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    ChatGPT’s Applications, Status and Trends in the Field of Cyber Security
    Journal of Information Security Reserach    2023, 9 (6): 500-.  
    Abstract847)      PDF (2555KB)(688)       Save
    ChatGPT, as a large language model technology, demonstrates extremely strong language understanding and text generation capabilities. It has not only attracted tremendous attention across various industries but also brought new transformations to the field of cybersecurity. Currently, research on ChatGPT in the cybersecurity field is still in its infancy. To help researchers systematically understand the research status of ChatGPT in cybersecurity, this paper provides the first comprehensive summary of ChatGPT’s applications in the field of cybersecurity and potential accompanying security issues. The article first outlines the development of large language model technologies and briefly introduces the technology and features of ChatGPT. Then, it discusses the enabling effects of ChatGPT in the cybersecurity field from two perspectives: assisting attacks and assisting defense. This includes vulnerability discovery, exploitation and remediation, malicious software detection and identification, phishing email generation and detection, and potential use cases in security operations scenarios. Furthermore, the article delves into the accompanying risks of ChatGPT in the cybersecurity field, including content risks and prompt injection attacks, providing a detailed analysis and discussion of these risks. Finally, the paper looks into the future of ChatGPT in the cybersecurity field from the perspectives of security enablement and accompanying security, pointing out the direction for future research on ChatGPT in the cybersecurity domain.
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    Computing Force Network Security Architecture and Data Security Governance Technology
    Journal of Information Security Reserach    2022, 8 (4): 340-.  
    Abstract746)      PDF (2657KB)(548)       Save
    As a new information infrastructure which provides deep integration of computing force and network services, computing force network (CFN) provides important support for national cyber power, digital China and smart society. At present, the planning and construction of CFN has entered a critical period, and the work related to CFN security is gradually advancing, but the systematic security architecture has not been formed. This paper summarizes the relevant research progress of CFN, analyzes the security opportunities and challenges faced by CFN, and proposes a security reference architecture based on sorting out the key security technologies, so as to provide a reference for promoting the construction of CFN security system and deploying CFN security mechanism.Key words computing force network; new information infrastructure; security reference architecture; orchestration security; privacy computation; data security; artificial intelligence
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    Research on the Application of Commercial Cryptography in 5G Network
    Journal of Information Security Reserach    2023, 9 (4): 331-.  
    Abstract626)      PDF (1197KB)(357)       Save
    As a new generation of mobile communication network infrastructure, 5G application scenarios run through all aspects of production and life, such as industrial Internet, energy industry, transportation, medical industry and education. However, unprecedented security risks have been brought to 5G networks, including massive terminal access, largescale network deployment, and massive data aggregation. 5G security has gradually become a worldwide research trend in recent years since it is crucial to social development, economic operation, and even national security. Cryptography is the core technology and basic support to assure network and information security. After more than ten years of development, national commercial cryptographic algorithms ZUC, SM4, SM3, SM2, whose independent intellectual property rights are available, have gradually exerted more indispensable effects in maintaining the security of national cyberspace. Starting from the 5G network architecture and interfaces, this paper analyzes the underlying security risks faced by the 5G networks and proposes a corresponding solution as an example in terms of the commercial cryptography application practices of the 5G network.
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    A Survey of Deep Face Forgery Detection
    Journal of Information Security Reserach    2022, 8 (3): 241-.  
    Abstract616)      PDF (2995KB)(460)       Save
    Video media has developed rapidly with the popularity of the mobile Internet in recent years. At the same time, face forgery technology has also made great progress with the development of computer vision. Face forgery technology can be adopted to make interesting short video applications, but due to characteristics such as high fidelity, easy and quick generation, its malicious use poses a great threat to social stability and information security. Therefore, how to detect fake videos of faces in the Internet has become an urgent problem to be solved. With the efforts of scholars in the world, forgery detection has also made great breakthroughs in recent years. Therefore, this review aims to summarize the existing forgery detection methods in detail. In particular, we first introduce the forgery detection data set, and then summarizes the existing methods from the aspects of forgery video trace, neural network architecture, temporal information of videos, face identity information, and generalization of detection algorithms. Then we compare and analyze their corresponding detection results. Finally, we summarize the research directions and existing problems of deep forgery detection and discusses the challenges and development trends, providing reference for relevant research. 
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    On the Exploration and Prospect of the Development Path of  Cyberspace Trusted Identity in China
    Journal of Information Security Reserach    2022, 8 (12): 1236-.  
    Abstract591)      PDF (1941KB)(131)       Save
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    Data Security Governance Technology and Practice in Big Data Applications
    Journal of Information Security Reserach    2022, 8 (4): 326-.  
    Abstract571)      PDF (2139KB)(653)       Save
    The wide application of big data technology makes data burst into unprecedented value and vitality. However, due to the large amount of data, multiple data sources, and complex data access relationships, data security lacks refined and standardized management, and the importance of data security governance becomes increasingly prominent. By analyzing data security problems in existing big data applications and common pitfalls in data security governance, this paper puts forward the ideas, principles and methods of data security governance, and with classification and grading as the entry point, presents the technical architecture of data security governance. Finally, taking the big data platform as an example, presents the application practice of data security governance technology.
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    Journal of Information Security Reserach    2023, 9 (3): 206-.  
    Abstract539)      PDF (513KB)(350)       Save
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    Journal of Information Security Reserach    2023, 9 (E1): 105-.  
    Abstract535)      PDF (1450KB)(288)       Save
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    Towards a Privacy-preserving Research for AI and Blockchain Integration
    Journal of Information Security Reserach    2023, 9 (6): 557-.  
    Abstract534)      PDF (1307KB)(301)       Save
    With the widespread attention and application of artificial intelligence (AI) and blockchain technologies, privacy protection techniques arising from their integration are of notable significance. In addition to protecting the privacy of individuals, these techniques also guarantee the security and dependability of data. This paper initially presents an overview of AI and blockchain, summarizing their combination along with derived privacy protection technologies. It then explores specific application scenarios in data encryption, deidentification, multitier distributed ledgers, and kanonymity methods. Moreover, the paper evaluates five critical aspects of AIblockchainintegration privacy protection systems, including authorization management, access control, data protection, network security, and scalability. Furthermore, it analyzes the deficiencies and their actual cause, offering corresponding suggestions. This research also classifies and summarizes privacy protection techniques based on AIblockchain application scenarios and technical schemes. In conclusion, this paper outlines the future directions of privacy protection technologies emerging from AI and blockchain integration, including enhancing efficiency and security to achieve more comprehensive privacy protection of AI privacy.
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    Application of Penetration Testing for Industrial Control System Terminals
    Journal of Information Security Reserach    2023, 9 (4): 313-.  
    Abstract514)      PDF (3070KB)(191)       Save
    The security of industrial control system terminals is getting crucial with the development of the industrial Internet. How to conduct effective safety tests for industrial control system terminals has become a key problem to be studied and solved urgently. In this paper, the general process of penetration testing is firstly introduced, then the application of penetration testing for industrial control system terminals is examined using improper input validation vulnerability as an example. The method starts from information collection and penetration tools to deeply understand the system input verification. Then, during the stage of the vulnerability discovery, the modeling of the vulnerability to sensitive input is proposed, as well as the seed mutation pattern for the industrial control programs is designed. The experiment demonstrates the effectiveness of the proposed method and the vulnerability widely existed in the industrial control systems. This method also discovers the security threats such as data tampering, denial of service, permission access and malicious script injection caused by the input validation vulnerability. At last, this work provides security suggestions for industrial control network security protection and equipment protection.
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    Journal of Information Security Reserach    2022, 8 (9): 856-.  
    Abstract458)      PDF (391KB)(279)       Save
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    Secure Sharing Scheme of Sensitive Data Based on Blockchain
    Journal of Information Security Reserach    2022, 8 (4): 364-.  
    Abstract449)      PDF (2009KB)(395)       Save
    At present, blockchain technology mainly realized the protection and verification of data subjects in data sharing applications, and for sensitive data, it should also focus on the storage and supervision of user behavior and authorized information. In this regard, this paper proposes a blockchainbased secure sharing scheme for sensitive data: a basic environment for secure sharing and data verification is built through technologies such as consortium blockchain and interplanetary file system. Then the secure sharing of sensitive data, reliable storage of user’s behavior and reasonable supervision of authorized information can be realized by sensitive data storage and sharing algorithms. The system implementation and analysis show that the scheme can share all kinds of sensitive data securely, ensure the security of storage, access and authorization of sensitive data, and meet the needs of sensitive data sharing.
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    Automated Vulnerability Mining and Attack Detection
    Journal of Information Security Reserach    2022, 8 (7): 630-.  
    Abstract441)      PDF (434KB)(352)       Save
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    Key Points and Practice of Compliance Assessment for Government Data Security
    Journal of Information Security Reserach    2022, 8 (11): 1050-.  
    Abstract437)      PDF (719KB)(368)       Save
    With the development of digital government, the security of government data has become a crucial task. The state attaches great importance to the security risk prevention of government data, and has issued a series of laws, regulations and policy documents, which put forward clear requirements for strengthening the security management of government data. Based on the requirements of government data security compliance, this article proposes the evaluation method and index system of compliance assessment for government data security, which will provide reference for the manager of government data to carry out government data security compliance assessment.
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    Research on Content Detection Generated by Large Language Model  and the Mechanism of Bypassing
    Journal of Information Security Reserach    2023, 9 (6): 524-.  
    Abstract437)      PDF (1924KB)(299)       Save
    In recent years, there has been a surge in the development of large language models. AI robots like ChatGPT, although they have a largescale security confrontation mechanism inside, attackers can still elaborate questionandanswer patterns to bypass the mechanism, with their help to automatically produce phishing emails and carry out network attacks. In this case, how to identify the text generated by AI robots has also become a hot issue. In order to carry out LLMgenerated content detection experiment, our team collected a certain number of questionandanswer data samples from an Internet social platform and ChatGPT platform, and proposed a series of detection strategies according to different conditions of AI text availability. It includes text similarity analysis based on online controllable AI samples, text data mining based on statistical differences under offline conditions, adversarial analysis based on the LLM generation method under the condition that AI samples are not available, and AI model analysis based on building a classifier by finetuning the target LLM model itself. We calculated and compared the detection capabilities of the analysis engine in each case. On the other hand, we give some antikill techniques against AI text detection engines based on the characteristics of detection strategies, from the perspective of network attack and defense.
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    Research on a New Generation Network Security Framework for Network Security Assurance of Major Event
    Journal of Information Security Reserach    2022, 8 (5): 492-.  
    Abstract425)      PDF (5642KB)(660)       Save
    Due to the open network environment,complex information system and widespread social concern, major event faces increasing network security risks. The traditional plugin network security protection is more and more difficult to adapt to the increasingly complex network security situation of major event. Based on the network security assurance work of 2022 Beijing Winter Olympic Games and 2022 Beijing Winter Paralympic Games, this paper systematically sorts out the main characteristics of network security assurance for major event, puts forward a new generation network security framework, and analyzes the structure, characteristics and models of the framework in detail. The “zero accident” in the network security assurance work of Beijing Winter Olympic Games and Beijing Winter Paralympic Games shows that the framework can effectively guide the network security assurance work for major event, and provides a successful model for network security assurance work for major event.
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    A Survey on Threats to Federated Learning
    Journal of Information Security Reserach    2022, 8 (3): 223-.  
    Abstract421)      PDF (1579KB)(286)       Save
    At present, federated learning has been considered as an effective solution to solve data island and privacy protection. Its own security and privacy protection issues have attracted widespread attentions from industry and academia. The existing federated learning systems have been proven to have vulnerabilities. These vulnerabilities can be exploited by adversaries, whether within or without the system, to destroy data security.  Firstly, this paper introduces the concept, classification and threat models of federated learning in specific scenarios. Secondly, it introduces the confidentiality, integrity, and availability (CIA) model of federated learning. Then, it carries out a classification study on the attack methods that destroy the federated learning CIA model. Finally, it explores the current challenges and future research directions of federated learning CIA model.
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    Research on Memorycorruption Vulnerability Defense Methods  Based on Memory Protection Technology
    Journal of Information Security Reserach    2022, 8 (7): 694-.  
    Abstract418)      PDF (1030KB)(216)       Save
    Since its outbreak of COVID19 in the world, the process of digital transformation has been further accelerated in all sectors around the world. With the increasing value of information assets, information security problems follow. Vulnerability attacks are the root cause of frequent security incidents in recent years. Vulnerability defense ability directly affects the security of the system. How to prevent vulnerability exploitation without patches has become an urgent need. Vulnerability exploitation defense has also become an important research content in the field of attack and defense confrontation of information security. This paper studies the binary memorycorruption vulnerability defense methods and puts forward a new method to deal with the increasing vulnerability attacks.Key words memory protection technology; memorycorruption vulnerability; network security; behavior monitoring; vulnerability defense; endpoint security
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    The Review of Generation and Detection Technology for Deepfakes
    Journal of Information Security Reserach    2022, 8 (3): 258-.  
    Abstract414)      PDF (1583KB)(308)       Save
    In recent years, deepfakes technology can tamper with or generate highly realistic and difficult to distinguish audio and video content, and has been widely used in benign and malicious applications. For the generation and detection of deepfakes, experts and scholars at home and abroad have conducted in-depth research, and put forward the corresponding generation and detection scheme. This paper gives a comprehensive overview and detailed analysis of the existing audio and video deepfakes generation and detection technology based on deep learning , data set and future research direction, which will help relevant personnel to understand deepfakes and research on malicious deepfakes prevention and detection.
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    A Survey of SQL Injection Attack Detection and Defense Technology
    Journal of Information Security Reserach    2023, 9 (5): 412-.  
    Abstract413)      PDF (2612KB)(322)       Save
    In the era of “Internet+”, data is the most valuable resource of the Internet. Attackers often use SQL injection attacks to destroy the database in order to obtain important data information in the database. The threat to database security is becoming more and more serious. At present, the research on SQL injection attacks mostly focuses on traditional SQL injection attacks, but lacks the cognition of new advanced SQL injection technology with stronger concealment and higher risk, and the research on related detection and defense technology. In response to this phenomenon, this paper analyzes and evaluates traditional and advanced SQL injection attack technologies and their technical characteristics based on the classification of SQL injection technologies; summarizes existing detection and defense technologies, and evaluates the advantages and disadvantages of these methods for defense effectiveness; finally The problems existing in the current research field are sorted out, and suggestions for future research directions are put forward.

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    Journal of Information Security Reserach    2022, 8 (8): 734-.  
    Abstract410)      PDF (422KB)(325)       Save
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    Data Security Governance Practices
    Journal of Information Security Reserach    2022, 8 (11): 1069-.  
    Abstract409)      PDF (5897KB)(332)       Save
    Data security governance has been written into the Data Security Law of the People’s Republic of China. At the same time, data security governance is also one of the key points in the construction of systematic network security. This paper analyzes the data security governance concepts of Gantner and Microsoft, combines enterprise architecture, stakeholder theory, data flow security assessment, maturity security assessment and other methodologies, forms a set of data security governance concepts, and designs a data security management and operation platform for dynamic supervision and data security operation of data security governance indicators. Since 2018, this methodology and platform have been put into practice in the project to solve the construction and optimization of users’ data management and defense system.
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    Research on Network Security Governance and Response of  Largescale AI Model
    Journal of Information Security Reserach    2023, 9 (6): 551-.  
    Abstract406)      PDF (1101KB)(380)       Save
    With the continuous development of artificial intelligence technology, largescale AI model technology has become an important research direction in the field of artificial intelligence. The publication of ChatGPT4.0 and ERNIE Bot has rapidly promoted the development and application of this technology. However, the emergence of largescale AI model technology has also brought new challenges to network security. This paper will start with the definition, characteristics and application of largescale AI model technology, and analyze the network security situation under largescale AI model technology. The network security governance framework of largescale AI model is proposed, and the given steps can provide reference for network security work of largescale AI model.
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    Challenges and Countermeasures of Artificial Intelligence Security Governance
    Journal of Information Security Reserach    2022, 8 (4): 318-.  
    Abstract400)      PDF (2934KB)(377)       Save
    AbstractThe development of artificial intelligence has gone through several ups and downs. In recent years, it has once again attracted the great attention of academia and industry. Its technology is being rapidly applied in various fields and has become a new round of strategic technology for countries to realize industrial transformation and upgrading. However, the indepth application of artificial intelligence with machine learning as the core technology has brought about increasingly prominent technical and social risks. This paper summarizes and analyzes the security risks faced by artificial intelligence and its governance status from three aspects: potential security vulnerabilities, excessive abuse, and social ethics. To further deal with the issue of AI security governance, this paper puts forward solutions and suggestions from the perspectives of technology, standards, and laws, aiming to provide an idea for the establishment of AI security governance systems and industrial applications. Meanwhile, this paper also gives a direction for the exploration of AI security technology research.Key wordsartificial intelligence; security governance; machine learning; social ethics; lasws and regulations
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    Survey of Coverage-guided Grey-box Fuzzing
    Journal of Information Security Reserach    2022, 8 (7): 643-.  
    Abstract372)      PDF (1745KB)(281)       Save
    In recent years, coverageguided greybox fuzzing has become one of the most popular techniques for vulnerability mining, which plays an increasingly important role in the software security industry. With the increasing variety of application scenarios and complexity of test applications, the performance requirements of coverageguided greybox fuzzing are further improved. This paper studies the existing coverageguided greybox fuzzing methods, summarizes its general framework, and analyzes its challenges and the development status. The experimental results of these methods are summarized and the problems existing in the experimental evaluation are discussed. Finally, the future development trend of coverageguided greybox fuzzing is prospected.Key words fuzzing; hole mining; coverageguided; greybox; software security

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    Journal of Information Security Reserach    2022, 8 (8): 812-.  
    Abstract368)      PDF (4751KB)(220)       Save
    Because deep learning can freely extract and combine features, an increasing number of academics are using it to perform sidechannel attacks without taking into consideration preprocessing processes like choosing sites of interest and alignment. The sidechannel attack model based on deep learning is built with multilayer perceptron networks, convolution neural networks, and recurrent neural networks, but it has several issues in the training stage, such as overfitting, gradient disappearance, and sluggish convergence speed. Meanwhile, the selfattention mechanism is capable of extracting characteristics in natural language processing, computer vision, and other domains. To make the selfattentiveness mechanism accessible to the area of deep learning sidechannel attacks, we present SADLSCA, a deep learning sidechannel attack model based on the selfattentiveness mechanism, based on the features of deep learningbased sidechannel attacks. SADLSCA addresses the issues of fast overfitting, gradient disappearance, and slow convergence of deep learningbased sidechannel attack models during training, and experimentally verifies that the energy traces required for a successful attack on public datasets ASCAD and CHES CTF 2018 are reduced by 23.1% and 41.7%, respectively.
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    DCR Defense Mechanism of Federated Learning Model for  Data Governance Poison
    Journal of Information Security Reserach    2022, 8 (4): 357-.  
    Abstract366)      PDF (1091KB)(233)       Save
    Federated learning is a new mode of data security governance, which can make available data invisible, but federated learning is facing the threat of model poisoning attack, and its security needs to be improved. To this end, a Dynamic Cacheable Revocable (DCR) model poison defense mechanism based on federated learning is proposed. Based on the lossbased model poisoning defense method, the Dynamic threshold is calculated and used before each iteration. It makes the enemy unable to know the defense mechanism a priori, which increases the difficulty of the enemy’s attack. Moreover, the buffer period is set in the mechanism to reduce the risk of benign nodes being “killed by mistake”. At the same time, the system stores the global model parameters of each round. In case of model poisoning, the global model parameters before the round in buffer period are reloaded to achieve callback. The callable setting can reduce the negative impact of model poisoning attack on the global model, so that the federated learning model can still achieve convergence with good performance after being attacked, and ensure the security and performance of the federated learning model. Finally, in the experimental environment of TFF, the defense effect and model performance of this mechanism are verified.Key words data governance; federated learning; model poisoning; malicious node; dynamic cacheable revocable
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    Journal of Information Security Reserach    2022, 8 (5): 418-.  
    Abstract343)      PDF (2768KB)(277)       Save
    Most consortium blockchains now run in closed and deterministic environments, and their smart contracts cannot have IO operations with the outside world. Some application scenarios (such as crediting blockchain, carbon trading blockchain, supply chain, express tracking, etc.) require a mechanism responsible for data interaction with the outside of consortium blockchains, generally called an oracle machine. The existing oracle techniques in the consortium chain have the following shortcomings: 1) The limited data interaction mode cannot meet the needs of distributed applications; 2) With the increase in the number of distributed oracle nodes, the consensus delay will also increase. 3) The participants of the consortium blockchain usually maintain the oracle nodes in the distributed oracle system, and the behavior in the data consensus process is invisible to the blockchain, which is not conducive to data governance. To address the problems, this paper proposes the following methods: 1) Based on the eventdriven mechanism, four oracle design patterns or interaction patterns are proposed, which support Pull and Push, Inbound and Outbound, four combinations of the oracle data interactions; 2) The threshold signature algorithm is used to reach a consensus on the data, which improves the scalability of the oracle system while ensuring the credibility of the data; 3) A reputation mechanism is introduced for data governance to maintain a local and global reputation for each oracle node, and dynamic update is carried out in the data consensus process. Finally, by designing multichain scenairos in crediting blockchain and carbon trading blockchain, the applications of the four oracle design patterns, scalability, and reliability of the oracle nodes are evaluated and analyzed.
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    Journal of Information Security Reserach    2022, 8 (3): 270-.  
    Abstract341)      PDF (1210KB)(242)       Save
    On the premise of protecting user privacy, ensuring data security and legal compliance, integrating data from various industry organizations has become a major problem for artificial intelligence practitioners. This paper proposes a Security protection method for Federated Learning models based on secure Shuffling and Differential Privacy (SFLSDP). The owner of the federated model uses differential privacy technology to add noise to the model parameters of federated learning to generate noisy model parameters, and then use the authorization key and the secure shuffling algorithm encrypt the model parameters, and send the encrypted federated learning model parameters to the user. When the user uses the federated learning model locally, he firstly uses the authorization key and the secure shuffling algorithm to decrypt the model parameter ciphertext, and obtain a noisy federated learning model. The users can get the desired output results by taking their own data as the input of the model. Experiments show that this method can protect the privacy of the original learning model and obtain high utility at the same time.

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    Survey of Network Intrusion Detection Based on Deep Learning
    Journal of Information Security Reserach    2022, 8 (12): 1163-.  
    Abstract341)      PDF (2421KB)(226)       Save
    The rapid development of the Internet not only brings great convenience to users, but also causes many security incidents. With the increasing number of network attacks such as zeroday vulnerabilities and encryption attacks, the network security situation is becoming more and more serious. Intrusion detection is an important means of network attack detection. In recent years, with the continuous development of deep learning technology, intrusion detection system based on deep learning is gradually becoming a research hotspot in the field of network security. This paper introduces recent work on network intrusion detection using deep learning technology based on extensive investigation of literature. Firstly, it briefly summarizes the current network security situation and traditional intrusion detection technologies. Then, several deep learning models commonly used in network intrusion detection system are introduced. Then it summarizes the commonly used data preprocessing techniques, data sets and evaluation indicators in deep learning. Then from the perspective of practical application, it introduces the specific application of deep learning model in network intrusion detection system. Finally, the problems in the current research process are discussed, and the future development direction is put forward.
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    Key Technologies and Research Prospects of Privacy Computing
    Journal of Information Security Reserach    2023, 9 (8): 714-.  
    Abstract332)      PDF (1814KB)(239)       Save
    Privacy computing, as an important technical means taking into account both data circulation and privacy protection, can effectively break the “data island” barriers while ensuring data security, it enables open data sharing, and promotes the deep mining and use of data and crossdomain integration. In this paper, the background knowledge, basic concepts and architecture of privacy computing were introduced, the basic concepts of three key technologies of privacy computing, including secure multiparty computation, federated learning and trusted execution environment were elaborated, and studies on the existing privacy security was conducted, a multidimensional comparison and summarization of the differences of the three key technologies were made. On this basis, the future research direction of privacy computing is prospected from the technical integration of privacy computing with blockchain, deep learning and knowledge graph.
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    Research on the Progress of Crossborder Data Flow Governance
    Journal of Information Security Reserach    2023, 9 (7): 624-.  
    Abstract331)      PDF (1036KB)(155)       Save
    While promoting the sharing of global data resources, the crossborder data flow will inevitably threaten data sovereignty and national security. The competition for the right to speak in international data with crossborder data flow governance as the game will become the focus of competition in the international community in the future. This paper introduces the background knowledge and constraints of crossborder data flow, investigates and compares the crossborder data flow governance models of the United States, the European Union, Russia, Japan, and Australia, and analyzes the current policy status and challenges of crossborder data flow governance in our country, on this basis, countermeasures and suggestions are proposed for the governance of crossborder data flow in our country from the perspective of data sovereignty, including promoting the classification supervision of crossborder data flow, innovating and developing crossborder data flow governance models, improving countermeasures against extraterritorial “longarm jurisdiction”, and actively participating in and leading the formulation of international governance rules.
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    Model of Data Security Governance Based on Business Scenarios
    Journal of Information Security Reserach    2022, 8 (4): 392-.  
    Abstract331)      PDF (1743KB)(323)       Save
    With the rapid development of the digital economy, all countries around the world regard data assets as important resources that may affect national security, and have taken actions to issue laws and regulations related to data security in order to comprehensively improve data security capabilities. In this context, organizations involved in data processing activities on the one hand need to face constraints related to data security policy requirements; on the other hand, they want to protect the data that may affect the vital interests of the organization. Therefore, in addition to data security compliance work, it is also necessary to implement data securityrelated requirements effectively. Based on the organization’s own business, the realization of business goals as the driving force is the key element of sustainable improvement of data security capability. This paper reviews the typical data security framework and proposes a data security governance model based on business scenarios, which can provide some references for organizations to carry out data security governance work.Key words business scenarios; data security governance model; data flow transformation; data classification and grading; data security operation; data security risks
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    Journal of Information Security Reserach    2023, 9 (6): 498-.  
    Abstract326)      PDF (472KB)(404)       Save
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    Research on the Application of Commercial Cryptography to Cloud Computing
    Journal of Information Security Reserach    2023, 9 (4): 375-.  
    Abstract320)      PDF (3447KB)(279)       Save
    Cloud computing, as a new information processing method, enables users to access information and communication resource services through the network, and it has become an inevitable trend in the development of information technology industry. Users, data, and information resources are highly concentrated, highly dependent on the continuity of cloud platform services, and the scalability of virtualized resources bring inevitable security risks to cloud computing., and the scalability of virtualized resources bring inevitable security risks to cloud computing. Therefore, how to eliminate the security risks of cloud computing by using commercial cryptography technology has become the current research hotspot. This paper starts from the cloud computing network architecture, anlyzes the cryptography application requirements of cloud computing. The paper proposes the corresponding commercial cryptography application scheme for cloud computing scenarios on this basis. The research results provide a theoretical guidance and reference for the application practice of commercial cryptography in cloud computing scenarios, and are expected to solve the key problems of cloud computing security.
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    Technology and Research Progress of Generative Adversarial Networks
    Journal of Information Security Reserach    2022, 8 (3): 235-.  
    Abstract314)      PDF (866KB)(232)       Save
    In recent years, generative adversarial networks (GANs) researches have increased exponentially. The generative adversarial networks utilize zero-sum game theory to combine two competing neural networks, so that they can produce clearer and much more discrete outputs. In the fields of computer vision, medical treatment, finance, etc., significant progress has been made in the field of image and video processing and generation, data set enhancement, and time sequence prediction. This paper introduces the basic framework, theory and implementation process of generative adversarial networks, and analyzes the mainstream research status in recent years, and lists the problems which need to be improved by reviewing the variants of generative adversarial networks and their application scenarios. In addition, this paper also focuses on how to apply generative adversarial networks to arrange privacy measures and deal with sensitive data, as well as the future development trend of generation countermeasure network technology in related fields.
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    Journal of Information Security Reserach    2022, 8 (8): 845-.  
    Abstract307)      PDF (1967KB)(207)       Save
    Aiming at the problems of complex sources, difficult to understand and share security threat intelligence, this paper realizes deep learning of threat intelligence features based on restricted Boltzmann machine, which maps the original threat intelligence features from high dimensional space to low dimensional space layer by layer, and constructs the cyberspace security threat knowledge map. By using the cyberspace security threat knowledge map, and combining with the current context, the path evolution and tracing of security threats are carried out through event flow processing to accurately perceive cyberspace security threats. The experiment verifies the feasibility of constructing the cyberspace security threat knowledge map, and verifies the security threat perception method based on the knowledge map is more suitable for the perception of highintensity security threats by comparing with traditional threat detection methods.
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    Journal of Information Security Reserach    2022, 8 (5): 484-.  
    Abstract306)      PDF (1191KB)(252)       Save
    Smart contract is the program code that can be shared on the blockchain, involving account address, digital assets and other information. In recent years, smart contracts develop rapidly, expanding the blockchain platform from a simple distributed ledger system to a rich decentralized operating system, leading the era of blockchain 2.0. However, smart contracts are facing a serious problem of privacy disclosure, which limits the further development and application of smart contract technology. This paper analyzes four smart contract privacy protection key technologies of zero knowledge proof, secure multiparty computing, homomorphic encryption and trusted execution environment, summarizes the latest research results of current smart contract privacy protection solutions, and prospects the future research direction.
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    Journal of Information Security Reserach    2021, 7 (E2): 90-.  
    Abstract304)      PDF (2497KB)(302)       Save
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    Journal of Information Security Reserach    2022, 8 (8): 831-.  
    Abstract301)      PDF (719KB)(280)       Save
    At present, open source has become one of the best organizing methods for human superlargescale intellectual collaboration, and has also become the "main battlefield" of technological innovation, ushering in great development worldwide. At the same time, open source software has also become a mature target for software supply chain attacks, facing security vulnerabilities, intellectual property rights, open source regulation and other risks. This paper analyzes the current security situation and risks of open source software supply chain, puts forward open source software development security solutions, and puts forward suggestions for the development of open source software supply chain.
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