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Journal of Information Security Reserach    2025, 11 (E1): 14-.   Abstract （71）      PDF （999KB）（29）       Knowledge map    Save Reference | Related Articles | Metrics

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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 （16）      PDF （1439KB）（24）       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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Research on Critical Information Infrastructure Security Protection Journal of Information Security Reserach    2025, 11 (12): 1074-.   Abstract （63）      PDF （334KB）（39）       Knowledge map    Save Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E1): 19-.   Abstract （36）      PDF （1799KB）（20）       Knowledge map    Save Reference | Related Articles | Metrics

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Research on Data Space Security Under Critical Information  Infrastructure Security Journal of Information Security Reserach    2025, 11 (12): 1093-.   Abstract （50）      PDF （968KB）（31）       Knowledge map    Save Against the backdrop of the deepening development of the digital economy, researching the security of trustworthy data spaces is of great significance for enhancing the data protection level of critical information infrastructure and promoting the highquality development of the datafactor market. This study systematically analyzes the development status of data spaces in the United States, the European Union and Japan. Building on international experience, it focuses on industrial sectors, examining the development landscape and existing challenges of data space security in each field. The study proposes policy recommendations, including strengthening the legal and regulatory framework for data spaces, advancing breakthroughs in core technologies, fostering diverse application scenarios and market ecosystems, optimizing the supply structure, and enhancing international cooperation. These proposals aim to ensure the secure circulation of data as a production factor and to promote the highquality development of the data factor market. 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 （3）      PDF （2690KB）（18）       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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Journal of Information Security Reserach    2025, 11 (E1): 5-.   Abstract （45）      PDF （1368KB）（17）       Knowledge map    Save Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 63-.   Abstract （17）      PDF （706KB）（15）       Knowledge map    Save Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2024, 10 (E2): 27-.   Abstract （409）      PDF （763KB）（199）       Knowledge map    Save Reference | Related Articles | Metrics

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Research on Frontier Technologies for Critical Information  Infrastructure Security Protection Journal of Information Security Reserach    2025, 11 (12): 1075-.   Abstract （69）      PDF （994KB）（27）       Knowledge map    Save Currently, China’s critical information infrastructure (CII) faces significant threats, including statesponsored cyber attacks and supply chain disruptions. This research aims to systematically analyze the key technological frameworks and development trends in CII security protection, assess China’s current technological capabilities and core bottlenecks in this domain, and propose development strategies and implementation pathways aligned with national conditions. Focusing on key technology clusters such as dynamic active defense, intelligent analysis and response, and resilience architectures, the study explores their synergistic application mechanisms and integration points with existing policies. The study seeks to provide critical technical support and policy recommendations for enhancing the security resilience and compliance of CII. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 2-.   Abstract （18）      PDF （1416KB）（14）       Knowledge map    Save Reference | Related Articles | Metrics

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A Survey of Zero Trust Research Journal of Information Security Research    2020, 6 (7): 608-614.   Abstract （1383）      PDF （2068KB）（1639）       Knowledge map    Save With the popularization of cloud computing, mobile office and other technologies, the enterprise network structure becomes complex. The traditional network security model is based on the idea of boundary protection, which can not meet the current needs. Zero trust is a new network security model, where no distinction is made between internal and external networks and all entities need authentication and authorization before accessing resources, which can be used to protect the network whose perimeter is increasingly fuzzy. This paper gives the definition of zero trust, introduces the architecture of zero trust, analyzes the core technology of zero trust, compares and analyses several representative zero trust schemes, summarizes the development status, points out the research direction needing attention in this field, which can provide reference for the research and application of zero trust. Reference | Related Articles | Metrics

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An Access Control Model Based on Data Classification and Grading  System for Education Cloud Platform Journal of Information Security Reserach    2022, 8 (4): 400-.   Abstract （249）      PDF （2511KB）（261）       Knowledge map    Save The education cloud platform is one of the key infrastructures for education digitization construction. It unifies business data from different departments and organizations to eliminate information silos and reduce the redundant construction of information systems. However, although the education cloud platform realizes data sharing, it also seriously influences the security of data resources because of its open and dynamic characteristics. Considering the data management and control of the education cloud platform, this paper proposes an access control model based on data classification and grading system. The model comprehensively considers the security factors such as data class, security grade, life cycle and sensitive level, and tags the data from multidimension views. The secure tag is integrated with the rolebased access control policy to construct a twostage authorization model of coarsegrained filtering and finegrained control for managing data. The prototype system proves that the proposed model can restrict data sharing and prevent users from overprivileged manipulation.Key wordscloud platform; data security; access control model; data classification and grading; secure tag; RBAC Reference | 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 （5）      PDF （979KB）（13）       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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Design and Implementation of Dark Net Data Crawler Based on Tor Journal of Information Security Research    2019, 5 (9): 798-804.   Abstract （1353）      PDF （3976KB）（1471）       Knowledge map    Save tWith the development of anonymous communication technology, more and more users begin to use anonymous communication to protect personal privacy. Tor, as the most popular application of anonymous communication system, can effectively prevent behavior such as traffic sniffing, eavesdropping and other behaviors. While protecting the privacy of users from being stolen, “dark net” is also used by many criminals. Thus, this has brought great challenges to the supervision of public security. How to strengthen the regulation and crackdown on illegal information of dark network websites is an urgent problem to be solved. Therefore, the data of crawling anonymous websites is an important basis for supervising those websites effectively. The most mainstream dark network anonymous communication system Tor was introduced briefly, its technical principles were analyzed, and a dark network data crawler program was designed, which mainly use Selenium to enter the Tor network, bulk crawl the dark Web pages and save the data to the local. It will help the public security department to further monitor and analyze the relevant content in the dark network, and also propose a feasible technical means for the police department to supervise the dark network. Reference | Related Articles | Metrics

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Research on Security Challenges and Countermeasures for Critical  Information Infrastructure in the Artificial Intelligence Era Journal of Information Security Reserach    2025, 11 (12): 1087-.   Abstract （58）      PDF （944KB）（21）       Knowledge map    Save With the rapid advancement of artificial intelligence (AI) technologies, critical information infrastructure is confronting unprecedented security challenges. This paper employs systematic analysis and comparative research methods to examine the security threats faced by critical information infrastructure in the AI era, specifically focusing on structural vulnerabilities, governance lag, and dual technical risks. Drawing on the strategic practices of major economies such as the United States, the European Union, and Japan, it proposes that China should enhance AI security policy standards, establish a security risk governance framework, and strengthen security technology innovation. Through these pathways, China can build a selfreliant, secure, and reliable AIenabled critical information infrastructure system, thereby enhancing national digital security capabilities and global competitiveness. Reference | Related Articles | Metrics

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TOPSEC, Leading Brand of Independent Innovation, Supporting Cyberspace Power Strategy Journal of Information Security Research    2018, 4 (9): 774-782.   Abstract （186）      PDF （1579KB）（888）       Knowledge map    Save Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E1): 109-.   Abstract （35）      PDF （770KB）（11）       Knowledge map    Save 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 （11）      PDF （2062KB）（11）       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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Copyright Open Licensing Rules and Their Implementation Paths in Data Training Journal of Information Security Reserach    2026, 12 (1): 68-.   Abstract （2）      PDF （1135KB）（11）       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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AI and Data Privacy Protection: The Way to Federated Learning Journal of Information Security Research    2019, 5 (11): 961-965.   Abstract （1396）      PDF （1395KB）（1331）       Knowledge map    Save With the tremendous advance in computing, algorithms and data volume, artificial intelligence ushered in the third development climax, and began to gain a foot hold in exploring various industries. However, as the emergence of “big data”, more “small data” or “poorquality data”, and “data silos” exist in industry applications. For example, in the information security realm, it is difficult for enterprises who provide security services such as content security auditing and intrusion detection based on artificial intelligence technology to exchange raw data due to the consideration of user privacy and trade secrets protection. The services between enterprises are independent, and the overall development of cooperation and technology is difficult to make a breakthrough in a short period of time. How to promote greater cooperation on the premise of protecting the privacy of organizations? Will there be any chance for technical means to solve the data privacy protection problems? Federated Learning is an effective way to solve this problem and achieve acrossenterprise collaborative governance. Reference | 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 （275）      PDF （3966KB）（145）       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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Journal of Information Security Reserach    2023, 9 (E2): 53-.   Abstract （187）      PDF （1403KB）（156）       Knowledge map    Save Reference | Related Articles | Metrics

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A Federated Learning Privacy Protection Method for Multikey Homomorphic  Encryption in the Internet of Things Journal of Information Security Reserach    2024, 10 (10): 958-.   Abstract （624）      PDF （1704KB）（237）       Knowledge map    Save With federated learning, multiple distributed IoT devices can jointly train a global model by updating the transmission model without leaking raw data. However, federated learning systems are susceptible to model inference attacks, resulting in compromised system robustness and data privacy. A federated learning privacy protection method for multikey homomorphic encryption in the Internet of Things is proposed to address the issues of existing federated learning solutions being unable to protect the confidentiality of shared gradients and resisting collusion attacks initiated by clients and servers. This method utilizes multikey homomorphic encryption to achieve gradient update confidentiality protection. Firstly, by using proxy reencryption technology, the ciphertext under different public keys is converted into encrypted data under the public key, ensuring that the cloud server can decrypt the gradient ciphertext. Then, IoT devices use their own public key and random secret factor to encrypt local gradient data, which can resist collusion attacks initiated by malicious devices and servers. Secondly, an identity authentication method based on hybrid cryptography was designed to achieve realtime verification of the identities of participants in federated modeling. In addition, in order to further reduce client computing costs, some decryption calculations are coordinated with trusted servers for computation, and users only need a small amount of computation. A comprehensive analysis was conducted on the proposed solution to evaluate its safety and efficiency. The results indicate that the proposed scheme meets the expected security requirements. Experimental simulation shows that compared to existing schemes, this scheme has lower computational overhead and can achieve faster and more accurate model training. Reference | Related Articles | Metrics

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Reentrancy Vulnerability Detection Method in Smart Contracts #br# Based on Hybrid Model and Attention Mechanism#br# Journal of Information Security Reserach    2024, 10 (11): 1056-.   Abstract （130）      PDF （2021KB）（70）       Knowledge map    Save Addressing the challenges of low efficiency and accuracy in reentrancy vulnerability detection by traditional smart contract vulnerability detection tools and single deep learning models, this paper proposes a reentrancy vulnerability detection method based on hybrid model and attention mechanism (CNNBiLSTMATT). Firstly, data processing is performed using the Word2vec model to obtain feature vectors. Secondly, these vectors undergo processing through a combination of convolutional neural network (CNN) and bidirectional long shortterm memory (BiLSTM) networks to extract features. The attention mechanism then assigns weights to highlight key features. Finally, a fully connected layer and Softmax classifier are utilized to classify the generated results, enabling reentrancy vulnerability detection in smart contracts. The experimental results demonstrate that compared with the traditional tools and deep learning methods, the method based on CNNBiLSTMATT proposed in this paper has been greatly improved in reentrant vulnerability detection. The accuracy, precision, recall rate and F1 value reached 92.53%, 93.27%, 91.73% and 92.5% respectively, confirming the effectiveness of the proposed method. Reference | Related Articles | Metrics

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Lightweighted Mutual Authentication and Key Agreement in V2N IoV Journal of Information Security Reserach    2025, 11 (8): 753-.   Abstract （95）      PDF （2403KB）（31）       Knowledge map    Save Aiming at the scenario of vehicle secure access to application servers in the V2N (vehicle to network) environment, a Kerberos extension protocol is proposed based on the PUF (physical unclonable function). This protocol provides the twoway authentication and key agreement between the vehicle and the remoted application server and ensured the confidentiality and authentication of the V2N data transmission. The CRP (challenge response pair) generated by the PUF is used to replace the password in standard Kerberos to prevent the threats of key leakage caused by physical attacks such as intrusion, semiintrusion, sidechannel attacks, etc. The characteristics of Kerberos’s lightweighted twoway authentication protocol can overcome the defects of high calculation complexity and slow speed of the public key authentication algorithms, and effectively provide the secure data transmission between vehicles and application servers. Reference | Related Articles | Metrics

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A Lightweight PUFbased Anonymous Authentication Protocol for  Wireless Medical Sensor Networks Journal of Information Security Reserach    2025, 11 (12): 1134-.   Abstract （43）      PDF （2231KB）（13）       Knowledge map    Save In response to the current challenges of resource constraints and the vulnerability of wireless medical sensor nodes, this paper proposes a lightweight anonymous authentication protocol specifically designed for wireless medical sensor networks. The protocol utilizes a physical unclonable function (PUF), deployed by the gateway, to facilitate secure authentication and key negotiation between medical experts and wireless medical sensor nodes via the gateway. The Proverif protocol analysis tool, the ROR Oracle model and nonformal analysis demonstrate that this protocol achieves mutual authentication and session key negotiation between medical specialists and wireless medical sensors, and is resistant to common attacks with good security properties. A comparison of the proposed protocol with other authentication protocols from recent years reveals that it has the lowest computational costs, with the total computational costs outperforming other protocols by more than 22.7% when the number of authentication times reaches 3500. Furthermore, experiments demonstrate that the protocol has good security attributes and lightweight characteristics, making it suitable for resourceconstrained wireless medical sensor networks. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E1): 43-.   Abstract （32）      PDF （529KB）（10）       Knowledge map    Save Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E1): 139-.   Abstract （32）      PDF （945KB）（10）       Knowledge map    Save Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 12-.   Abstract （13）      PDF （979KB）（10）       Knowledge map    Save 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 （3）      PDF （2353KB）（10）       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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Building Cyber Security Defense by Trusted Computing 3.0 Journal of Information Security Research    2017, 3 (4): 290-298.   Abstract （406）      PDF （1075KB）（1805）       Knowledge map    Save Related Articles | Metrics

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Research on Software Reliability Engineering Integrated Application Modeling Technology Journal of Information Security Research    2018, 4 (11): 1002-1010.   Abstract （143）      PDF （2236KB）（320）       Knowledge map    Save tSoftware reliability engineering, as a technology to ensure and improve software reliability, plays an important role in software development. But because of software reliability engineering activities is put in bigger difference, the purpose and process in engineering practice to the software reliability engineering technology organically unifies in together, and it's easy to have a software reliability engineering process from the situation of the software development process, seriously affected the application and promotion of software reliability engineering. This article through to the software reliability engineering activities and the development process, and the reliability engineering activity data analysis of the interactive relationship between data-driven software reliability engineering process model is put forward, the model in the form of a workflow implementation information interaction between the software reliability engineering activities, realize the whole process of the software reliability engineering of software development technical support, reliability is conducive to the realization of the software reliability engineering integrated environment. Reference | Related Articles | Metrics

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Flow Anomaly Detection Based on Hierarchical Clustering Method Journal of Information Security Research    2020, 6 (6): 0-0.   Abstract （1175）      PDF （1784KB）（674）       Knowledge map    Save With the advent of the big data era, the attacks in network traffic are rising dramatically. Detecting malicious traffic through abnormal flow detection is vital. Nowadays, the equipment of abnormal flow detection used in industry mainly adopts statistical analysis method or simple machine learning method. However, the amount of flow data and redundant data is large. The precision rate is low and the false alarm rate is high. In order to solve these problems, this paper presents a new method to detect flow anomalies based on hierarchical clustering in data processing. This method first uses the hierarchical clustering algorithm to achieve the purpose of data reduction. Then based on seven different machine learning algorithms, an abnormal traffic model based on hierarchical clustering is constructed. The experimental results show that this method can detect the abnormal behavior on the DARPA dataset with a precision rate of 99% and a recall rate of 99%. At the same time, while maintaining the precision rate of 90%, the data reduction can be up to 47.58%, which greatly improves the detection efficiency. Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 72-.   Abstract （11）      PDF （1162KB）（9）       Knowledge map    Save Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 80-.   Abstract （10）      PDF （1807KB）（9）       Knowledge map    Save Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 97-.   Abstract （15）      PDF （570KB）（9）       Knowledge map    Save Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 116-.   Abstract （16）      PDF （725KB）（9）       Knowledge map    Save Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 171-.   Abstract （10）      PDF （615KB）（9）       Knowledge map    Save Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E2): 245-.   Abstract （13）      PDF （769KB）（9）       Knowledge map    Save Reference | Related Articles | Metrics