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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-.   Abstract （532）      PDF （2555KB）（469）       Knowledge map    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. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2023, 9 (6): 498-.   Abstract （254）      PDF （472KB）（302）       Knowledge map    Save Related Articles | Metrics

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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-.   Abstract （283）      PDF （1924KB）（204）       Knowledge map    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. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2023, 9 (E2): 4-.   Abstract （39）      PDF （2945KB）（197）       Knowledge map    Save Related Articles | Metrics

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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-.   Abstract （246）      PDF （1101KB）（194）       Knowledge map    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. Reference | Related Articles | Metrics

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ChatGPT’s Security Threaten Research Journal of Information Security Reserach    2023, 9 (6): 533-.   Abstract （201）      PDF （1801KB）（172）       Knowledge map    Save With the rapid development of deep learning technology and natural language processing technology, the large language model represented by ChatGPT came into being. However, while showing surprising capabilities in many fields, ChatgPT also exposed many security threats, which aroused the concerns of academia and industry. This paper first introduces the development history, working mode, and training methods of ChatGPT and its series models, then summarizes and analyzes various current security problems that ChatGPT may encounter and divides it into two levels: user and model. Then, countermeasures and solutions are proposed according to the characteristics of ChatGPT at each stage. Finally, this paper looks forward to developing a safe and trusted ChatGPT and a large language model. Reference | Related Articles | Metrics

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Research and Thinking on Data Classification and Grading of Important Information Systems#br# Journal of Information Security Reserach    2023, 9 (7): 631-.   Abstract （149）      PDF （1882KB）（172）       Knowledge map    Save With the development of information technology and networking, incidents surrounding data security are also increasing. The data as a new production factor, is particularly important to ensure the security of important data. The “Data Security Law of the People’s Republic of China” clearly stipulates that the country should establish a data classification and grading protection system to implement classification and grading protection for data. This paper will study China’s data safety management regulations and policies, analyze the the degree of impact and influening objects of data damage, propose specific data classification and grading methods, and provide security protection and governance measures under data classification and grading management based on the industry characteristics and application scenarios of government data. It will achieve the openness and sharing of the data under safety protection, and provide reference for the classification and classification protection of the data in the future. Reference | Related Articles | Metrics

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Research on Privacy Protection Technology in Federated Learning Journal of Information Security Reserach    2024, 10 (3): 194-.   Abstract （148）      PDF （1252KB）（172）       Knowledge map    Save In federated learning, multiple models are trained through parameter coordination without sharing raw data. However,  the extensive parameter exchange in this process renders the model vulnerable to threats not only from external users but also from internal participants. Therefore, research on privacy protection techniques in federated learning is crucial. This paper introduces the current research status on privacy protection in federated learning. It classifies the security threats of federated learning into external attacks and internal attacks.Based on this classification,  it summarizes external attack techniques such as model inversion attacks, external reconstruction attacks, and external inference attacks, as well as internal attack techniques such as poisoning attacks, internal reconstruction attacks, and internal inference attacks. From the perspective of attack and defense correspondence, this paper summarizes data perturbation techniques such as central differential privacy, local differential privacy, and distributed differential privacy, as well as process encryption techniques such as homomorphic encryption, secret sharing, and trusted execution environment. Finally, the paper analyzes the difficulties of federated learning privacy protection technology and identifies the key directions for its improvement. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2023, 9 (E1): 105-.   Abstract （341）      PDF （1450KB）（166）       Knowledge map    Save Reference | Related Articles | Metrics

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Key Technologies and Research Prospects of Privacy Computing Journal of Information Security Reserach    2023, 9 (8): 714-.   Abstract （264）      PDF （1814KB）（161）       Knowledge map    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. Reference | Related Articles | Metrics

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Towards a Privacy-preserving Research for AI and Blockchain Integration Journal of Information Security Reserach    2023, 9 (6): 557-.   Abstract （222）      PDF （1307KB）（159）       Knowledge map    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. Reference | Related Articles | Metrics

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Research on Artificial Intelligence Data Falsification Risk  Based on GPT Model Journal of Information Security Reserach    2023, 9 (6): 518-.   Abstract （170）      PDF （1887KB）（150）       Knowledge map    Save The rapid development and application of artificial intelligence technology have led to the emergence of AIGC (Artificial Intelligence Generated Context), which has significantly enhanced productivity. ChatGPT, a product that utilizes AIGC, has gained popularity worldwide due to its diverse application scenarios and has spurred rapid commercialization development. This paper takes the artificial intelligence data forgery risk as the research goal, takes the GPT model as the research object, and focuses on the possible causes of data forgery and the realization process by analyzing the security risks that have been exposed or appeared. Based on the offensive and defensive countermeasures of traditional cyberspace security and data security, the paper makes a practical study of data forgery based on model finetuning and speculates some data forgery utilization scenarios after the widespread commercialization of artificial intelligence. Finally, the paper puts forward some suggestions on how to deal with the risk of data forgery and provides directions for avoiding the risk of data forgery before the largescale application of artificial intelligence in the future. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2023, 9 (7): 610-.   Abstract （142）      PDF （519KB）（145）       Knowledge map    Save Related Articles | Metrics

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Security Risks and Countermeasures to Artificial Intelligence#br# #br# Journal of Information Security Reserach    2024, 10 (2): 101-.   Abstract （109）      PDF （469KB）（144）       Knowledge map    Save Related Articles | Metrics

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Challenges and Responses to Data Governance in China Journal of Information Security Reserach    2023, 9 (7): 612-.   Abstract （169）      PDF （924KB）（136）       Knowledge map    Save At present, data can hold a substantial value in promoting economic and social development, and possess important strategic significance. Data governance has also been a significant topic and practical direction in the development of China’s digital economy and the construction of Digital China. By analyzing the difficulties in the following aspects of data rights confirmation, data security, data compliance, and data circulation, the institutional dilemmas and practical issues faced by data governance are being clarified. And a comprehensive approach for data governance has also been proposed, including protecting data rights and interests, strengthening compliance guidance, stimulating the vitality of the data market, and promoting technological empowerment. It is expected to advance the process of data governance in China. Reference | Related Articles | Metrics

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The Status and Trends of Confidential Computing Journal of Information Security Reserach    2024, 10 (1): 2-.   Abstract （101）      PDF （1466KB）（134）       Knowledge map    Save Related Articles | Metrics

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Research on the Integration of Full Lifecycle Data Security Management and Artificial Intelligence Technology#br# Journal of Information Security Reserach    2023, 9 (6): 543-.   Abstract （127）      PDF （1143KB）（131）       Knowledge map    Save With data becoming a new production factor, China has elevated data security to a national strategic level. With the promotion of a new round of technological revolution and the deepening of digital transformation, the artificial intelligence technology has increasing development potential, and gradually empowers the field of data security management actively. Firstly, the paper introduces the concept and significance of data security lifecycle management, analyzes the security risks faced by data in various stages of the lifecycle, and further discusses the problems and challenges faced by traditional data security management technologies in the context of massive data processing and upgraded attack methods. Then, the paper introduces the potential advantages of artificial intelligence in solving these problems and challenges, and summarizes the current mature data security management technologies based on artificial energy and typical application scenarios. Finally, the paper provides an outlook on the future development trends of artificial intelligence technologies in the field of data security management. This paper aims to provide useful references for researchers and practitioners in the field of data security management, and promote the innovation and application of artificial intelligence in the field of data security management technology. Reference | Related Articles | Metrics

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Research on Security Risks and Protection of Container Images Journal of Information Security Reserach    2023, 9 (8): 792-.   Abstract （87）      PDF （1788KB）（124）       Knowledge map    Save As the digital transformation speeds up, more and more enterprises shift to adopt container technology to improve business productivity and scalability in order to deepen the process of industrial digital transformation. As the basis for container operation, container images contain packaged applications and their dependencies, as well as process information for container instantiation. However, container images also have various insecure factors. In order to solve the problem from the source and reduce the various security risks and threats faced by containers after they are instantiated, the fulllifecycle management of container images should be implemented. In this paper, the advantages that container images bring to the application development and deployment were investigatesd, the security risks faced by container images were analyzed. Key technologies for container mirroring security protection from the three stages of construction, distribution, and operation were proposed, and then a container image security scanning tool was developed, which can scan container images for applications and underlying infrastructure that use container technology. It was proved to have good practical effects, which can help enterprises achieve fulllifecycle image security protection. Reference | Related Articles | Metrics

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Research on the Disclosure and Sharing Policy of Cybersecurity  Vulnerabilities in China and the United States Journal of Information Security Reserach    2023, 9 (6): 602-.   Abstract （158）      PDF （2305KB）（123）       Knowledge map    Save With the increasing scale and complexity of computer software systems, vulnerability attacks on software and systems become more and more frequent, and attack methods become more and more diverse. Various countries have published vulnerability management regulations to avoid the threat of software and system vulnerabilities to national cyberspace security. Proper disclosure and sharing of security vulnerabilities can help security researchers learn security threats quickly and reduce vulnerability repair costs through sharing and communication, which has become essential to mitigating security risks. This paper introduces the public vulnerability database, focuses on the summary of China and the United States network security vulnerability disclosure and sharing related policies and regulations, and gives the possible problems and countermeasures  in vulnerability disclosure and sharing in China so that security researchers can better understand and learn the security vulnerability disclosure process and sharing related regulations, which ensures that security researchers can study security vulnerabilities in the extent permitted by regulations. Reference | Related Articles | Metrics

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Vulnerability Mining and Threat Detection Journal of Information Security Reserach    2023, 9 (10): 930-.   Abstract （108）      PDF （510KB）（122）       Knowledge map    Save Related Articles | Metrics

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Research on Identity Authentication Technology Based on Block Chain and PKI Journal of Information Security Reserach    2024, 10 (2): 148-.   Abstract （76）      PDF （1573KB）（120）       Knowledge map    Save Public key infrastructure (PKI) is a secure system based on asymmetric cryptographic algorithm and digital certificate to realize identity authentication and encrypted communication, operating on the principle of  trust transmission based on trust anchor. However, this technology has the following problems: The CA center is unique and there is a single point of failure; The authentication process involves a large number of operations, such as certificate resolution, signature verification, and certificate chain verification. To solve the above problems, this paper builds an identity authentication model based on Changan Chain, and proposes an identity authentication scheme based on Changan Chain digital certificate and public key infrastructure. Theoretical analysis and experimental data demonstrate  that this scheme reduces certificate parsing, signature verification and other operations, simplifies the authentication process, and improves the authentication efficiency. Reference | Related Articles | Metrics

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Android Malware Multiclassification Model Based on Transformer Journal of Information Security Reserach    2023, 9 (12): 1138-.   Abstract （118）      PDF （2073KB）（114）       Knowledge map    Save Due to the open source and openness, the Android system has become a popular target for malware attacks, and there are currently a large number of research on Android malware detection, among which machine learning algorithms are widely used. In this paper, the Transformer algorithm is used to classify and detect the grayscale images converted by Android software classes.dex files, and the accuracy rate reaches 86%, which is higher than that of CNN, MLP and other models. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2023, 9 (E2): 13-.   Abstract （88）      PDF （1022KB）（113）       Knowledge map    Save Reference | Related Articles | Metrics

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Research and Practice on Data Security Compliance Check  Technology for Operators Journal of Information Security Reserach    2023, 9 (7): 643-.   Abstract （165）      PDF （889KB）（113）       Knowledge map    Save In the context of the development of the global digital economy, data has become an important asset for enterprises. China positions data as one of the national basic strategic resources and innovative elements of social production. In recent years, the proliferation of ransomware attacks from hackers has posed a significant risk of data leakage to enterprise data security management. Secondly, unconscious data-sharing operations by employees during the production process are also an important way for enterprise data asset leakage. With the promulgation of the Data Security Law, regulatory agencies have made data security reviews a part of the industry security inspections for operators. Therefore, based on regulatory compliance, research and practice related inspection technologies to help operators enhance their security inspection capabilities, ensure data security, and meet the needs of compliance regulation and business development. Reference | Related Articles | Metrics

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Security and Privacy Protection in 6G Network: A Survey Journal of Information Security Reserach    2023, 9 (9): 822-.   Abstract （103）      PDF （1096KB）（111）       Knowledge map    Save The scale of 5G network deployments continues to grow. While there are obvious advantages over 4G network, the limitations of 5G network are emerging, which leads to research on 6G network technologies. The complexity of 6G network and the diversity of 6G’s applications make the security issues of 6G more prominent. Coupled with the fact that 6G frameworks and related technologies are largely in a conceptual state, the security and privacy issues of 6G network are still in the exploratory stage. In this paper we analyzed the current state of 6G security and privacy research at first, and than pointed out the security challenges in 6G network, discussed potential security solutions for 6G network from the aspects of physical layer security, artificial intelligence (AI), distributed ledger technology (DLT), and edge computing, and finally we provided an outlook on future research trends of security and privacy protection in 6G network. Reference | Related Articles | Metrics

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Classification and Grading Method of Transportation Government Data Journal of Information Security Reserach    2023, 9 (8): 808-.   Abstract （91）      PDF （1008KB）（109）       Knowledge map    Save In order to promote the open sharing of government data and improve data security, it is urgent to solve the classification and grading of government data resources. This paper summarized the experience of domestic and foreign government data classification and grading, using a hybrid classification method combining surface and line to build transportation government data classification framework. A fivelevel data grading model was formed base on the data grading method of data security risk analysis, and the effect of the method was verified by introducing actual data. Transportation government data classification and grading method can effectively assist the relevant departments to carry out classification and grading of government data, as well as important data protection, and promoting the level of industry data security governance and security technology advancement. Reference | Related Articles | Metrics

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A Network Intrusion Detection Model Integrating CNN-BiGRU and  Attention Mechanism Journal of Information Security Reserach    2024, 10 (3): 202-.   Abstract （81）      PDF （2042KB）（108）       Knowledge map    Save To enhance the feature extraction capabilities and classification accuracy of the network intrusion detection model, a network intrusion detection model integrating CNNBiGRU (Convolutional Neural NetworkBidirectional Gated Recurrent Unit) and attention mechanism is proposed. CNN is employed to effectively extract nonlinear features from traffic datasets,while BiGRU extracts timeseries features. The attention mechanism is then integrated to differentiate the importance of different types of traffic data through weighted means, thereby improvingthe overall performance of the model in feature extraction and classification. The experimental results indicate that the overall accuracy rate is 2.25% higher than that of the BiLSTM (Bidirectional Long ShortTerm Memory) model. Kfold crossvalidation results demonstrate that the proposed model's good generalization performance, avoiding the occurrence of overfitting phenomenon, and affirming its effectiveness and rationality. Reference | Related Articles | Metrics

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Research on Network Malicious Traffic Detection Technology Based on  Ensemble Learning Strategy Journal of Information Security Reserach    2023, 9 (8): 730-.   Abstract （94）      PDF （2586KB）（101）       Knowledge map    Save Network traffic is the main carrier of network attacks, and the identification and analysis of malicious traffic is an important means to ensure network security. Machine learning method has been widely used in malicious traffic identification, which can achieve high precision identification. In the existing methods, the fusion model is more accurate than the single statistical model, but the depth of network behavior mining is insufficient. This paper proposes a stacking model that identifies multilevel network features and is MultiStacking for malicious traffic. It employs the network behavior patterns of network traffic in different session granularity and combines the robust fitting capability of the stacking model for multidimensional data to deeply heap malicious network behaviors. By verifying the detection capabilities of multiple fusion models on the CICIDS2017 and CICIDS2018 datasets, various detection methods are comprehensively quantified and compared, and the performance of MultiStacking detection methods in MultiStacking scenarios is deeply analyzed. The experimental results show that the malicious traffic detection method based on multilevel stacking can further improve the detection accuracy. Reference | Related Articles | Metrics

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Survey of Intelligent Vulnerability Mining and Cyberspace Threat Detection Journal of Information Security Reserach    2023, 9 (10): 932-.   Abstract （93）      PDF （1093KB）（97）       Knowledge map    Save At present, the threat of cyberspace is becoming more and more serious. A large number of studies have focused on cyberspace security defense techniques and systems. Vulnerability mining technique can be applied to detect and repair vulnerabilities in time before the occurrence of network attacks, reducing the risk of intrusion; while threat detection technique can be applied to threat detection during and after network attacks occur, which can detect threats in a timely manner and respond to them, reducing the harm and loss caused by intrusion. This paper analyzed and summarized the research on vulnerability mining and cyberspace threat detection based on intelligent methods. In the aspect of intelligent vulnerability mining, the current research progress is summarized from several application classifications combined with artificial intelligence technique, namely vulnerability patch identification, vulnerability prediction, code comparison and fuzz testing. In the aspect of cyberspace threat detection, the current research progress is summarized from the classification of information carriers involved in threat detection based on network traffic, host data, malicious files, and network threat intelligence. Reference | Related Articles | Metrics

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Research on Vulnerability Text Feature Classification Technology  Based on BERT Journal of Information Security Reserach    2023, 9 (7): 687-.   Abstract （116）      PDF （944KB）（95）       Knowledge map    Save With the development of informatization and the increase of network applications, many software and hardware products are affected by various types of cybersecurity vulnerabilities. Vulnerability analysis and management often require people to classify large amounts of vulnerability intelligence texts. In order to efficiently and accurately determine the category of the vulnerability described by the vulnerability intelligence text, this paper proposes a cybersecurity vulnerability classification model based on BERT (bidirectional encoder representation from Transformers). First, the vulnerability classification dataset is constructed, and the pretrained model represents the vulnerability intelligence text as feature vectors. Then the feature vectors complete the classification through the classifier. At last, we use the test set to evaluate the classification effect. In our experiment, we use TextCNN, TextRNN, TextRNN_Att, fastText and the proposed model to classify 48000 vulnerability intelligence texts containing vulnerability descriptions. Experimental results show that the proposed model scored the highest on the classification evaluation indicators on the test set, and it can be effectively applied to cybersecurity vulnerability classification tasks and reduce manual workload. Reference | Related Articles | Metrics

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Research on the Security Architecture of Artificial Intelligence  Computing Infrastructure Journal of Information Security Reserach    2024, 10 (2): 109-.   Abstract （64）      PDF （1146KB）（94）       Knowledge map    Save The artificial intelligence computing infrastructure is a crucial foundation for the development of artificial intelligence. However, due to its diverse attributes, complex nodes, large number of users, and vulnerability of artificial intelligence itself, the construction and operation of artificial intelligence computing infrastructure face severe security challenges. This article analyzes the connotation and security development background of artificial intelligence computing infrastructure, proposes a security architecture for artificial intelligence computing infrastructure from three aspects: strengthening its own security, ensuring operational security, and facilitating security compliance. It puts forward development suggestions aiming to provide methodological ideas for the security construction of artificial intelligence computing infrastructure, offer a basis for selection and use of safe artificial intelligence computing infrastructure, and provide decisionmaking reference for the healthy and sustainable development of the artificial intelligence industry. Reference | Related Articles | Metrics

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A Secure Data Sharing Scheme Supporting Finegrained Authorization Journal of Information Security Reserach    2023, 9 (7): 667-.   Abstract （103）      PDF （1681KB）（93）       Knowledge map    Save Considering the problems such as centralized data storage and difficulty in data sharing in cloud computing environments, based on the combination of multiconditional proxy reencryption and attributebased proxy reencryption, a multiconditional attributebased threshold proxy reencryption scheme which supports multiple authorization conditions is proposed. The scheme supports finegrained access to ciphertext data under multiple keyword authorization conditions, and can limit the authorization conditions and scope of ciphertext sharing. Only when the attribute set meets the access structure in the ciphertext and the keywords are consistent with the keywords set in the ciphertext, users can access the data. This solution achieves finegrained access to ciphertext data under multiple keyword authorization conditions, supports flexible user revocation, prevents unauthorized decryption of ciphertext by conspirators, and protects the sensitive information of data owners. Through the provable security analysis, it is shown that under the general group model, the scheme can resist chosen plaintext attack; compared with other conditional proxy reencryption schemes, the functions it supports are more diverse. Reference | Related Articles | Metrics

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Research and Application of EndtoEnd Traceability Technology for Government Data Journal of Information Security Reserach    2023, 9 (7): 655-.   Abstract （108）      PDF （1997KB）（92）       Knowledge map    Save Along with the national digital government strategic layout’s continuous advancement, in order to give full play to the benefits of big data aggregation and analysis, the nodes of digital government deal with a large amount of important data, and the data communication and information sharing among the nodes, and the data security risk is exposed day by day, which brings a great challenge to trace the source of data leakage events. This paper first analyzes the risk scenario of digital government data leakage. Then, based on the domestic and foreign wellknown traceability models 7W, ProVOC and so on, the endtoend traceability model and technical method are proposed. The model is a comprehensive application of the annotation method and the reverse query method. The method is a scenariobased improvement of database watermarking, dynamic desensitization and other technologies, and makes use of big data and association analysis technology, the traceability technology and the landing practice strategy are formed through each link of the service data flow, including data marking, staining, data operation log association analysis. Finally, taking a government core node network environment as an example, the paper carries on the application practice research, and achieves the effect of successfully tracing the evidence chain of data leakage exit and data access transmission chain, it improves the traceability efficiency and accuracy of data security events. Reference | Related Articles | Metrics

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A Mechanism Design for Compliance and Trusted Circulation of Data Journal of Information Security Reserach    2023, 9 (7): 618-.   Abstract （123）      PDF （957KB）（91）       Knowledge map    Save The circulation of data factors is critical to the development of the digital economy and highquality development of the economy. A trusted and practical data circulation mechanism should satisfy the incentives of all relevant participants simultaneously. The mechanism should be accompanied by an immediate regulation mechanism in data right authentication, registration, circulation, delivery and settlement to protect national information security and individual privacy exante. The rules of the mechanism should be observable to all so that a trusted consensus is established. The difference in features of data from tangible and intangible assets in physical existence, legal authentication, exclusiveness in use and relevant supporting techniques implies that a trusted data circulation mechanism should combine both theories of law, economics, management science and information techniques in designing circulation form, supplyside incentive, consistency in operation and screening signals in demandside. Reference | Related Articles | Metrics

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Research on the Progress of Crossborder Data Flow Governance Journal of Information Security Reserach    2023, 9 (7): 624-.   Abstract （212）      PDF （1036KB）（90）       Knowledge map    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. Reference | Related Articles | Metrics

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Legislative Thinking of Artificial Intelligence Law in the Era of  Generative Artificial Intelligence Journal of Information Security Reserach    2024, 10 (2): 103-.   Abstract （72）      PDF （874KB）（90）       Knowledge map    Save With the technological advancements and widespread adoption of Generative Artificial Intelligence (GAI), the structure of human society has undergone fundamental changes.The development of artificial intelligence technology has brought new risks and challenges. The “Interim Measures for the Management of Generative Artificial Intelligence Services” represents China’s latest exploration achievement in the field of GAI. It emphasizes the dual importance of development and security, advocates for innovation and governance in accordance with the law, and serves as a reference and inspiration for the ongoing legislative process of the Artificial Intelligence Law. Specifically, the Artificial Intelligence Law should consider the adoption of promoting legislative model, reduce the use of normative references in the legislative content, clarify the legislative approach of classification and grading, enhance  international exchanges and cooperation in artificial intelligence, and promote the positive use of science and technology by establishing a more scientific and reasonable toplevel design scheme. Reference | Related Articles | Metrics

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Data Life Cycle Safety Monitoring Method Driven by Big Data Journal of Information Security Reserach    2023, 9 (12): 1226-.   Abstract （86）      PDF （1859KB）（89）       Knowledge map    Save Aiming at the problems of small coverage, low monitoring accuracy and low automation of traditional data monitoring methods, a data lifecycle safety monitoring method driven by large data is put forward, which is based on feature analysis recognition model, content segmentation model, realtime data monitoring model, file analysis retrieval model and user abnormal behavior prediction model to monitor data security risk in realtime. It effectively guarantees the safe flow of data assets. After testing, the overall accuracy of sensitive data collection, sensitive page capture, sensitive flow monitoring and sensitive file parsing under this method is higher than 92%, and the accuracy of user’s sensitive behavior prediction is higher than 93%, which effectively improves the monitoring range and accuracy of sensitive data. Reference | Related Articles | Metrics

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Consideration on Some Problems in the Development of GPT4 and Its Regulation Scheme Journal of Information Security Reserach    2023, 9 (6): 510-.   Abstract （138）      PDF （1273KB）（89）       Knowledge map    Save With the release of the new generation of generative artificial intelligence (AI) foundation model GPT4, the era of AI has arrived. GPT4’s rapid popularity also raises some risk issues. In the aspect of data security, facing with frequent data leakage events, data storage period should be set to ensure the parallel development of data security and technology. In the aspect of intellectual property, GPT4 brings challenges on copyright infringement, subject status and works identification, which should be kept in mind in the future. In the aspect of the core algorithm, GPT4 hides the risk of algorithm discrimination. The algorithm should be continuously optimized to make GPT4 towards the true artificial general intelligence. At present, GPT4 is still in the process of continuous development, so it is still too early to design a detailed regulation scheme. In order to better deal with the risks caused by GPT4, independent innovation in the digital age should be sought, and generative AI should be included in the category of deep synthesis technology through special legislation on AI and combined with existing algorithms governing practice. Reference | Related Articles | Metrics

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Research and Practice of Government Data Security Governance System Journal of Information Security Reserach    2023, 9 (9): 900-.   Abstract （76）      PDF （4365KB）（88）       Knowledge map    Save Critical data is an important engine that keeps organizations and societies going, which makes it a target for malicious hackers, a target for intense scrutiny by regulators, and a need to prevent employees from inadvertently disclosing secret internal information. As the “guardian” to maintain the order of data opening and ensure data security, government departments should not only protect the security of sensitive data, maintain regulatory compliance, but also quickly deploy and implement data security protection projects without changing the existing business processes, and effectively control costs and reduce complexity and risks. This paper starts from the background of government data security governance, through the analysis of the government data security management status and security management needs, refer to the latest data security governance theory and technology research results at home and abroad, according to the relevant policies, laws and regulations, based on the security needs under the background of information technology application innovation, puts forward the framework of the system which applies to the security governance of government affairs data in our country, introduces the related technologies and project practice case. Reference | Related Articles | Metrics

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Comparison Research on Intrusion Detection Model Based on  Machine Learning Journal of Information Security Reserach    2023, 9 (8): 739-.   Abstract （135）      PDF （942KB）（86）       Knowledge map    Save Nowadays, network threats are constantly evolving and demonstrate increasing invisibility. Studying the performance and characteristics of multiple machine learning models for intrusion detection on modern traffic data is of greater significance to improve the timeliness of intrusion detection systems. This paper explores the use of recent efficient machine learning models, including ensemble learning(Random Forest, XGBoost, LightGBM) and deep learning(CNN, LSTM, GRU, etc) models for intrusion detection tasks on the public dataset UNSWNB15.We elaborate the task flow and experimental configuration, compare and analyze the experimental results of different models, summarize the characteristics of each model in the network intrusion detection task. The experimental results demonstrate that, under a 10% sampled dataset of UNSWNB15, the bestperforming model for the binary classification task among the experimental models is LightGBM, with an F1 score of 0.897, an accuracy of 89.86%, a training time of 1.98s, and a prediction time of 0.11s. In the case of multiclassification tasks, the most comprehensive prediction model among the experimental models is XGBoost, with an overall F1 score of 0.7907, an accuracy of 75.96%, a training time of 144.79s, and a prediction time of 0.21s. Reference | Related Articles | Metrics