials. It also gives users the ability to choose from a very large number of identity providers instead of just a select few corporations. The main advantages of the proposed solution include the elimination of the need for a central authority for identity verification and identity data management, the reduction of time spent on identity verification, the ability to share data with permission, and the ability to verify the origin of the data while sharing.
Stefano Marzo, Royston Pinto, Lucy McKenna, Rob Brennan
Federated learning (FL) is a distributed machine learning<br> approach that enables remote devices i.e. workers to collaborate to compute<br> the fitting of a neural network model without sharing their data.<br> While this method is favorable to ensure data privacy, an imbalanced<br> data distribution can introduce unfairness in the model training, causing<br> discriminatory bias towards certain under-represented groups. In this paper,<br> we show that imbalance federated data decreases indexes of equity<br> i.e. differences in treatment for underrepresented classes. To address the<br> problem, we propose a federated learning framework called Z-Fed that 1)<br> balances the training without exchange of privacy protected data using<br> a zero knowledge proof (ZKP) technique, and 2) allows for the collection<br> of information on data distributions based on one or more categorical<br> features to produce metadata about population proportions. The proposed<br> framework infers the precise data distribution without exchanging<br> knowledge of the data categories and uses it to coordinate a balanced<br> training set. Z-Fed aims to mitigate the effect of imbalanced data in<br> FL while respecting privacy and without using mediators or probabilistic<br> approaches. Compared to a non-balanced framework, Z-Fed improves<br> fairness and equality measured in equal opportunities (EPD) by 53.54%,<br> equal odds (EOD) by 56.41%, and statistical parity (SPD) by 46.1% on<br> imbalanced UTK datasets, reducing biased predictions among subgroups.<br> EPD, EOD, and SPD measure the disparity of treatment between privileged<br> e.g. over-represented and non-privileged groups. Given the results<br> obtained, Z-Fed can reduce discriminatory behaviors and enhance trustworthy<br> of federated learning.
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Privacy-Preserving Technologies in Data
Imbalanced Data Classification Techniques
Artificial Intelligence in Healthcare and Education
Paulo Valente Klaine, Hao Xu, Lei Zhang, Muhammad Ali Imran · 5 authors
Recent data leak scandals, together with the under-utilization of collected data (estimated that around 90% of data never leaves a device’s local storage), limits the applicability and potential of novel data driven applications. Thus, novel ways to treat data, in which users are guaranteed control, usability, and privacy over their generated data are needed. In this paper we propose a novel privacy-preserving blockchain framework for a data sharing marketplace. The proposed framework allows users (such as sensors and devices) that generate data to store it in external servers, while the blockchain is utilized to record buy and sell transactions between parties, as well as perform access control by generating access sequences whenever trades are performed. A novel perspective over data ownership is presented, in which whoever generates the data has completed ownership and control over it and the blockchain transactions are only utilized to guarantee temporary access to it. The proposed blockchain framework also supports different types of data and provides, via the distributed and openness of the framework, quality, timeliness and similarity control over the data stored in the marketplace. In this context, different types of applications that can benefit from this framework are presented and open problems are discussed.
This paper presents a new method for quantum identity authentication (QIA) protocols. The logic of classical zero-knowledge proofs (ZKPs) due to Schnorr is applied in quantum circuits and algorithms. This novel approach gives an exact way with which a prover $P$ can prove they know some secret by encapsulating it in a quantum state before sending to a verifier $V$ by means of a quantum channel - allowing for a ZKP wherein an eavesdropper or manipulation can be detected with a fail-safe design. This is achieved by moving away from the hardness of the Discrete Logarithm Problem towards the hardness of estimating quantum states. This paper presents a method with which this can be achieved and some bounds for the security of the protocol provided. With the anticipated advent of a `quantum internet', such protocols and ideas may soon have utility and execution in the real world.
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Physical Unclonable Functions (PUFs) and Hardware Security
Current consensus protocols for permissionless blockchain cannot balance security, performance and centralization issues. In the paper, we present a reputation based consensus, FPoR, which combines reputation, committee based consensus, PBFT, reward and penalization mechanisms. FPoR can balance scalability, security and decentralization, and promote fairness, increase participation and strengthen security. Experiment results show that FPoR is with high performance and scalability, which can be used for permissionless blockchain. FPoR can also be extended to permissioned blockchain applications.
An identity management system (IDMS) manages and organizes identities and credentials information exchanged between users, identity providers (IDPs), and service providers (SPs) to ensure confidentiality and enhance privacy of users’ personal data. Traditional or centralized IDMS rely on a third party to store a user’s personal information, authenticate the user, and organize the entire process. This clearly constitutes threats to the privacy of the user, in addition to other issues, such as single point of failure (SPOF), user tracking, and data availability issues. Blockchain technology has many useful features that can contribute to solving traditional IDMS issues, such as decentralization, immutability, and anonymity. Blockchain represents an attractive solution for many issues related to traditional IDMS, including privacy, third-party control, data leakage, and SPOF, supported by Distributed Ledger Technology (DLT) security features and powerful smart contracts technology. The current study presents a systematic literature review and analysis for recently proposed solutions that adopt the traditional centralized approach, as well as solutions based on blockchain technology. The study also aims to provide a deep understanding of proposed IDMS solutions and best practices, and highlight the research gaps and open issues related to IDMSs and users’ privacy. In particular, the current research focuses on analyzing the blockchain-based solutions and illustrating their strengths and weaknesses, as well as highlighting the promising blockchain technology framework that can be utilized to enhance privacy and solve security issues in a centralized IDMS. Such a study is an important step towards developing efficient solutions that address the pressing needs in the field.
The trade-off of secrecy is the difficulty of verification. This trade-off means that contracts must be kept private, yet their compliance needs to be verified, which we call the secrecy-verifiability paradox. However, the existing smart contracts are not designed to provide secrecy in this context without sacrificing verifiability. Without a trusted third party for notarization, the protocol for the verification of smart contracts has to be built on cryptographic primitives. We propose a blockchain-based solution that overcomes this challenge by storing the verifiable evidence as accessible data on a blockchain in an appropriate manner. This solution allows for cryptographic data verification but not revealing the data itself. In addition, with our proposal, it is possible to verify contracts whose form of existence has been destroyed as long as the contract is real and the people involved remember it.
The study aims to solve the problems in auditing ciphertext data, improve audit efficiency, and increase the security of audit data in the audit server. First, the existing encryption algorithms are analyzed. Second, the searchable encryption algorithm is proposed to audit the ciphertext data, and an audit server scheme is made based on blockchain technology (BT). Finally, the two schemes are compared with the traditional audit technology. The results show that the server's inspection efficiency of the searchable encryption algorithm is higher.
As a digital system that integrates cryptography, data management, networking, and incentive mechanisms to allow the verification, execution, and recording of transactions between parties, block chains are now firmly established. Block chain technologies have significant potential as a new basis for all types of transactions, even though its initial purpose was to support new kinds of digital currency enabling simpler and more secure payments. By using this technology as a platform to carry out "smart contracts" for transactions, particularly for high-value products, agribusiness stands to become a primary benefactor. Prior to further discussion, it is crucial to make a distinction between private digital currencies and the underlying distributed ledger and block chain technology. Since digital currencies like Bitcoin are dispersed and international in nature, central banks are unlikely to be able to effectively regulate their underlying protocols. Instead than being able to monitor and control the money itself, monetary authorities are more concerned with comprehending the "on-ramps" and "off-ramps" that make up the linkages to the conventional payments system. Contrary to the block chain's digital currency component, the distributed ledger feature has the potential to be widely used in agricultural and trade financing, particularly if processes involve several partners and there is no reliable central authority.
There is rising global demand for the deployment of a central bank digital currency (CBDC) system to achieve financial stability. However, striking a balance between privacy, transparency, and auditability in such a system is technically difficult. We propose a CBDC system based on a consortium blockchain that adopts a privacy-preserving, transparent unspent transaction output (UTXO) model. The proposed system satisfies the travel rule of payment, unlike existing cryptocurrencies. Unlike the conventional UTXO approach, users use wallet-linked addresses for transactions rather than their actual wallet addresses. Each transacting address is generated using two keys: a random private key computed by the sender and the recipient's public key. The final private key is known only to the recipient, and it is required to spend the UTXO received using the address. Thus, each user holds only a single authorized public key and address, which eases regulatory compliance in the network without compromising anonymity and privacy. To manage the blockchain, the central bank and several certificate authorities execute the energy-efficient Clique consensus algorithm. Only the central bank supplies money to the network. A prototype of the system was implemented using Python-Flask, and it outperformed the state-of-the-art systems by providing a smaller transaction size (665 B) and lower verification time (9 ms).
Maxime Buser, Rafael Dowsley, Muhammed F. Esgin, Clémentine Gritti · 12 authors
Blockchain technology provides efficient and secure solutions to various online activities by utilizing a wide range of cryptographic tools. In this article, we survey the existing literature on post-quantum secure digital signatures that possess exotic advanced features and that are crucial cryptographic tools used in the blockchain ecosystem for (1) account management, (2) consensus efficiency, (3) empowering scriptless blockchain, and (4) privacy. The exotic signatures that we particularly focus on in this work are the following: multi-/aggregate, threshold, adaptor, blind, and ring signatures. Herein the term ”exotic” refers to signatures with properties that are not just beyond the norm for signatures, e.g., unforgeability, but also imbue new forms of functionalities. Our treatment of such exotic signatures includes discussions on existing challenges and future research directions in the post-quantum space. We hope that this article will help to foster further research to make post-quantum cryptography more accessible so that blockchain systems can be made ready in advance of the approaching quantum threats.
Stefan More, Sebastian Ramacher, Lukas Alber, Marco Herzl
Authentication, authorization, and trust verification are central parts of an access control system. The conditions for granting access in such a system are collected in access policies. Since access conditions are often complex, dedicated languages -- policy languages -- for defining policies are in use. However, current policy languages are unable to express such conditions having privacy of users in mind. With privacy-preserving technologies, users are enabled to prove information to the access system without revealing it. In this work, we present a generic design for supporting privacy-preserving technologies in policy languages. Our design prevents unnecessary disclosure of sensitive information while still allowing the formulation of expressive rules for access control. For that we make use of zero-knowledge proofs (NIZKs). We demonstrate our design by applying it to the TPL policy language, while using SNARKs. Also, we evaluate the resulting ZK-TPL language and its associated toolchain. Our evaluation shows that for regular-sized credentials communication and verification overhead is negligible.
Zk-SNARK unleashes the great potential of ZKP (zero-knowledge proof) in the blockchain, distributed storage, etc. However, the proof-generation of zk-SNARK is excessively time intensive, making it a challenge to deploy a high-performance zk-SNARK in most real applications. As a result, NTT (Number Theoretic Transform), one of the most time-consuming parts in proof-generation, needs to be accelerated significantly. To address this issue, we propose a novel and efficient “data reordering” technique to enable a highly pipelined architecture, on which an FPGA-based hardware accelerator is designed to support the large-bitwidth and large-scale NTT tasks in zk-SNARK. Our architecture achieves a two-level pipeline: 1) the top-level pipeline is achieved among smaller NTT sub-tasks, which are decomposed from a large-scale NTT task; 2) the bottom-level pipeline is achieved in each sub-task, among butterfly operations with different step sizes. This architecture can effectively reduce the data dependency and memory access requirements, meanwhile, can be flexibly scaled to different scales of FPGAs. To balance computing efficiency and flexibility, the OpenCL equipped with HLS is used to implement the heterogeneous acceleration system. We prototype the accelerator on the AMD-Xilinx Alveo U50 card (UltraScale+ XCU50 FPGA). The evaluation results show that 1) our accelerator shows high scalability for different scales of FPGAs with a stable performance improvement; 2) it performs 1.95× faster than the one in PipeZK; 3) and it achieves 27.98×, 1.74× speedup and 6.9×, 6× energy efficiency improvement than AMD Ryzen 9 5900X single core and 12 cores respectively when integrated into the well-known ZKP open-source project, Bellman.
Due to the advantages in self-sovereignty identity management and scalability of blockchain, digital identity verification and management systems (DIVMS) of blockchain-based verifiable certificates (VC) are getting more and more attention. However, user privacy in the systems’ traditional architectures cannot be guaranteed. In this paper, the zero-knowledge succinct noninteractive arguments of knowledge (zkSNARKs) referred to as Groth16 are introduced in order to implement privacy protection of the user’s identity and behavior of DIVMS of blockchain-based VC. In the proposed architecture, the malleability attack of Groth16 is considered, and verifications of zero-knowledge proof (ZKP) and the digital signature of an identity provider (IDP) attached to VC and the status management of VC are implemented on the smart contracts of the blockchain to overcome single point failure. Furthermore, a prototype system is designed to verify the proposed architecture’s capability in privacy protection and to evaluate its performances in cost and throughput. Finally, the security of the proposed architecture is discussed, and its comparisons are conducted with those existing blockchain-based DIVMSs, especially those systems using Groth16 of zkSNARKs to improve the privacy of user. All results mentioned above have shown that the proposed system is efficient and safe, and it can improve the privacy of DIVMS of the blockchain based VC while avoiding single point failure.
With the drive to create a decentralized digital economy, Web 3.0 has become a cornerstone of digital transformation, developed on the basis of computing-force networking, distributed data storage, and blockchain. With the rapid realization of quantum devices, Web 3.0 is being developed in parallel with the deployment of quantum cloud computing and quantum Internet. In this regard, quantum computing first disrupts the original cryptographic systems that protect data security while reshaping modern cryptography with the advantages of quantum computing and communication. Therefore, in this paper, we introduce a quantum blockchain-driven Web 3.0 framework that provides information-theoretic security for decentralized data transferring and payment transactions. First, we present the framework of quantum blockchain-driven Web 3.0 with future-proof security during the transmission of data and transaction information. Next, we discuss the potential applications and challenges of implementing quantum blockchain in Web 3.0. Finally, we describe a use case for quantum non-fungible tokens (NFTs) and propose a quantum deep learning-based optimal auction for NFT trading to maximize the achievable revenue for sufficient liquidity in Web 3.0. In this way, the proposed framework can achieve proven security and sustainability for the next-generation decentralized digital society.
Rodrigo Dutra Garcia, Gowri Ramachandran, Raja Jurdak, Jó Ueyama
Real-world applications in healthcare and supply chain domains produce, exchange, and share data in a multi-stakeholder environment. Data owners want to control their data and privacy in such settings. On the other hand, data consumers demand methods to understand when, how, and who produced the data. These requirements necessitate data governance frameworks that guarantee data provenance, privacy protection, consent management, and selective disclosure. We introduce a decentralized data governance framework based on blockchain technology, proxy re-encryption, and Boneh, Boyen, and Shacham (BBS) signatures to let data owners control, selectively share and track their data through privacy-enhancing, consent management, and selective disclosure mechanisms. Besides, our framework allows the data consumers to understand data lineage through a blockchain-based provenance mechanism. We use Digital medical e-prescription as the use case since it handles sensitive data in a multi-stakeholder environment while showing how the medical community can manage patients’ sensitive prescription data, involving patients as data owners, and doctors, and pharmacists as data consumers. Our proof-of-concept implementation and evaluation results based on CosmWasm, Hyperledger Besu, Ethereum, pyUmbral PRE, and BBS signatures show that the proposed decentralized system is platform-agnostic, scalable and guarantees a higher degree of transparency, privacy, and trust with minimal overhead.
One of the key responsibilities of the Public Key Infrastructure is revocation management. Additionally, the security of any Public Key Infrastructure (PKI) depends on it. Today's revocation methods are susceptible to a single point of failure when network traffic rises due to the growth in the quantity and size of networks as well as the adoption of new paradigms like the Internet of Things and the use of the web. The author uses the strength and resiliency of blockchain to overcome these issues and present a productive decentralized certificate revocation management and status verification system. The author adds a field that specifies which distribution point the certificate will belong to in the event that it is revoked using the certificate structure extension field. Then, the author carries out a thorough assessment of our plan using performance indicators like execution time and data consumption to show that it can fulfill the demands with high effectiveness and little expense. Additionally, the author contrasts the effectiveness of our strategy with two of the most widely-used revocation approaches, namely the Certificate Revocation List and the Online Certificate Status Protocol. The data collected demonstrate that our suggested strategy works better than the existing scheme.
Lydia Negka, Angeliki Katsika, Γεώργιος Σπαθούλας, Vassilis P. Plagianakos
One of the major concerns regarding currently proposed public blockchain systems relates to the feasible transaction processing rate. It is common for such systems to limit this rate to maintain the required levels of security and decentralisation. State channels are an approach to overcome this limitation, as they aim to decrease the required on-chain transactions for a given application and thus indirectly increase the capacity (in terms of applications) of public blockchain systems. In the present paper, we propose a state channel design that, through the use of RSA accumulators, operates on a compact state structure. This scheme is optimal for applications whose state includes large sets of elements. The novel state channel design is presented by analysing all state channel operations and how they have to be revised. The security of the design is discussed, while a practical use case scenario regarding the use of the design for an on-chain asset (e.g., non-fungible tokens) exchange application is also analysed.
<abstract><p>With the continuous development of Internet of Things, finance, big data and many other fields, blockchain has been widely used in these areas for transactions, data sharing, product traceability and so on. Numerous assets have appeared in the blockchain, and there are some levels of conflicts among privacy protection of these assets, transaction transparency and auditability in blockchain; so how to provide privacy preserving, make public verifications and audit the encrypted assets are challenging problems. In this paper, we propose a privacy-preserving transaction scheme with public verification and reliable audit in blockchain. First, we provide privacy preserving of transaction contents based on homomorphic encryption. It is flexible, as we decouple user identity and transaction contents. Then, we propose and design a multiplicative zero-knowledge proof with formal security analysis. Furthermore, several verification rules are defined by us in the scheme, such as balance verification and multiplicative verification based on the proposed multiplicative zero-knowledge proof. Our scheme enables reliable and offline auditing for each transaction, and we aggregate the zero-knowledge proofs to save the ledger space. Finally, we make a security analysis of our proposal in terms of transaction confidentiality, public verification and audit reliability, and we give a performance analysis of the proposed scheme.</p></abstract>
Sarah Azouvi, Christian Cachin, Le, Duc V., Marko Vukolić · 5 authors
Blockchain protocols implement total-order broadcast in a permissionless setting, where processes can freely join and leave. In such a setting, to safeguard against Sybil attacks, correct processes rely on cryptographic proofs tied to a particular type of resource to make them eligible to order transactions. For example, in the case of Proof-of-Work (PoW), this resource is computation, and the proof is a solution to a computationally hard puzzle. Conversely, in Proof-of-Stake (PoS), the resource corresponds to the number of coins that every process in the system owns, and a secure lottery selects a process for participation proportionally to its coin holdings. Although many resource-based blockchain protocols are formally proven secure in the literature, the existing security proofs fail to demonstrate why particular types of resources cause the blockchain protocols to be vulnerable to distinct classes of attacks. For instance, PoS systems are more vulnerable to long-range attacks, where an adversary corrupts past processes to re-write the history, than Proof-of-Work and Proof-of-Storage systems. Proof-of-Storage-based and Proof-of-Stake-based protocols are both more susceptible to private double-spending attacks than Proof-of-Work-based protocols; in this case, an adversary mines its chain in secret without sharing its blocks with the rest of the processes until the end of the attack. In this paper, we formally characterize the properties of resources through an abstraction called resource allocator and give a framework for understanding longest-chain consensus protocols based on different underlying resources. In addition, we use this resource allocator to demonstrate security trade-offs between various resources focusing on well-known attacks (e.g., the long-range attack and nothing-at-stake attacks).
Consumers in electricity markets are becoming more proactive because of the rapid development of demand-response management and distributed energy resources, which boost the transformation of peer-to-peer (P2P) energy-trading mechanisms. However, in the P2P negotiation process, it is a challenging task to prevent private information from being attacked by malicious agents. In this paper, we propose a privacy-preserving, two-party, secure computation mechanism for consensus-based P2P energy trading. First, a novel P2P negotiation mechanism for energy trading is proposed based on the consensus + innovation (C + I) method and the power transfer distribution factor (PTDF), and this mechanism can simultaneously maximize social welfare and maintain physical network constraints. In addition, the C + I method only requires a minimum set of information to be exchanged. Then, we analyze the strategy of malicious neighboring agents colluding to attack in order to steal private information. To defend against this attack, we propose a two-party, secure computation mechanism in order to realize safe negotiation between each pair of prosumers based on Paillier homomorphic encryption (HE), a smart contract (SC), and zero-knowledge proof (ZKP). The energy price is updated in a safe way without leaking any private information. Finally, we simulate the functionality of the privacy-preserving mechanism in terms of convergence performance, computational efficiency, scalability, and SC operations.