House renting information management system and method

Abstract

According to the house leasing information management system and method provided by the invention, comprehensive, efficient and safe management of house leasing information is realized in combination with a special hardware system and terminal equipment. The system integrates a plurality of cooperative work modules such as block chain data storage, intelligent housing resource recommendation, dynamic credit evaluation, automatic contract management and privacy protection, and adopts advanced technologies such as a distributed account book, a deep neural network, a graph neural network and an intelligent contract. And data cannot be tampered, recommendation is personalized, credit evaluation is accurate, contract management is automatic, and user privacy is strictly protected. Meanwhile, the system is provided with hardware supports such as a high-performance computing and storage cluster, security encryption and privacy protection equipment and the like, and special terminal equipment provides convenient user interaction experience. According to the invention, transparency, efficiency and user experience of the house renting market can be significantly improved, renting risks are reduced, rights and interests of both renting parties are guaranteed, and healthy development of the house renting industry is promoted.

Description

Technical Field

[0001] The invention belongs to the field of information management, and specifically discloses a house rental information management system and method. Background Art

[0002] With the acceleration of urbanization and the increase in population mobility, the housing rental market is booming, but the traditional housing rental information management system faces multiple challenges, such as data storage is vulnerable to single point failure, lack of deep learning and personalized analysis in housing recommendation, reliance on manual review and lack of dynamics in credit assessment, error-prone contract management and complex process, and insufficient privacy protection and data security measures. Specifically, although the traditional data storage method is easy to manage, the data security and reliability are low, and it is vulnerable to attacks or failures that lead to data loss or leakage; the housing recommendation system mostly relies on simple keyword searches or rule-based recommendations, the recommendation results are not accurate enough, and the rental matching efficiency is low; the credit assessment process is cumbersome and time-consuming, the results are easily affected by subjective factors, and the monitoring and early warning capabilities of potential risks are insufficient; paper or simple electronic contracts lack intelligent and automated management, and human errors or malicious breaches are prone to occur during contract execution, and the change and breach handling process is complicated; at the same time, traditional data encryption and privacy protection measures are difficult to cope with complex network attacks and data leakage risks, user data is vulnerable to attacks during transmission and storage, and there is a lack of sound data protection policies and compliance management. To sum up, the existing housing rental information management system has obvious deficiencies in terms of efficiency, security and personalization. A new system is urgently needed to overcome these shortcomings and improve the overall efficiency and user experience of the rental market. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention proposes a house rental information management system and method.

[0004] The present invention includes the following technical solutions:

[0005] A house rental information management system, which integrates the following multiple collaborative modules:

[0006] 1) Blockchain data storage module:

[0007] Distributed ledger technology is combined with hash chain to build a tamper-proof data storage structure; each data transaction is automatically verified and recorded through the Ethereum smart contract Smart Contract, and the ring signature technology is used to protect transaction privacy and prevent information leakage; the blockchain consensus algorithm is integrated, including proof of work PoW, proof of stake PoS or delegated proof of stake DPoS, so as to ensure the consistency and synchronization of data among nodes in the whole network and improve the overall stability of the system;

[0008] 2) Intelligent housing recommendation and optimization module:

[0009] Integrate deep neural network DNN and attention mechanism to conduct in-depth learning and analysis of tenants' historical behaviors, preferences, geographic locations and market trends; apply a hybrid recommendation algorithm that combines collaborative filtering with content-based recommendation to provide tenants with personalized and accurate housing recommendations based on their personal needs and market dynamics; use reinforcement learning algorithm to continuously optimize recommendation strategies based on user feedback and market changes, and improve rental matching efficiency and user satisfaction;

[0010] 3) Dynamic credit assessment and risk management module:

[0011] Using graph neural network (GNN) and social network analysis technology, we can mine the interaction and evaluation information between tenants and landlords and build a credit evaluation system. We can combine the transaction data on the blockchain and apply Bayesian Network to conduct dynamic credit evaluation to improve the accuracy and reliability of the evaluation and reduce the rental risk. We can integrate risk prediction models, including models based on Random Forest or Gradient Boosting Tree, to monitor and warn potential risks in real time and provide decision support for both parties to the lease.

[0012] 4) Automated contract management and execution module:

[0013] Design a smart contract template library containing complex conditional logic, covering rent payment, contract changes, and breach of contract processing, to achieve automated contract management and execution; apply formal verification technology to verify the logic of smart contracts to improve the correctness and security of contracts; integrate event-driven architecture Event-Driven Architecture and microservices technology to achieve efficient collaboration and flexible expansion of contract processes;

[0014] 5) Privacy protection and data security module:

[0015] Homomorphic Encryption and Differential Privacy technologies are used to improve the security of user data during processing and storage, and prevent data leakage and abuse. Zero-Knowledge Proof and Secure Multi-Party Computation technologies are used to verify and share data, while protecting user privacy and improving the legality and compliance of data use. Relevant laws and regulations are strictly observed, and international standards such as GDPR are combined to formulate a complete data protection policy to improve the legality and compliance of user data processing.

[0016] The invention also discloses a housing rental information management method, which applies the above system.

[0017] 8. The housing rental information management method according to claim 7, characterized in that it comprises the following steps:

[0018] S1 uses blockchain data storage modules for data storage and verification: it uses a combination of distributed ledger technology and hash chains to build an unalterable data storage structure for storing all transactions and data related to house rentals; it uses Ethereum smart contracts to automatically verify and record each data transaction to improve the authenticity and integrity of the data; it uses ring signature technology to protect transaction privacy and prevent information leakage; it uses blockchain consensus algorithms to improve the consistency and synchronization of data among nodes in the entire network, thereby improving the overall stability of the system;

[0019] S2 provides personalized housing recommendations through the intelligent housing recommendation and optimization module: integrating deep neural networks and attention mechanisms to conduct in-depth learning and analysis of tenants' historical behaviors, preferences, geographic locations, and market trends; applying a hybrid recommendation algorithm that combines collaborative filtering with content-based recommendations to generate personalized and accurate housing recommendation lists based on tenants' personal needs and market dynamics; using reinforcement learning algorithms to continuously optimize recommendation strategies based on user feedback and market changes, thereby improving rental matching efficiency and user satisfaction;

[0020] S3 uses dynamic credit assessment and risk management modules to conduct credit assessment and risk warning: using graph neural network and social network analysis technology to mine the interaction relationship and evaluation information between tenants and landlords, and build a credit assessment system; combining transaction data on the blockchain, applying Bayesian networks to conduct dynamic credit assessment to improve the accuracy and reliability of the assessment; integrating risk prediction models to conduct real-time monitoring and early warning of potential risks, and providing decision support for both parties to the lease;

[0021] S4 realizes automated contract management through automated contract management and execution modules: design and use smart contract template libraries containing complex conditional logic, covering key links such as rent payment, contract changes, and breach of contract processing; apply formal verification technology to verify the logic of smart contracts to improve the correctness and security of contracts; integrate event-driven architecture and microservice technology to achieve efficient collaboration and flexible expansion of contract processes, and improve automated contract management and execution;

[0022] The S5 application privacy protection and data security module ensures the security of user data: it uses homomorphic encryption and differential privacy technologies to improve the security of user data during processing and storage, and prevent data leakage and abuse; it uses zero-knowledge proof and secure multi-party computing technologies to achieve data verification and sharing while protecting user privacy; it complies with relevant laws and regulations, and in combination with the international standard GDPR, formulates and implements a comprehensive data protection policy to achieve the legality and compliance of user data processing.

[0023] The present invention also discloses a hardware system for house rental information management, the system comprising:

[0024] aHigh-performance computing and storage cluster:

[0025] a1 is equipped with high-performance servers for running deep learning models, graph neural network algorithms, and blockchain nodes to achieve efficient data processing and secure storage;

[0026] The a2 server cluster adopts a distributed storage architecture and combines high-speed network interconnection technology to achieve high data availability and scalability;

[0027] a3 integrates GPU accelerator cards or dedicated AI processors to accelerate the calculation of deep neural networks and reinforcement learning algorithms, improving the real-time and accuracy of house recommendations and credit assessments;

[0028] bSecure encryption and privacy protection equipment:

[0029] b1 is equipped with hardware-level encryption devices, including hardware security modules (HSMs) or encryption cards, which are used to implement advanced encryption algorithms such as homomorphic encryption and differential privacy to ensure the security of user data during transmission and storage.

[0030] b2 integrates dedicated hardware for zero-knowledge proof and secure multi-party computing, supporting efficient data verification and sharing while protecting user privacy;

[0031] b3 is equipped with physical security facilities, including firewalls, intrusion detection systems (IDS) and security audit systems, to build a multi-level security protection system to prevent data leakage and illegal access.

[0032] The present invention also discloses a dedicated terminal device for a house rental information management system, the device comprising:

[0033] aSmart contract execution and verification module:

[0034] a1 has a built-in smart contract execution engine that supports smart contract execution on Ethereum or other blockchain platforms, ensuring the automated execution and verification of contract terms;

[0035] a2 integrates formal verification tools to perform static analysis and dynamic testing on smart contracts to improve the correctness and security of contracts;

[0036] a3 is equipped with a secure encrypted communication module for secure data exchange with the blockchain network and other system components;

[0037] bUser interface and interactive equipment:

[0038] b1 is equipped with a high-resolution touch screen or virtual reality VR device, providing users with an intuitive and easy-to-use interface for browsing and selecting properties;

[0039] b2 integrates speech recognition and speech synthesis technology, supports voice interaction, and facilitates users to query properties and sign contracts through voice commands;

[0040] b3 has built-in identity authentication modules, including but not limited to fingerprint recognition, facial recognition or QR code scanning, to enhance the authenticity and security of user identity;

[0041] b4 is equipped with a mobile payment module that supports multiple payment methods, including but not limited to Alipay, WeChat Pay or blockchain wallets, enabling convenient payment and management of rent.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The house rental information management system and method provided by the present invention realizes the safe and reliable data storage, the personalized and accurate house recommendation, the dynamic and comprehensive credit assessment, the automated and efficient contract management, and the strict compliance of privacy protection by integrating advanced technologies such as blockchain, deep learning, and graph neural network. The system not only improves the overall efficiency and user experience of the rental market, but also significantly reduces the rental risk and data leakage risk. The introduction of high-performance computing and storage clusters and secure encryption devices further guarantees the operating performance of the system and the security of user data. The design of dedicated terminal equipment, from the user's perspective, provides an intuitive and easy-to-use interactive interface and a convenient payment method, which greatly improves the user's convenience and satisfaction. In summary, the present invention brings a new solution to the house rental industry, which not only meets the high efficiency, safety and personalized needs of the modern rental market, but also lays a solid foundation for the digital transformation and sustainable development of the industry, and has significant social and economic benefits and broad application prospects. DETAILED DESCRIPTION

[0044] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] Example 1

[0046] An application of a housing rental information management system based on blockchain.

[0047] 1. System Overview

[0048] This embodiment provides a housing rental information management system based on blockchain technology. The system integrates multiple modules such as blockchain data storage, intelligent housing recommendation and optimization, dynamic credit assessment and risk management, automated contract management and execution, privacy protection and data security, etc., aiming to improve the efficiency, transparency and security of the housing rental market.

[0049] 2. System Modules and Implementation Details

[0050] 1Blockchain data storage module

[0051] 1.1 Combination of distributed ledger and hash chain: The system uses distributed ledger technology to ensure redundant backup of data among multiple nodes, improving data reliability and availability. At the same time, combined with hash chain technology, a unique hash value is generated for each piece of data, forming an unalterable data chain.

[0052] 1.2 Ethereum smart contract and ring signature technology: All data transactions are automatically verified and recorded through the smart contract of the Ethereum platform to ensure the transparency and fairness of the transaction. Ring signature technology is used to encrypt sensitive information in the transaction to protect the privacy of tenants and landlords.

[0053] 1.3 Blockchain consensus algorithm integration: The system flexibly selects consensus algorithms such as Proof of Work (PoW), Proof of Stake (PoS) or Delegated Proof of Stake (DPoS) according to the network environment and application requirements to ensure the consistency and synchronization of data among nodes in the entire network.

[0054] 2. Intelligent housing recommendation and optimization module

[0055] 2.1 Deep Neural Network and Attention Mechanism: The system uses deep neural network (DNN) to conduct in-depth learning and analysis of tenants’ historical behaviors, preferences, geographic locations, and market trends to extract data features. At the same time, the attention mechanism is introduced to improve the accuracy of recommendations.

[0056] 2.2 Hybrid recommendation algorithm: Combine collaborative filtering and content-based recommendation algorithms to provide tenants with personalized and accurate housing recommendations. By continuously optimizing algorithm parameters, the diversity and novelty of recommendation results can be improved.

[0057] 2.3 Reinforcement learning optimization: The system uses reinforcement learning algorithms to dynamically adjust recommendation strategies based on user feedback and market changes, thereby achieving self-learning and self-optimization of the recommendation system.

[0058] 3Dynamic credit assessment and risk management module

[0059] 3.1 Graph Neural Network and Social Network Analysis: Use Graph Neural Network (GNN) to deeply mine the interaction relationship and evaluation information between tenants and landlords and build a credit network. Combined with social network analysis technology, reveal the social connection and trust relationship between tenants and landlords.

[0060] 3.2 Bayesian network dynamic credit assessment: Combined with the transaction data on the blockchain, the Bayesian network is applied to perform dynamic credit assessment to improve the accuracy and reliability of the assessment.

[0061] 3.3 Risk prediction and monitoring: Integrate risk prediction models based on random forests or gradient boosting trees to conduct real-time monitoring and early warning of potential risks, and provide decision support for both parties to the lease.

[0062] 4Automated contract management and execution module

[0063] 4.1 Smart contract template library: Design a smart contract template library containing complex conditional logic, covering scenarios such as rent payment, contract changes, and breach of contract handling. Through template-based approach, the difficulty and cost of writing smart contracts are reduced.

[0064] 4.2 Formal verification improves contract security: Formal verification technology is used to perform rigorous mathematical proof and verification on the logic of smart contracts to ensure the correctness and security of the contract.

[0065] 4.3 Event-driven architecture and microservice technology: Integrate event-driven architecture and microservice technology to achieve efficient collaboration and flexible expansion of contract processes. Improve the scalability and maintainability of the system by decoupling service dependencies.

[0066] 5Privacy protection and data security module

[0067] 5.1 Homomorphic encryption and differential privacy technology: Homomorphic encryption technology is used to improve the security of data processing and storage. Differential privacy technology is used to desensitize sensitive data to prevent data leakage and abuse.

[0068] 5.2 Zero-knowledge proof and secure multi-party computing technology: Use zero-knowledge proof technology to verify and share data while protecting user privacy. Secure multi-party computing technology allows multiple parties to perform collaborative computing and analysis without decrypting data.

[0069] 5.3 Compliance with laws, regulations and international standards: Strictly comply with relevant laws, regulations and international standards such as GDPR, formulate a comprehensive data protection policy, strengthen data security management, user authority control, data auditing and monitoring measures, and ensure the legality and compliance of user data processing.

[0070] Practical application effect: The system has been put into practical use in a certain city and has achieved remarkable results. Tenants can quickly find housing that meets their needs, and landlords can manage their properties more efficiently. At the same time, the credit assessment and risk management functions of the system effectively reduce rental risks and improve the transparency and security of the rental market. The automated contract management and execution module greatly simplifies the contract process and improves the efficiency and accuracy of contract management. The privacy protection and data security module ensures the security and privacy of user data and enhances users' trust in the system.

[0071] Example 2

[0072] A hardware system designed specifically for house rental information management

[0073] 1. System Overview

[0074] This embodiment provides a hardware system designed specifically for house rental information management, which integrates high-performance computing and storage clusters as well as security encryption and privacy protection equipment, aiming to achieve efficient data processing, secure storage and comprehensive protection of user privacy.

[0075] 2. System composition and implementation details

[0076] 1. High-performance computing and storage cluster

[0077] a1 high performance server configuration:

[0078] The system deploys multiple high-performance servers equipped with powerful CPU and memory resources, which are specially used to run deep learning models, graph neural network algorithms and blockchain nodes. This configuration ensures the efficiency of data processing and the security of storage, especially when processing large-scale data and complex algorithms, it can maintain stable performance.

[0079] a2 distributed storage architecture:

[0080] The server cluster adopts a distributed storage architecture, combined with high-speed network interconnection technology (such as 10Gbps Ethernet or InfiniBand), to achieve high data availability and scalability. This architecture not only improves the data reading and writing speed, but also ensures redundant backup of data among multiple nodes, reducing the risk of data loss.

[0081] a3 GPU accelerator card and AI processor:

[0082] The cluster integrates GPU accelerator cards or dedicated AI processors (such as NVIDIA's Tesla series or Google's TPU), which are specially designed to accelerate the calculation of deep neural networks and reinforcement learning algorithms. By utilizing the parallel processing capabilities of these hardware, the system can significantly improve the real-time and accuracy of house recommendations and credit assessments.

[0083] 2. Security encryption and privacy protection equipment

[0084] b1 Hardware-level encryption device:

[0085] The system deploys hardware security modules (HSM) or encryption cards, which support advanced encryption algorithms such as homomorphic encryption and differential privacy. Through hardware-level encryption processing, the security of user data during transmission and storage is ensured, and even if the data is stolen, it cannot be easily decrypted.

[0086] b2 Zero-Knowledge Proof and Secure Multi-Party Computing Hardware:

[0087] The system integrates dedicated hardware that supports zero-knowledge proof and secure multi-party computing. This hardware can efficiently verify and share data while protecting user privacy. For example, through zero-knowledge proof technology, the system can verify the authenticity and integrity of data without revealing specific user data; while secure multi-party computing technology allows multiple participants to perform collaborative calculations and analysis without decrypting the data.

[0088] b3 Physical security facilities:

[0089] The system is equipped with complete physical security facilities, including firewalls, intrusion detection systems (IDS) and security audit systems. Firewalls are used to isolate internal networks from external networks to prevent unauthorized access; IDS can monitor abnormal behaviors in the network in real time, promptly detect and prevent potential attacks; and the security audit system records all access and operation behaviors to provide a basis for subsequent security analysis and tracing. These facilities together build a multi-level security protection system to effectively prevent data leakage and illegal access.

[0090] Practical application effect: The hardware system has been put into practical use in a large housing rental platform and has achieved remarkable results. The deployment of high-performance computing and storage clusters has greatly improved the efficiency of data processing and storage, enabling the platform to quickly respond to user query requests and provide accurate housing recommendations and credit assessment services. At the same time, the integration of security encryption and privacy protection devices ensures the security and privacy of user data and enhances user trust in the platform. The provision of physical security facilities effectively prevents the risk of data leakage and illegal access, providing a strong guarantee for the stable operation of the platform.

[0091] Example 3

[0092] A special terminal device for house rental information management system

[0093] 1. Equipment Overview

[0094] This embodiment introduces a special terminal device designed for a house rental information management system. The device integrates a smart contract execution and verification module as well as a user interface and interactive equipment, aiming to provide an efficient, safe, and convenient house rental service experience. By combining blockchain technology, smart contracts, advanced user interfaces, and multiple payment methods, the device can meet the high requirements of the modern rental market for efficiency, security, and ease of use.

[0095] 2. Equipment composition and implementation details

[0096] 1. Smart contract execution and verification module

[0097] a1 Smart Contract Execution Engine:

[0098] The device has a built-in smart contract execution engine that is compatible with Ethereum or other mainstream blockchain platforms. This allows users to directly execute and verify blockchain-based smart contracts on the device, ensuring the automated execution of contract terms and reducing human intervention and disputes. For example, when a lease expires or rent is paid, the smart contract can automatically execute the corresponding actions.

[0099] a2 Formal Verification Tool:

[0100] The device integrates formal verification tools for static analysis and dynamic testing of smart contracts. This helps to find potential logic errors and security vulnerabilities before the contract is deployed, improving the correctness and security of the contract. By simulating the contract execution process, it can be verified whether the contract behaves as expected in various situations.

[0101] a3 secure encrypted communication module:

[0102] The device is equipped with an advanced encrypted communication module and uses security protocols such as TLS / SSL to ensure that data exchange with the blockchain network and other system components is encrypted and secure. This prevents data from being stolen or tampered with during transmission, protecting user privacy and transaction security.

[0103] 2. User interface and interactive devices

[0104] b1 High-resolution touch screen or virtual reality VR device:

[0105] The device is equipped with a high-resolution touch screen or virtual reality VR device, providing users with an intuitive and easy-to-use interface for browsing and selecting properties. Users can intuitively view the detailed information, location, pictures and videos of the property through touch or VR devices to enhance the browsing experience.

[0106] b2 speech recognition and speech synthesis technology:

[0107] The device integrates advanced speech recognition and speech synthesis technology and supports voice interaction. Users can use voice commands to search for properties, filter conditions, view detailed information and even sign contracts. This greatly facilitates users, especially those who are not used to using touch screens or keyboards.

[0108] b3 Authentication Module:

[0109] The device has built-in authentication methods, including but not limited to fingerprint recognition, facial recognition or QR code scanning. These methods enhance the authenticity and security of user identities and prevent unauthorized access and fraud. When signing a contract or making a payment, users need to confirm their identity through authentication.

[0110] b4 mobile payment module:

[0111] The device is equipped with a mobile payment module that supports multiple payment methods, including Alipay, WeChat Pay, and blockchain wallets. This enables convenient payment and management of rent, and users can choose the payment method that best suits them. At the same time, the device also provides payment history and bill query functions, allowing users to view and manage their payment status at any time.

[0112] Practical application effect: This dedicated terminal device has been put into practical use in a large housing rental company and has achieved remarkable results. The introduction of the smart contract execution and verification module has greatly improved the efficiency and accuracy of contract execution and reduced disputes and human errors. The optimization of the user interface and interactive devices has improved the user experience, making the house query, selection and payment process more convenient and intuitive. The integration of the identity authentication module has enhanced the security of the system and protected the privacy and property safety of users. The diversified payment methods of the mobile payment module meet the needs of different users and improve the convenience and flexibility of payment.

[0113] The above are limited to several preferred embodiments of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A house rental information management system, characterized in that: The system integrates the following modules that work together: 1) Blockchain data storage module: Distributed ledger technology is combined with hash chain to build a tamper-proof data storage structure; each data transaction is automatically verified and recorded through the Ethereum smart contract Smart Contract, and the ring signature technology is used to protect transaction privacy and prevent information leakage; the blockchain consensus algorithm is integrated, including proof of work PoW, proof of stake PoS or delegated proof of stake DPoS, so as to ensure the consistency and synchronization of data among nodes in the whole network and improve the overall stability of the system; 2) Intelligent housing recommendation and optimization module: Integrate deep neural network DNN and attention mechanism to conduct in-depth learning and analysis of tenants' historical behaviors, preferences, geographic locations and market trends; apply a hybrid recommendation algorithm that combines collaborative filtering with content-based recommendation to provide tenants with personalized and accurate housing recommendations based on their personal needs and market dynamics; use reinforcement learning algorithm to continuously optimize recommendation strategies based on user feedback and market changes, and improve rental matching efficiency and user satisfaction; 3) Dynamic credit assessment and risk management module: Using graph neural network (GNN) and social network analysis technology, we can mine the interaction and evaluation information between tenants and landlords and build a credit evaluation system. We can combine the transaction data on the blockchain and apply Bayesian Network to perform dynamic credit evaluation to improve the accuracy and reliability of the evaluation and reduce the rental risk. We can integrate risk prediction models, including models based on Random Forest or Gradient Boosting Tree, to monitor and warn potential risks in real time and provide decision support for both parties to the lease. 4) Automated contract management and execution module: Design a smart contract template library containing complex conditional logic, covering rent payment, contract changes, and breach of contract processing, to achieve automated contract management and execution; apply formal verification technology to verify the logic of smart contracts to improve the correctness and security of contracts; integrate event-driven architecture and microservices technology to achieve efficient collaboration and flexible expansion of contract processes; 5) Privacy protection and data security module: Homomorphic Encryption and Differential Privacy technologies are used to improve the security of user data during processing and storage, and prevent data leakage and abuse. Zero-Knowledge Proof and Secure Multi-Party Computation technologies are used to verify and share data, while protecting user privacy and improving the legality and compliance of data use. Relevant laws and regulations are strictly observed, and international standards such as GDPR are combined to formulate a complete data protection policy to improve the legality and compliance of user data processing.

2. A house rental information management system according to claim 1, characterized in that: In the module 1): Combination of distributed ledger and hash chain: Distributed ledger technology is used to improve the distributed storage and redundant backup of data. It is also combined with hash chain technology to generate a unique hash value for each piece of data to form a data chain. Any tampering with the data will cause the hash value to change. Ethereum smart contract and ring signature technology: Each data transaction is automatically verified and recorded through the smart contract of the Ethereum platform, which improves the transparency and fairness of the transaction. At the same time, the ring signature technology is used to encrypt sensitive information in the transaction, protect transaction privacy, and prevent information leakage to unauthorized third parties; Blockchain consensus algorithm integration: The system integrates a variety of blockchain consensus algorithms, including Proof of Work (PoW), Proof of Stake (PoS) and Delegated Proof of Stake (DPoS). According to the network environment and application requirements, the most suitable consensus mechanism is selected to achieve consistency and synchronization of data among nodes in the entire network, thereby improving the overall stability and response speed of the system.

3. A house rental information management system according to claim 1, characterized in that: In the module 2): Deep neural network and attention mechanism: Deep neural network (DNN) is used to conduct in-depth learning and analysis of tenants’ historical behaviors, preferences, geographic locations, and market trends, extracting features and patterns hidden in the data. At the same time, the attention mechanism is introduced to enable the model to pay more attention to information that has an important impact on the recommendation results, thereby improving the accuracy of recommendations. Hybrid recommendation algorithm: Combining collaborative filtering and content-based recommendation algorithms, it fully utilizes tenants’ historical behavior data and property information to provide tenants with personalized and accurate property recommendations. By continuously optimizing algorithm parameters and model structure, it improves the diversity and novelty of recommendation results. Reinforcement learning optimization: Using reinforcement learning algorithms, we dynamically adjust recommendation strategies based on user feedback and market changes to achieve self-learning and self-optimization of the recommendation system. Through continuous trial and error and iteration, we find the optimal recommendation solution to improve rental matching efficiency and user satisfaction.

4. A house rental information management system according to claim 1, characterized in that: In the module 3): Graph neural network and social network analysis: Use graph neural network GNN to deeply mine the interaction relationship and evaluation information between tenants and landlords, build a complex credit network, and combine social network analysis technology to reveal the social connection and trust relationship between tenants and landlords, providing support for credit assessment; Bayesian network dynamic credit assessment: Combined with the transaction data on the blockchain, the Bayesian network is used for dynamic credit assessment, taking into account a variety of factors and influences to improve the accuracy and reliability of the assessment; the assessment model is continuously updated and revised to reflect changes in the credit status of tenants and landlords; Risk prediction and monitoring: Integrate risk prediction models based on Random Forest or Gradient Boosting Tree to conduct real-time monitoring and early warning of potential risks; By analyzing historical and real-time data, risk signals and trends can be identified to provide decision support for both parties of the lease.

5. A house rental information management system according to claim 1, characterized in that: In the module 4): Smart contract template library: Design a smart contract template library containing complex conditional logic, covering scenarios such as rent payment, contract changes, and breach of contract handling; through template-based approach, reduce the difficulty and cost of writing smart contracts, and improve the efficiency and accuracy of contract management; Formal verification improves contract security: Formal verification technology is used to perform rigorous mathematical proof and verification on the logic of smart contracts to improve the correctness and security of contracts. Automated verification tools are used to detect vulnerabilities and errors in contracts to prevent contracts from being maliciously attacked or exploited. Event-driven architecture and microservice technology: Integrate event-driven architecture and microservice technology to achieve efficient collaboration and flexible expansion of contract processes; improve the scalability and maintainability of the system by decoupling the dependencies between services; at the same time, use event-driven mechanisms to achieve real-time updates and notifications of contract status, and improve the responsiveness and transparency of contract management.

6. A house rental information management system according to claim 1, characterized in that: In the module 5): Homomorphic encryption and differential privacy technology: Homomorphic encryption technology is used to improve the security of user data during processing and storage. Differential privacy technology is used to desensitize sensitive data to prevent data leakage and abuse. At the same time, data desensitization and anonymization technology are combined to protect user privacy and data security. Zero-knowledge proof and secure multi-party computing technology: Use zero-knowledge proof technology to verify and share data while protecting user privacy; Through secure multi-party computing technology, multiple parties are allowed to conduct collaborative computing and analysis without decrypting the data, thus improving the legality and compliance of data use; Compliance with laws, regulations and international standards: Comply with relevant laws and regulations, formulate a comprehensive data protection policy in combination with GDPR international standards; improve the legality and compliance of user data processing by strengthening data security management, user authority control, data auditing and monitoring, etc.; at the same time, cooperate with regulatory agencies to ensure the compliance operation and sustainable development of the system.

7. A housing rental information management method, characterized in that: Application of the system as described in any one of claims 1 to 6.

8. The housing rental information management method according to claim 7, characterized in that: The following steps are involved: S1 uses blockchain data storage modules for data storage and verification: it uses a combination of distributed ledger technology and hash chains to build an unalterable data storage structure for storing all transactions and data related to house rentals; it automatically verifies and records each data transaction through Ethereum smart contracts to improve the authenticity and integrity of the data; Ring signature technology is used to protect transaction privacy and prevent information leakage; blockchain consensus algorithm is used to improve the consistency and synchronization of data among nodes in the entire network and improve the overall stability of the system; S2 provides personalized housing recommendations through the intelligent housing recommendation and optimization module: integrating deep neural networks and attention mechanisms to conduct in-depth learning and analysis of tenants’ historical behaviors, preferences, geographic locations, and market trends; A hybrid recommendation algorithm combining collaborative filtering and content-based recommendation is applied to generate a personalized and accurate list of recommended properties based on tenants’ personal needs and market dynamics. A reinforcement learning algorithm is used to continuously optimize the recommendation strategy based on user feedback and market changes, thereby improving rental matching efficiency and user satisfaction. S3 uses dynamic credit assessment and risk management modules to conduct credit assessment and risk warning: using graph neural network and social network analysis technology to mine the interaction relationship and evaluation information between tenants and landlords, and build a credit assessment system; combining transaction data on the blockchain, applying Bayesian networks to conduct dynamic credit assessment to improve the accuracy and reliability of the assessment; integrating risk prediction models to conduct real-time monitoring and early warning of potential risks, and providing decision support for both parties to the lease; S4 realizes automated contract management through automated contract management and execution modules: design and use smart contract template libraries containing complex conditional logic, covering key links such as rent payment, contract changes, and breach of contract processing; apply formal verification technology to verify the logic of smart contracts to improve the correctness and security of contracts; integrate event-driven architecture and microservice technology to achieve efficient collaboration and flexible expansion of contract processes, and improve automated contract management and execution; The S5 application privacy protection and data security module ensures the security of user data: it uses homomorphic encryption and differential privacy technologies to improve the security of user data during processing and storage, and prevent data leakage and abuse; it uses zero-knowledge proof and secure multi-party computing technologies to achieve data verification and sharing while protecting user privacy; it complies with relevant laws and regulations, and in combination with the international standard GDPR, formulates and implements a comprehensive data protection policy to achieve the legality and compliance of user data processing.

9. A hardware system for house rental information management, characterized in that: The system includes: aHigh-performance computing and storage cluster: a1 is equipped with high-performance servers for running deep learning models, graph neural network algorithms, and blockchain nodes to achieve efficient data processing and secure storage; The a2 server cluster adopts a distributed storage architecture and combines high-speed network interconnection technology to achieve high data availability and scalability; a3 integrates GPU accelerator cards or dedicated AI processors to accelerate the calculation of deep neural networks and reinforcement learning algorithms, improving the real-time and accuracy of house recommendations and credit assessments; bSecure encryption and privacy protection equipment: b1 is equipped with hardware-level encryption devices, including hardware security modules (HSMs) or encryption cards, which are used to implement advanced encryption algorithms such as homomorphic encryption and differential privacy to ensure the security of user data during transmission and storage. b2 integrates dedicated hardware for zero-knowledge proof and secure multi-party computing, supporting efficient data verification and sharing while protecting user privacy; b3 is equipped with physical security facilities, including firewalls, intrusion detection systems (IDS) and security audit systems, to build a multi-level security protection system to prevent data leakage and illegal access.

10. A dedicated terminal device for a house rental information management system, characterized in that: The equipment includes: aSmart contract execution and verification module: a1 has a built-in smart contract execution engine that supports smart contract execution on Ethereum or other blockchain platforms, ensuring the automated execution and verification of contract terms; a2 integrates formal verification tools to perform static analysis and dynamic testing on smart contracts to improve the correctness and security of contracts; a3 is equipped with a secure encrypted communication module for secure data exchange with the blockchain network and other system components; bUser interface and interactive equipment: b1 is equipped with a high-resolution touch screen or virtual reality VR device, providing users with an intuitive and easy-to-use interface for browsing and selecting properties; b2 integrates speech recognition and speech synthesis technology, supports voice interaction, and facilitates users to query properties and sign contracts through voice commands; b3 has built-in identity authentication modules, including but not limited to fingerprint recognition, facial recognition or QR code scanning, to enhance the authenticity and security of user identity; b4 is equipped with a mobile payment module that supports multiple payment methods, including but not limited to Alipay, WeChat Pay or blockchain wallets, enabling convenient payment and management of rent.