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Research Progress on Detection Technologies for Network Attack Based on Large Language Model#br# Journal of Information Security Reserach    2026, 12 (1): 16-.   Abstract （46）      PDF （1439KB）（56）       Knowledge map    Save Large language model (LLM), with its powerful feature learning ability, the ability to recognize complex patterns, and generalization ability, has paved the way for innovative and powerful methods in network attack detection. Firstly, this paper elaborates on the technical advantages of LLM in network attack detection and proposes a corresponding technical framework. Then, drawing on existing literature, the application status of LLM in network attack detection is reviewed from three aspects: processing original security data, extracting threat features, correlation analysis, and identifying threats in the target environment. Furthermore, the problems and challenges associated with network threat detection using LLM are analyzed. Lastly, the paper outlines the future research directions for network attack detection technology leveraging LLM. This paper aims to provide references for the further development of network attack detection technology based on LLM in the field of network security. Reference | Related Articles | Metrics

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Review of Secure Containers Based on System Call Isolation#br# #br# Journal of Information Security Reserach    2026, 12 (1): 2-.   Abstract （40）      PDF （2062KB）（40）       Knowledge map    Save This article elucidates the research progress in enhancing container security through the isolation of system calls. The article firstly outlines the development background of containerization technology and its major security challenges. Subsequently, an indepth analysis is conducted on the role of system call isolation in enhancing the security of containers, including the techniques of limiting the system calls of containerized applications to reduce the attack surface, and leveraging operating system middleware and hardware protection mechanisms to accomplish the isolation and protection of containers. By comparing the implementation principles, performance, and their effects on isolation, reduction of attack surfaces, and data protection, the article reveals the advantages and limitations of system call isolation technologies in enhancing container security. Reference | Related Articles | Metrics

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PUFbased Identity Authentication for Internet of Things Against Machine Learning Attacks in Zerotrust Architecture#br# Journal of Information Security Reserach    2026, 12 (1): 33-.   Abstract （23）      PDF （2690KB）（35）       Knowledge map    Save To enable scalable IoT systems, edge computing, as a new decentralized model, is introduced into IoT scenarios. Zero trust architecture (ZTA) is wellsuited for cloudedgeend systems with blurred boundaries, offering continuous dynamic authentication and improved security. Due to their lightweight and unclonable properties, physical unclonable functions (PUFs) are often used to generate hardware fingerprint identities for devices. PUFs exploit inherent randomness introduced during hardware fabrication processes to generate unique and nonpredictable challengeresponse pairs. If an attacker collects many plaintext CRPs during continuous authentication, he may model and predict future responses, enabling machine learning attacks. This paper proposes a PUFbased authentication solution (PAMLCA). It enhances privacy protection against machine learning attacks by leveraging oblivious pseudorandom function techniques to obfuscate CRP transmission. The solution combines static and continuous multilayer dynamic verification protocols, limiting implicit trust domains within a session. Security analysis and performance comparisons demonstrate that PAMLCA offers better security, functionality, communication, and computational efficiency compared to other related solutions. Reference | Related Articles | Metrics

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Compound Admissibility Rules of Blockchain Evidence in Online Litigation Journal of Information Security Reserach    2026, 12 (2): 134-.   Abstract （99）      PDF （1088KB）（33）       Knowledge map    Save Blockchain evidence offers a solution to the limitations of traditional electronic evidence by establishing a new model of “evidence selfauthentication”. However, current regulations in China exhibit obvious limitations, failing to fully cover the application of blockchain evidence in both online and offline spaces, while prioritizing authenticity at the expense of admissibility. To realize the proper application of blockchain evidence in the Chinese context, this paper proposes a dualspace framework integrating technological selfauthentication with legal presumptions. This approach aims to achieve consensual justice, composite admissibility rules for preservation, presentation, crossexamination, and authentication, and thereby foster a novel form of evidence rule of law with benign interaction between rule of law and technical rule of law. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2026, 12 (2): 98-.   Abstract （22）      PDF （532KB）（32）       Knowledge map    Save Related Articles | Metrics

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Legal Regulation of Facial Recognition Applications from the Perspective of a Lawbased Government#br# Journal of Information Security Reserach    2026, 12 (1): 75-.   Abstract （19）      PDF （979KB）（28）       Knowledge map    Save The use of facial recognition by administrative organs has special characteristics in terms of the source of usage permissions, usage purposes, usage methods, etc., which puts forward a practical need for differentiated norms for the use of facial recognition by administrative organs. However, at present, there is no special regulation on the personal information processing behavior of administrative organs in China, and the relevant legal provisions are relatively rough and vague. Therefore, in response to the existing problems and based on the requirements of building a rule of law government, it is proposed to choose an appropriate legal regulatory model, restrict facial recognition application subjects through prior approval, grant facial recognition application permissions in stages, facilitate participation in supervision channels and improve information transparency, and carry out differentiated accountability for different types of administrative actions, so as to achieve the legalization of the institutions, functions, authorities, procedures, and responsibilities of administrative agencies using facial recognition. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 2-.   Abstract （29）      PDF （1416KB）（38）       Knowledge map    Save Reference | Related Articles | Metrics

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The EU Artificial Intelligence Regulatory Sandbox System and Its Enlightenment#br# #br# Journal of Information Security Reserach    2026, 12 (1): 82-.   Abstract （24）      PDF （1138KB）（24）       Knowledge map    Save In order to cope with the potential risks and regulatory challenges brought by the rapid development of artificial intelligence technology, exploring how to stimulate technological innovation while ensuring public safety has become the core topic in the current reform of regulatory systems. This paper proposes an institutional analysis method to systematically analyze the balancing role of the EU’s artificial regulatory sandbox system in promoting technological innovation and ensuring public safety. The research findings reveal that although the system has the positive significance of reducing the risk cost of enterprises and improving the effectiveness of supervision, it also has the problems of limited application scenarios, limited scope of liability exemption and the emergence of power rentseeking in the access process. Based on the experience of the EU, China can advance the exploration of the artificial intelligence regulatory sandbox system in the following aspects: coordinating technological innovation and public safety, and establishing a centrallocal coordinated regulatory agency; optimizing the application, evaluation, testing, reporting and exit process; improving consumers’ risk tolerance, and safeguarding their rights to know and to be compensated; and through the establishment of regulatory chat rooms and institutional incentives to promote the effective implementation of the system. Reference | Related Articles | Metrics

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A Survey on the Application of LSTM in Malicious Code Detection Journal of Information Security Reserach    2026, 12 (1): 89-.   Abstract （21）      PDF （9291KB）（24）       Knowledge map    Save With the continuous evolution of hacking technology, the iterative upgrades of malicious code variants have been acclerating and the number of malicious codes has exploded. How to rapidly and accurately detect malicious code has become a challenging research hotspot in the realm of cybersecurity. The unique gating mechanism of long shortterm memory network (LSTM) can selectively retain important historical information. Moreover, it demonstrates excellent performance for the sequential dependence of data on time series, which can effectively solve the problem of gradient vanishing or gradient explosion that may occur when traditional RNNs deal with such problems. This distinctive sequential processing capability of LSTM is particularly important for malware detection, thus learning to its extensive application in this area. This paper comprehensively sorts out and summarizes the application of LSTM in malicious code detection from five aspects, including the detection method of malicious code, the basic model and variants of LSTM, the application of LSTM in malicious code detection, the performance analysis of LSTM in malicious code detection, and the future development direction of LSTM in the field of malicious code detection, aiming to facilitating further research and improvement of existing methods for malicious code detection. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2024, 10 (E2): 27-.   Abstract （415）      PDF （763KB）（214）       Knowledge map    Save Reference | Related Articles | Metrics

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Smart Contract Vulnerabilities Based on Differential Evolutionary Algorithms and Solution Time Prediction Detection#br# Journal of Information Security Reserach    2026, 12 (1): 24-.   Abstract （31）      PDF （2331KB）（22）       Knowledge map    Save Aiming at the problems of inefficient exploration, nonguided test case generation, and poor constraintsolving tenacity in current hybrid fuzzy testing frameworks for smart contracts, this paper proposes an improved hybrid fuzzy detection framework DEST.The model integrates the advantages of fuzzy testing and symbolic execution methods to efficiently detect smart contracts, incorporates the differential evolution (DE) algorithm to optimize the quality of test cases and global search capability, and learns SMT script features through LSTM framework to predict the solving time. The DEST model uses the differential evolutionary (DE) algorithm to optimize the quality of test cases and global search capability, and learns SMT script features through LSTM framework to predict the solving time,thereby improving the solving efficiency of symbolic execution. Experiments show that the DEST model improves vulnerability detection by 9.42% and average code coverage by 3.6% over the stateoftheart benchmark model. Reference | Related Articles | Metrics

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Studies on Cybersecurity Assurance System Lv Xin Journal of Information Security Research    2015, 1 (1): 37-43.   Abstract （479）      PDF （6424KB）（766）       Knowledge map    Save With the rapid development of internet and the deep integration of social and reality space, the concept of cyberspace has been continuously expanding. Cyberspace brings new challenges to national sovereignty, security and development interests, and presents new requirements which have a profound influence. The whole world attaches great importance to the construction of cybersecurity national strategy and research on cyberspace security issues. This paper introduceds the concept and process of cyberspace and cybersecurity, and analyzesd systematics behaviors of cyberspace from the perspective of systematology. Through regarding cybersecurity Assurance System as a complex giant system, the paper makes analysis of the security objects, objectives, measures, time and information security threats of cybersecurity, and finally buildst a five-dimensional model of Cybersecurity Assurance System. Related Articles | Metrics

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Copyright Open Licensing Rules and Their Implementation Paths in Data Training Journal of Information Security Reserach    2026, 12 (1): 68-.   Abstract （17）      PDF （1135KB）（19）       Knowledge map    Save The reliance of generative artificial intelligence training on massive volumes of copyrighted works has given rise to increasingly significant risks of copyright infringement. Jurisdictions such as the European Union, the United States, and Japan have introduced regulatory responses, including innovative rules on text and data mining exceptions. Although allowing the use of copyrighted works for data training has become a general theoretical consensus in China, there remains considerable controversy over the specific pathways to compliance. This article argues for the establishment of a copyright open licensing mechanism for data training, replacing individualized authorization with voluntary public declarations, and incentivizing right holders’ participation through fair benefit allocation and transparent regulatory safeguards. This approach aims to strike a dynamic balance between technological innovation and copyright protection. Given the automatic protection and vast quantity of copyrighted works, the legal effect of publicity of open licensing declarations should be expressly recognized to protect bona fide thirdparty reliance. Additionally, right holders should be permitted to grant collective licenses for series or sets of works to better accommodate the dataintensive utilization demands in the era of artificial intelligence. Reference | Related Articles | Metrics

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Journal of Information Security Research    2016, 2 (11): 969-971.   Abstract （488）      PDF （726KB）（1396）       Knowledge map    Save Related Articles | Metrics

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Object Removal Video Tampering Detection and Localization Based on Learnable Ptuning#br# Journal of Information Security Reserach    2026, 12 (1): 61-.   Abstract （17）      PDF （2050KB）（17）       Knowledge map    Save With the continuous advancement of artificial intelligence and big data technologies, the threshold for making fake videos has been significantly reduced. Therefore, identifying whether a video has been tampered with is crucial for ensuring the authenticity and credibility of the information. Current mainstream video forgery detection methods rely on convolutional neural networks, which exhibit limited capability in capturing temporal dependencies and lack comprehensive understanding of global temporal patterns. To address this issue, this paper proposes a learnable Ptuning based method for video object removal tamper detection and localization. Firstly, the prior knowledge of the pretrained model is fully mined by learnable Ptuning, and multiview features such as spatial, temporal and highfrequency are efficiently extracted. Secondly, a multiscale feature interaction module is proposed to accurately capture the tampering traces from finegrained to coarsegrained through multiscale convolution operation and twostep decomposition strategy. Furthermore, a multiview fusion attention module is designed to significantly enhance the information sharing and fusion ability among multiview features via the crossview interaction mechanism. Experimental results demonstrate that the proposed method outperforms existing detection methods in both the time domain and the spatial domain. Reference | Related Articles | Metrics

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Innovative and Professional Talent Education Architecture of  Cyberspace Security in New Situation Journal of Information Security Reserach    2025, 11 (4): 385-.   Abstract （196）      PDF （3780KB）（120）       Knowledge map    Save The emerging new problems and technologies in the field of cybersecurity currently do not match the applicability and timeliness of existing talent cultivation in technological development. In response to this, this paper investigates the innovative professional training system for cybersecurity talents under new circumstances. We systematically examine key issues in talent cultivation, dynamic updates of training objectives, evolution of knowledge systems, and cultivation of innovative competencies. The study proposes and constructs a comprehensive, multilevel, and dynamic talent cultivation framework for cyberspace security professionals, encompassing core theoretical research, critical technology R&D, and comprehensive innovation capability development that adapts to new technological trends. Through innovative processes including instructional objective design, content adaptation, teaching implementation, and feedback mechanisms, we establish an internationally adaptable training system that dynamically responds to technological advancements. This approach strengthens the dynamism, adaptability, and practical orientation of cybersecurity talent cultivation, effectively addressing the demand for innovative professionals in cyberspace security under evolving technological landscapes and emerging requirements. Reference | Related Articles | Metrics

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Feedbackbased Quantum Key Dynamic Adjustment Scheme for Power System Journal of Information Security Reserach    2026, 12 (1): 43-.   Abstract （20）      PDF （2353KB）（15）       Knowledge map    Save The power system features numerous nodes and heavy traffic. Current quantum key distribution have insufficient key generation rates to meet the encryption requirements of power system services. This paper proposes a dynamic feedbackbased quantum key adjustment scheme to address the security challenges in power system under limited quantum key resources in crossdomain key pools. The scheme consists of two phases, corresponding to the dynamic adjustment of key pool input and output. The feedback mechanism is applied to maintain equilibrium. During the dynamic adjustment of input, realtime selection and optimization of quantum key distribution protocols are carried out based on environmental factors to improve the realtime input rate of quantum keys. During the dynamic adjustment of output, the allocation and utilization of quantum key resources are settled to maximize the overall security level of data within the sampling time. Feedback on data security is reported to the input phase to ensure that the encryption can reach the predetermined lower limit of overall security level. Experimental results show that the proposed scheme achieves an average gain of 12.59% in overall service security under highsecurityrisk conditions, outperforming conventional methods. Reference | Related Articles | Metrics

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Research and Application of General Testbed for Heterogeneous and Multimodal Blockchain#br# Journal of Information Security Reserach    2026, 12 (1): 51-.   Abstract （18）      PDF （2826KB）（15）       Knowledge map    Save In the current era of digital economy, where globalization and informatization are deeply integrated, blockchain technology due to its inherent features of decentralization, immutability, and transparency has offered innovative solutions for secure data storage, value transfer, and trust building. Given the system complexity brought about by the distributed and decentralized nature of blockchain systems, conducting effectiveness tests is of particular importance. Taking this as a starting point, this research deeply analyzes blockchain technology and existing testing tools at home and abroad, and constructs a universal testing platform for heterogeneous and multimodal blockchain systems, with a focus on technical dimensions such as compatibility, universality, scalability, stability, reliability, and security. The aim is to promote research, facilitate product development, and enable realworld applications through testing, thereby accelerating the pace of innovation in blockchain technology. Reference | Related Articles | Metrics

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A Graphembedded Data Security Audit Scheme Based on Risk Elements Journal of Information Security Reserach    2026, 12 (2): 100-.   Abstract （21）      PDF （2173KB）（14）       Knowledge map    Save With the increasing complexity of data security risks in big data environments, existing data security audit technologies are limited by fragmented feature utilization and insufficient scalability, preventing comprehensive lifecycle risk coverage and thereby reducing risk detection efficiency. To address these challenges, a graphembedded data security audit scheme based on risk elements (REGDSA) has been proposed. The scheme first constructs a security risk elements space comprising data attributes (D), user characteristics (U), carrier environment (C), and actions (A), achieving structured mapping of risk features throughout the entire data lifecycle. It then employs graph embedding technology to map these security risk elements into lowdimensional semantic vectors, constructs a crossdimensional association model for integrated analysis, and achieves efficient risk detection. The feasibility of the scheme is validated through effectiveness and performance analysis. Reference | Related Articles | Metrics

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The General Theory of Security Journal of Information Security Research    2016, 2 (4): 372-376.   Abstract （332）      PDF （1171KB）（786）       Knowledge map    Save Related Articles | Metrics

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Journal of Information Security Reserach    2024, 10 (E2): 32-.   Abstract （325）      PDF （3674KB）（207）       Knowledge map    Save Reference | Related Articles | Metrics

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Research on Trusted Data Collection Metrics Mechanism for IoT in Smart Cities Journal of Information Security Reserach    2026, 12 (2): 109-.   Abstract （16）      PDF （1939KB）（13）       Knowledge map    Save The diversity, heterogeneity, and wide distribution characteristics of IoT devices expose their operational processes to risks such as data source forgery or tampering in sensing devices. However, current trust evaluation models in multidomain IoT scenarios for smart cities exhibit limited dynamic adaptability and lack comprehensive capabilities in addressing security threats. To address these issues, this study proposes a framework from the macrooperational perspective of IoT, integrating trusted computing technologies. We construct static attribute metrics and dynamic attribute metrics mechanisms for IoT device nodes, categorize trust levels by employing clustering algorithms, and establish a comprehensive trusted metrics mechanism tailored for multisource heterogeneous IoT devices. Subsequently, through simulation experiments based on a multidomain distributed IoT architecture, we validate that the proposed trusted metrics scheme effectively detects initial malicious propagation by malicious nodes, confines malicious propagation within a limited scope, and robustly addresses security challenges under varying proportions of malicious nodes. Reference | Related Articles | Metrics

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Research on the Development Challenges and Governance Pathways of  Network Data Labeling and Tagging Technology Journal of Information Security Reserach    2026, 12 (2): 118-.   Abstract （8）      PDF （689KB）（13）       Knowledge map    Save Network data labeling and tagging technology serves as a critical enabler for ensuring the trusted circulation and secure controllability of data elements, offering significant application prospects and developmental potential. This paper reviews the global governance landscape of data labeling and tagging technologies, identifies three core challenges hindering their advancement and proposes targeted governance strategies. By addressing technical bottlenecks through institutional innovation, technological optimization, and collaborative supervision, this study provides theoretical guidance for building a secure, efficient, and modernized network data governance system in China. Reference | Related Articles | Metrics

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Blockchain Technology and Its Prospect of Industrial Application Journal of Information Security Research    2017, 3 (3): 200-210.   Abstract （559）      PDF （9369KB）（379）       Knowledge map    Save The Blockchain industry is current developing rapidly globally, with a clearer picture of the whole industry chain. The underlying infrastructure and platform, Blockchain applications in different industry segments, and venture capital investment all have sound foundations. The paper introduces the basic concept and work principle of Blockchain, describes the design philosophy, technological application and security issues of the three mainstream Blockchain platforms nowadays (Bitcoin, Ethernet and Hyperledger), and then puts forward a number of potential Blockchain application scenarios in the world. With great attention on Blockchain in terms of industry application, its helpful for Blockchain practices with Design Thinking and IBM Garage. Both in China and around the world, the paper summarizes the status quo of the Blockchain industry development, and outlines its future in general. Reference | Related Articles | Metrics

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Building Cyber Security Defense by Trusted Computing 3.0 Journal of Information Security Research    2017, 3 (4): 290-298.   Abstract （410）      PDF （1075KB）（1812）       Knowledge map    Save Related Articles | Metrics

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Research on the Application of Quantum Technology in  Egovernment Extranet Journal of Information Security Reserach    2023, 9 (2): 171-.   Abstract （301）      PDF （3966KB）（147）       Knowledge map    Save With the continuous breakthrough of quantum technology, especially the continuous development of quantum technology in the developed countries, the original classical password security measures of Chinese egovernment extranet have been seriously threatened, which must be prevented before the actual threat occurs; Using quantum secret communication to solve the security problem of key distribution in classical cryptography has become an important security measure for cryptographic applications in government affairs, finance and other fields. Based on quantum technology, this paper explores the application of special line encryption, application encryption, data encryption, identifying network attacks based on quantum computing, verifying the robustness of password security and other scenarios in the egovernment extranet, which improves the confidentiality, integrity and availability of the system business data transmission carried on the egovernment extranet to a certain extent. Reference | Related Articles | Metrics

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Research on ECDSA Key Recovery Attacks Based on the Extended  Hidden Number Problem Journal of Information Security Reserach    2026, 12 (2): 174-.   Abstract （8）      PDF （797KB）（12）       Knowledge map    Save Elliptic curve digital signature algorithm (ECDSA) is one of the most widely used digital signature algorithms. During the signing process, it requires computing scalar multiplication on elliptic curves, which is typically the most timeconsuming component of the signature. In many present cryptographic libraries, the windowed nonadjacent form representation is commonly used to represent the ephemeral key in order to reduce time consumption. This exposes sidechannel vulnerability to malicious attackers, allowing them to extract partial information about the ephemeral key from sidechannel traces and subsequently recover the signing key. Leveraging the extended hidden number problem to extract information from sidechannel traces and applying latticebased attacks to recover keys constitutes one of the mainstream attack frameworks against ECDSA. Based on above, we propose three optimization methods. First, we introduce a neighboring dynamic constraint merge strategy. By dynamically adjusting the merging parameters, we reduce the dimension of the lattice and control the amount of known information lost during the attack, ensuring high success rates for key recovery across all signatures. Second, we analyze and optimize the embedding number in the lattice, reducing the Euclidean norm of the target vector by approximately 8%, thereby improving the success rate and reducing time consumption. Finally, we propose a linear predicate method which significantly reduces the time overhead of the lattice sieving. In this work, we achieve a success rate of 0.99 in recovering the private key using only two signatures. Reference | Related Articles | Metrics

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Journal of Information Security Research    2018, 4 (8): 687-688.   Abstract （156）      PDF （607KB）（377）       Knowledge map    Save Related Articles | Metrics

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Research on Security of 5G Mobile Communication Network Journal of Information Security Research    2020, 6 (8): 699-704.   Abstract （197）      PDF （815KB）（371）       Knowledge map    Save With the rapid development of mobile communications and smart devices, the commercial implementation of the fifth generation mobile communication system (5G) provides users with a better experience, faster, smoother, and stable communication services. Aiming at the security of 5G mobile communication network,The security of 5G mobile communication network is introduced from four aspects of new services, new network architecture, new air interface technology and higher user privacy Requirements, and proposed 5G UE access and switching methods, lightweight security mechanism of the Internet of Things, network slice security isolation strategy, user privacy protection and blockchain technology and other five aspects of protection and response strategies. Reference | Related Articles | Metrics

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A Covert Backdoor Attack Method in Fewshot Class Incremental Learning Journal of Information Security Reserach    2025, 11 (9): 797-.   Abstract （70）      PDF （2644KB）（26）       Knowledge map    Save The rapid development of deep learning has led to a sharp increase in the demand for training data, and fewshot classincremental learning has become an important technique for enhancing data integrity when training deep learning models. Users can directly download datasets or models trained using fewshot classincremental learning algorithms to improve efficiency. However, while this technology brings convenience, the security issues of the models should also raise concerns. In this paper, the backdoor attack is studied on the fewshot classincremental learning model in the image domain, and a covert backdoor attack method in fewshot class incremental learning is proposed, which carries out the backdoor attack in the initial and incremental phases, respectively: in the initial phase, the covert backdoor trigger is injected into the base dataset, and the base dataset which contains the backdoor is used for the incremental learning in place of the original data; in the incremental phase, when new batch samples arrive, select some samples to add to the trigger, and iteratively optimize the trigger during the incremental process to achieve the best triggering effect. The experimental evaluation shows that the attack success rate (ASR) of the stealthy backdoor attack method proposed in this paper can reach up to 100%, the clean test accuracy (CTA) and the clean sample model performance remain at a stable level, and at the same time, the method proposed in this paper is robust to the backdoor defense mechanism. Reference | Related Articles | Metrics

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Research on Critical Information Infrastructure Security Protection Journal of Information Security Reserach    2025, 11 (12): 1074-.   Abstract （76）      PDF （334KB）（50）       Knowledge map    Save Related Articles | Metrics

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Research on Phishing Email Detection Based on Large Language Model Journal of Information Security Reserach    2026, 12 (2): 151-.   Abstract （17）      PDF （1835KB）（11）       Knowledge map    Save With the rapid increase in phishing email volumes and the continuous evolution of adversarial techniques, traditional phishing detection methods have encountered significant challenges regarding efficiency and accuracy. To address issues such as low detection rates, high falsenegative rates, and poor humancomputer interaction in existing systems, the authors proposed a phishing email detection system based on large language model. Through comprehensive analysis of key phishing email characteristics—including header fields, body content, URLs, QR codes, attachments, and HTML pages—they constructed a highquality training dataset using feature insertion algorithms. Building upon the pretrained LLaMA model, the researchers implemented LoRA finetuning technology, achieving domain knowledge transfer by updating only 0.72% of model parameters (approximately 50MB). Experimental results demonstrate that compared to traditional methods, the LLMbased detection approach achieves 94.5% overall accuracy with enhanced robustness, effectively reduces falsepositive rates, improves classification and interpretation capabilities for phishing email features, and provides a more practical and reliable solution for phishing detection. Reference | Related Articles | Metrics

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New Trends of the Main Countries Cybersecurity Strategy in 2015 Cui Chuanzhen Journal of Information Security Research

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The Totlal Solution of Cyber Security in Critical Information Infrastructure Journal of Information Security Research    2016, 2 (10): 946-951.   Abstract （292）      PDF （1455KB）（1105）       Knowledge map    Save Related Articles | Metrics

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Remote Office Solution and Its Application Based on Secure Instant Messaging Technology Journal of Information Security Research    2020, 6 (4): 301-310.   Abstract （192）      PDF （3086KB）（323）       Knowledge map    Save Remote office is getting more and more favored by users for its characteristics of unconstrained time and space, high-efficiency and convenience, fragmentation time utilization and so on, but it also raised a lot of security problems. This article systematically introduces a security solution for remote office and its innovative applications. Based on the secure instant messaging architecture of interconnection and interworking, it realizes vertical security support and application aggregation, as well as horizontal data sharing and application collaboration through open aggregation interfaces. Therefore an remote office ecosystem is built. The solution has been widely used in sectors such as government, military, finance and energy, providing a security application solution to meet the requirements of relevant national standards for the high-security users’ remote office. Reference | Related Articles | Metrics

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Great Attention to Artificial Intelligence Security Issues Journal of Information Security Reserach    2022, 8 (3): 311-.   Abstract （266）      PDF （1250KB）（305）       Knowledge map    Save Related Articles | Metrics

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Overview of Regulation of Crossborder Data Flow Journal of Information Security Reserach    2025, 11 (2): 164-.   Abstract （323）      PDF （1274KB）（153）       Knowledge map    Save The development of the digital economy has made crossborder data flow an inevitable trend, and while bringing economic benefits, the security of crossborder data flow cannot be ignored. Due to the complexity of the subjects and scenes involved in the process of crossborder data flow, and the uncontrollability of the process, how to regulate the possible security problems in the process of crossborder data flow has become the focus of the world. So far, there is no unified governance rule system for crossborder data flow in the world, and at the same time, there are huge differences in legislation on crossborder data flow in different countries, which results in the complex situation of legislation on crossborder data flow in the world. This paper describes the current situation of crossborder data flow from the perspectives of laws and regulations, bilateral agreements and standards, and in this way develops horizontal comparisons, sorts out the existing regulatory differences, analyzes the challenges and opportunities China faces under the current trend, and gives reasonable countermeasures. Reference | Related Articles | Metrics

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China’s Mirror and Insights for the Legitimate Interest Rule from  the EU Law Perspective Journal of Information Security Reserach    2026, 12 (2): 142-.   Abstract （13）      PDF （1832KB）（10）       Knowledge map    Save The rapid development of generative artificial intelligence (GAI) poses significant challenges to traditional informed consent rules. The European Union (EU) addresses this tension through the “legitimate interest rule” established under the General Data Protection Regulation. The EU effectively reconciles data protection with technological innovation by adopting an openstructured framework and dynamic balancing mechanisms. In contrast, China’s Personal Information Protection Law diverges from the EU counterpart in terms of the data processing lawfulness, rendering informed consent rules challenging to meet the demands of largescale data processing in the context of GAI. The EU’s approach is rooted in its governance doctrine that harmonizes rights protection with risk management, alongside an economic logic prioritizing a unified market. China adopts a riskbased regulatory strategy and has developed a “strong protection, weak circulation” regulatory model. To address the technical complexities of GAI, China should construct a localized legitimate interest rule which is confined to applications in commercial scenarios. This framework would incorporate a threetiered analysis—interest test, necessity test, and balance test—supported by risk mitigation measures and accountability mechanisms. Such institutional innovation would overcome the consent application dilemma while enabling adjudication to dynamically balance data subjects’ rights, commercial interests, and public values casebycase. This solution offers both a theoretical framework and practical feasibility for optimizing data governance in the AI era. Reference | Related Articles | Metrics

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Cloud Platform Accountability and Retrospect Technology Based on Security Label Journal of Information Security Research    2015, 1 (2): 181-186.   Abstract （297）      PDF （5191KB）（691）       Knowledge map    Save In oder to achieve the accountability system of cloud platform, retrospect is the primary technology method. Recalling the complete trajectory of the security event in this period,it can be controlled by the ability to trigger and record operations during this period. In order to tackle the challenges of business transparency in cloud system retrospect, the paper reviews the transparency, efficiency and cost of the enterprise. This paper states general retrospect technology based on security label, and establishes an accurate and efficient retrospect technology prototype. Reference | Related Articles | Metrics

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Promoting Information Security Is the Responsibility of the Enterprise Journal of Information Security Research    2017, 3 (5): 427-431.   Abstract （210）      PDF （476KB）（452）       Knowledge map    Save Related Articles | Metrics