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A Stateaware Fuzzing Method for Trusted Execution Environment Kernel Journal of Information Security Reserach    2026, 12 (3): 198-.   Abstract （86）      PDF （2080KB）（78）       Knowledge map    Save Trusted execution environment (TEE) is widely used, and its kernel security has become a significant area of focus. Fuzzing, a powerful technique for detecting vulnerabilities in operating system, has increasingly been applied to the security analysis of TEE. However, conventional fuzzing tools cannot be directly used for TEE kernels due to their isolation. Coverageguided fuzzers often discard test cases that trigger new states but cover the same code, which limits their effectiveness in discovering vulnerabilities. To address these challenges, a stateaware fuzzing method tailored for TEE kernels is proposed. Initially, a modeling and tracing approach is developed to represent the program state through statevariable values and retaining the test cases that trigger new states, overcoming the limitations of coverageguided fuzzers. Subsequently, we introduce an innovative communication scheme to tackle issues arising from TEE isolation. New seed retention and selection algorithms are proposed to better guide the fuzzer in exploring vulnerabilities. Finally, the NGram model is employed to enhance test case generation and optimize the framework’s performance. A prototype, named TrustyStatefuzz, has been implemented and evaluated on fuchsia, the selfdeveloped microkernel operating system Nebula, and OPTEE. The evaluation results show that TrustyStatefuzz is effective at detecting both new code and vulnerabilities. TrustyStatefuzz discovers 9 unknown vulnerabilities and 23 known vulnerabilities. Additionally, it achieves 13% higher code coverage and 27% higher state coverage than the stateoftheart fuzzer Syzkaller. Reference | Related Articles | Metrics

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Research of Cyber Situation Awareness System in the Implementation of Classified Protection 2.0 Journal of Information Security Research    2019, 5 (9): 828-833.   Abstract （290）      PDF （1470KB）（731）       Knowledge map    Save Cyber security classified protection regulations (classified protection 2.0) are proposed in order to ensure the implementation of cyber security law. Overall, at the legal level, the guaranty 2.0 will correspond to the cyber security level protection system in the “Cyber Security Law”, which is a concrete measure for implementing the cyber security law. Secondly, at the technical level, cyber security technology is developed from passive defense (classified protection 1.0) to active immune defense (classified protection 2.0). Finally, at the implementation level, there has been a shift from traditional information system protection to the construction of active defense system of cyber space. The new characteristics are analyzed in detail in this paper. Combining with the development of situation awareness system products, the challenge and feasible solution are also studied in face of classified protection 2.0, finally a feasible solution is also presented. Reference | Related Articles | Metrics

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Singapore’s Data Security Governance Model and Its Implications Journal of Information Security Reserach    2026, 12 (3): 284-.   Abstract （46）      PDF （1712KB）（44）       Knowledge map    Save As one of the countries with a relatively high level of digitalization in Asia, studying the successful experience of Singapore’s data security governance model is of great significance for improving China’s data security governance system. By using the methods of literature review and comparative research, this paper sorts out Singapore’s data security governance model from the aspects of institutional system, development process and collaborative mechanism, and finds the following characteristics: Singapore leads data security governance with the national innovation strategy, promotes data security governance with personal data rights, and builds an open crossborder data transmission rule system, forming a “rightspromoting” data security governance model. In light of China’s current circumstances, this paper proposes the optimization path of the data security governance model, including coordinating data security governance with an overall strategy, continuously deepening the personal data rights protection system, strengthening the multiparty collaborative governance system, and building a safe and effective crossborder data flow system. Reference | Related Articles | Metrics

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Federated Learning Backdoor Attack Based on Constrained Perturbation and Loss Regulation Journal of Information Security Reserach    2026, 12 (3): 210-.   Abstract （79）      PDF （3353KB）（39）       Knowledge map    Save Federated learning, as a distributed machine learning framework, enables multiparty collaborative training with data isolation and privacy protection, However, its decentralized architecture makes it vulnerable to backdoor attacks. This paper proposes a federated learning backdoor attack method based on the constrained perturbation and loss regulation (CPR). The method realizes backdoor implantation and proliferation through three modules: input perturbation, dynamic weight regulation, and secondary perturbation reinforcement. Input perturbation introduces constraintbased noise to poison the training samples. Dynamic weight regulation dynamically adjusts the task weights by introducing cosine annealing, which realizes the balance between backdoor feature learning and main task performance. Secondary perturbation reinforcement utilizes dynamic loss values to further perturb the poisoned samples and reinforce its backdoor features. The CPR backdoor attack is evaluated on MNIST, FashionMNIST and CIFAR10 datasets, and the experimental results show that the CPR backdoor attack is able to significantly improve the success rate of the attack while maintaining the accuracy of the model’s primary task and exhibits higher stealth and persistence under a variety of data distribution conditions, as compared to pixel, labelflipping and hybrid attacks. Reference | Related Articles | Metrics

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A Method of Active Defense for Intelligent Manufacturing  Device Swarms Based on Remote Attestation Journal of Information Security Reserach    2023, 9 (6): 580-.   Abstract （280）      PDF （1988KB）（218）       Knowledge map    Save With the development of artificial intelligence technology, intelligent manufacturing has become an inevitable choice for enterprise production. However, a compromised device not only causes issues such as confidentiality leaks and production chain errors, but also serves as a springboard for attackers and thus affects the security of the entire swarm. In this paper, we propose a proactive defense solution for intelligent manufacturing swarms based on remote attestation (SecRA). SecRA generates independent challenges for each device, enabling pointtopoint communication between gateways and devices. By extending the functionality of gateways, SecRA utilizes asynchronous communication to adapt to the existing network structure. In addition, based on the challengequery attestation protocol, communication and computation costs are transferred to resourcerich gateways, greatly reducing the burden of devices. Finally, the efficiency and feasibility of the SecRA are experimentally verified. Reference | Related Articles | Metrics

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Anomaly Encrypted Traffic Detection Method Based on Graph Attention Network Journal of Information Security Reserach    2026, 12 (3): 237-.   Abstract （42）      PDF （3111KB）（33）       Knowledge map    Save In response to the limitations of poor feature extraction, insufficient consideration of topological features, class imbalance, and lack of interpretability in existing anomaly encrypted traffic detection methods, this paper proposes an encrypted traffic detection model EGARNet that integrates a graph attention network  (GAT) with edge feature embedding and residual networks. First, traffic data is preprocessed, and the network’s fivetuple information is used to construct graph nodes, with the remaining flow features treated as edge features, transforming encrypted traffic data into graph data. To adapt to the GAT algorithm, a new network traffic graph is constructed where new nodes correspond to edges in the original graph, and shared vertices in the original graph correspond to edges between two nodes, transforming the traffic detection problem into a node classification problem. Next, the attention coefficient for each node is calculated through the GAT algorithm to aggregate and update features. Finally, residual connections of the original nodes are added to the algorithm to improve the performance for minority classes. Experimental results on the CICDarkNet dataset demonstrate that the method effectively addresses the class imbalance issue in anomaly detection of encrypted traffic, with significant improvements in detection metrics for both binary and multiclass scenarios. Reference | Related Articles | Metrics

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Overview of Voiceprint Recognition Technology and Applications Journal of Information Security Research    2016, 2 (1): 44-57.   Abstract （1319）      PDF （12707KB）（691）       Knowledge map    Save With the rapid development of information technology, how to identify a person to protect hisher personal privacy as well as information security has become a hot issue. Comparing with the traditional identity authentication, the biometric authentication technologies have the features of not being to get lost, to be stolen or forgotten when being used. The use of them is not only fast and convenient, but also accurate and reliable. Being one of the most popular biometric authentication technologies, the voiceprint recognition technology has its unique advantages in the field of remote authentication and other areas, and has attracted more and more attention. In this paper, the voiceprint recognition technology and its applications will be mainly introduced, including the fundamental concept, development history, technology applications and industrial standardizations. Various kinds of problems and corresponding solutions are overviewed, and the prospects are pointed out finally. Reference | Related Articles | Metrics

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Blockchain Technology and Application Journal of Information Security Research    2018, 4 (6): 559-569.   Abstract （191）      PDF （1884KB）（507）       Knowledge map    Save A rush of digital cryptocurrency is being set off by bitcoin since it was introduced in 2008. As its underlying core technology, blockchain and blockchain technology have received extensive attention from many aspects. Blockchain technology is a combination of many technologies for data exchange, processing and storage based on cryptography, peer-to-peer communications, distributed coherency protocols and smart contracts. Blockchain is a decentralized, distributed public database based on the blockchain technology. The implementation of the blockchain's classification, five-tier architecture, smart contracts, scalability and security are introduced in detail in this article. We introduced the application of blockchain in current fields and related development of domestic blockchain. Finally, the advantages and disadvantages of the blockchain are outlined, which lays the foundation for futther research and application. Reference | Related Articles | Metrics

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Research on Neural Networkbased Protocol Identification for Secure Multiparty Computation Journal of Information Security Reserach    2026, 12 (3): 228-.   Abstract （40）      PDF （1921KB）（30）       Knowledge map    Save Secure multiparty computation (SMPC) enables joint computation while keeping private data undisclosed, positioning it as a core technology in privacypreserving computing. However, its high computational complexity and substantial overhead render practical deployment reliant on cloud providers for computational resources. To meet the requirement of realtime protocol monitoring in privacypreserving computing scenarios on cloud platforms, this paper proposes a neural networkbased protocol identification scheme for SMPC. By collecting performance data from computation nodes, including CPU usage and network bandwidth usage, a 3D convolutional neural network (CNN) model integrating spatiotemporal feature extraction capabilities is constructed. This model, along with a dynamic threshold mechanism, enables highaccuracy classification of known protocols and anomaly detection of unknown protocols. Experimental results show that the model attains an accuracy of 98% on the validation dataset and a detection rate exceeding 98% for unknown protocols, thereby significantly improving the operational security and reliability of SMPC systems. Reference | Related Articles | Metrics

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Differentially Private Text Synthesis Based on Gradient Direction Filtering Journal of Information Security Reserach    2026, 12 (3): 220-.   Abstract （39）      PDF （1264KB）（26）       Knowledge map    Save Deep learning models enhance performance by memorizing training data, but this also poses a risk of training data leakage. Differential privacy, as a mainstream privacy protection method, effectively mitigates this risk. However, existing differentially private data synthesis approaches suffer from slow model convergence and low data usability. To address these issues, we propose the TVDPSGDLM_D framework. This approach introduces TVDPSGD, a thresholdvalidated differentially private optimization algorithm that incorporates a validation mechanism to filter gradient directions during differentially private model training. By discarding ineffective updates, this approach accelerates model convergence. TVDPSGDLM embeds TVDPSGD into a language generation model to synthesize labeled text datasets that maintain statistical similarity to the original data. Additionally, a pretrained classifier is used to filter the generated text, removing samples where the classification results do not match the assigned labels, thereby improving the quality of the synthetic dataset. Experimental results on public datasets demonstrate that the proposed method preserves data privacy while achieving a classification accuracy of 89.4% on the processed synthetic dataset. 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 （305）      PDF （1681KB）（272）       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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A Physical Security Scheme of Wireless Networks using Matrix Projection Journal of Information Security Research    2015, 1 (2): 131-139.   Abstract （297）      PDF （7324KB）（628）       Knowledge map    Save Because the physical layer of wireless communication lacks real shell protection, such as limited communication divergence of data transmission, content can be taken at the same time the listener and the eavesdropper, the purpose of this study lies in how to be wireless radio features as much as possible and improve the security performance of the wireless communication system as a whole, which is on the premise of the listeners can receive disrupt the eavesdropper information acquisition, both be short of one cannot. Most of the physical security method will be based on one or some hypothesis, some make assumptions to the position of the eavesdropper is limited, some assumption of signal attenuation level limit, although simplifies the analysis of the difficulty, but in the practical application often can't meet these assumptions, the safety of the actual situation to find a suitable for general scheme is imperative, this is the physical security research of the difficulty. Taking more into the system (MIMO) as the research basis, by many artificial noise by adding implementation method to improve security features, combined with the related knowledge of matrix projection in the matrix theory, realize the basic noise power allocation, complete the relevant simulation calculations, to improve the physical security of wireless network research purposes. Reference | Related Articles | Metrics

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A Rapid Method for WebShell Attack Success Determination Based on Web Page Structural Similarity Journal of Information Security Reserach    2026, 12 (3): 255-.   Abstract （28）      PDF （1396KB）（23）       Knowledge map    Save WebShell attack, a type of network attack, can control the website completely for a long time after a successful attack, which is extremely harmful. Most of the previous studies have concentrated on detecting and alerting WebShell attack traffic without distinguishing whether the attack is ultimately successful. As a result, in actual network security protection and monitoring work, security personnel are overwhelmed by a large number of WebShell attack alerts and are prone to alert fatigue, making it difficult to filter out successful WebShell attacks which are truly threatening. To address the problem, this paper proposes an anomaly detection method based on Web page structural similarity to quickly determine whether WebShell attacks are successful. Based on the structural information of the response pages of failed WebShell attack traffic, this method uses the HuntSzymanski algorithm to calculate structural similarity and then generate Web page templates. During the detection phase, this method uses the generated Web page templates for pattern matching and similarity assessment to determine whether the WebShell attacks are successful. It can well distinguish between successful and failed WebShell attack traffic, achieving an accuracy rate of 99.02% and a recall rate of 99.37%. This method has been applied to Wukong network security defense system and realizes rapid identification of successful WebShell attacks. Reference | Related Articles | Metrics

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A Colors Based Algorithm for License Plate Location Journal of Information Security Research    2016, 2 (1): 58-65.   Abstract （318）      PDF （5707KB）（675）       Knowledge map    Save Nowadays processing methods for license plate usually convert photos to gray scale images at first, and then find the characteristics based on the character of the edge texture for positioning. These methods do not work well on some conditions that there are the disturbance near the license plate, the instability of the light illumination and character edge gradient caused by floating dust. Then if it is in the fog and haze, these methods are more powerless. For that, in this paper a color based location algorithm is proposed, which is to select the candidate region according to the pixel color similarity and color domain in different color spaces and then based on a variety of geometric features to select the license plate region. This algorithm realizes the location of being at different light conditions, the strong interference of complex background and damaged license plates. Even in the fog and haze, this method performs excellent for those extremely blurred image. Reference | Related Articles | Metrics

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Research on Data Classification and Grading Method Based on Data Security Law Journal of Information Security Reserach    2021, 7 (10): 933-.   Abstract （1637）      PDF （2157KB）（1082）       Knowledge map    Save The Data Security Law of the People's Republic of China (hereinafter referred to as the Data Security Law) has been formally promulgated, which clearly stipulates that the state establishes data classification and grading protection system, and implements classified and graded protection for data. However, at present, the relevant standards and specifications of data classification and grading in China are relatively lacking, and the practical experiences that can be used for reference in various industries are relatively insufficient. How to effectively implement the data classification and grading protection is still a thorny problem. Based on Article 21 of the Data Security Law, this paper analyzes the factors such as the influence object, influence breadth and influence depth after the data is damaged, puts forward the principles and methods of data classification and data grading, and gives an implementation path of data classification and grading according to the application scenarios and industry characteristics of the data, which provide a certain reference for data classification and grading protection of various industries. Reference | Related Articles | Metrics

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Log Anomaly Detection Based on Graph Attention Networks and Collaborative Learning Journal of Information Security Reserach    2026, 12 (3): 246-.   Abstract （31）      PDF （2138KB）（21）       Knowledge map    Save Log anomaly detection plays a crucial role in the field of cybersecurity, yet existing methods still face significant challenges. Supervised learning approaches depend on large amounts of labeled data, making the annotation process timeconsuming and costly. Although unsupervised learning methods do not require labeled data, they struggle to effectively extract key features in complex log environments, which negatively impacts detection performance. To address these issues, this paper proposes a novel knowledge distillation approachcollaborative learningand introduces a log anomaly detection model based on this approach, CoLogGNN. The model first converts log data into a directed graph to comprehensively preserve the structural relationships between logs. During the early stages of training, CoLogGNN performs unsupervised learning on normal samples to explore the intrinsic structure of logs. In the mixedsample training phase, the graph attention network and the graph convolution module collaborate with each other and guide one another. When the graph attention network excels at processing certain samples, it transfers key knowledge to the graph convolutional network through collaborative learning, and vice versa. Through this dynamic mutual learning process, both modules improve their accuracy. Compared to existing models, CoLogGNN achieves effective training using only normal samples, significantly reducing the cost of data annotation. Experimental results on five public datasets demonstrate that the proposed model exhibits superior detection performance, improving the F1score by approximately 5% over previous methods. Reference | Related Articles | Metrics

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Overview on SM4 Algorithm Journal of Information Security Research    2016, 2 (11): 995-1007.   Abstract （1757）      PDF （8653KB）（1143）       Knowledge map    Save SM4 Algorithm, short for SM4 Block Cipher Algorithm, was published in 2006 to promote the application of WAPI. It became a cryptography industrial standard (GMT 0002—2012) in March 2012 and a national standard (GBT 32907—2016) in August 2016. This paper describes SM4s calculating process, structural features and cryptographic properties. Furthermore, we introduce some latest researches on SM4s security and compare SM4s security with several international block cipher standards such as AES, HIGHT and MISTY1. Reference | Related Articles | Metrics

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A Symbioticbased Framework for AI Safety Governance Journal of Information Security Reserach    2025, 11 (10): 897-.   Abstract （160）      PDF （2070KB）（64）       Knowledge map    Save Artificial intelligence technology is currently developing at an unprecedented pace, with safety concerns becoming a global focal point. Traditional AI safety research has predominantly relied on a “control paradigm”, emphasizing limitations, regulations, and value alignment to control AI behavior and prevent potential risks. However, as AI capabilities continue to strengthen, unidirectional control strategies are revealing increasingly significant limitations, with issues such as transparency illusions, adversarial evolution, and innovation suppression gradually emerging. Industry leaders like Sam Altman and Dario Amodei predict that AI may comprehensively surpass human capabilities in multiple fields within the next 23 years, making the reconstruction of AI governance paradigms particularly urgent. This paper proposes a new perspective—the “symbiotic paradigm”—emphasizing humanmachine collaboration as the core and understanding and trust as the foundation. Through establishing four pillars: transparent communication, bidirectional understanding, creative resonance, and dynamic boundaries, it promotes AI safety’s transition from control to cocreation, serving as one of the foundational paths for digital governance transformation. This paper systematically demonstrates the feasibility and necessity of the symbiotic paradigm through four dimensions: theoretical analysis, technological paths, practical cases, and governance recommendations, aiming to provide a sustainable alternative for future AI safety research and digital governance practices. Reference | Related Articles | Metrics

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Research on Highperformance Cryptographic Algorithms in Privacy Computation Journal of Information Security Reserach    2026, 12 (3): 274-.   Abstract （38）      PDF （1463KB）（20）       Knowledge map    Save With the rapid development of the digital economy, efficiently utilizing data while preserving privacy has become a critical challenge in modern technological advancement. Privacy computing, as a critical technical framework to address the contradiction between data availability and invisibility, is gradually transitioning from theory to practical application. Among its core technologies, homomorphic encryption, zeroknowledge proofs, and secure multiparty computation have made significant progress in both theoretical development and engineering implementation, demonstrating broad applicability in highperformance computing environments. This paper presents a comprehensive review of these three categories of highperformance encryption algorithms, focusing on their research progress and analyzing them across three dimensions: computational efficiency, communication overhead, and adaptability to highperformance computing environments. The analysis results indicate that homomorphic encryption is wellsuited for noninteractive data processing tasks with strong autonomy, although it incurs high computational and communication costs; zeroknowledge proofs exhibit high verification efficiency, making them suitable for highconcurrency scenarios, but still face performance bottlenecks in proof generation; secure multiparty computation excels in multiparty collaborative computing and has recently become feasible for deployment through protocol optimization and hardware support. This paper compares the performance and applicability of these algorithms, and explores future research directions, including the dynamic balance between generality and specialization of algorithms, as well as the multidimensional tradeoffs among performance, security, and interpretability, providing guidance for the future design and deployment of highperformance encryption algorithms. Reference | Related Articles | Metrics

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One-time Encryption Algorithm Based on Finite Field Key Exchange Journal of Information Security Reserach    2023, 9 (5): 457-.   Abstract （190）      PDF （516KB）（125）       Knowledge map    Save This paper presents a feasible solution to the worldwide problem of implementing onetime encryption. The scheme uses a finite field key exchange algorithm (i.e., public key cryptography algorithm) with the order of Mersenne prime proposed by me. The sender and the receiver do not need to preallocate, transmit and store symmetric keys, but only require the sender and the receiver to disclose their public keys and keep their private keys secret. The private keys and related public keys are changed every time they communicate, which fully realizes the perfect confidentiality of one key at a time. The finite field public key cryptography algorithm with the order of Mersenne prime is based on modulo2 operation, which is convenient for software and hardware implementation. Theoretical analysis and computational simulation have proved its effectiveness, and it has a wide range of theoretical and practical application value. Reference | Related Articles | Metrics

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Research on the Technology Architecture of Enterprise Trust Service Based On Trusted Identity Authentication Journal of Information Security Research    2017, 3 (9): 832-840.   Abstract （369）      PDF （7168KB）（184）       Knowledge map    Save With the development of enterprises, the enterprise information system construction develops rapidly, The importance of enterprise information security has become more and more important. In order to deal with the complex network environment, and accessing a variety of service system with external users, independent enterprise security is established respectively, with different complexity of user management system and application login system. These systems vary in safety strength. To solve the problem of corporate identity management, by the way, it takes some problems about the organization of the enterprise confusion, and user information dispersal. Faced with the dilemma of the development of enterprise information, this paper proposes a trusted service management system based on the trusted identity management and authentication framework. Based on the trusted identity of enterprise users, a series of related services such as identity authentication, single sign on, access control, authorization management, authentication service, and so on, are completed. Through a single point of logon enterprise application system, the realization of the enterprise internal users access to business applications, "a certification, the whole network access". And on this basis, the construction of public trust services is completed. As the basis of enterprise information security, the system architecture speeds up the process of enterprise information, helps business development. Reference | Related Articles | Metrics

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Safety Status and Solution of Coal Mine Industrial Control System Journal of Information Security Research    2019, 5 (8): 656-662.   Abstract （196）      PDF （4047KB）（418）       Knowledge map    Save AbstractWith the rapid development of automation and informatization in coal industry, the development speed of network security in coal industry is far behind the speed of informatization. Through the indepth analysis of the business structure and main control systems of the coal industry, the paper identifies 14 impacts of the current industrial control system of the coal industry, such as lack of overall information security planning, lack of border protection, abuse of mobile peripherals, lack of vulnerability patch updating, imperfect security strategy configuration, lack of or unreasonable security management system, etc. Aiming at the safety problems of industrial control and according to the design ideas of “network dedication, security zoning, white list baseline, defense in depth, comprehensive audit”, the paper proposed the design and solution of the security architecture applicable to coal mine industrial control system from the aspects of border protection, terminal security, configuration security, operation and maintenance security, flow audit, safety management, etc. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2026, 12 (2): 98-.   Abstract （101）      PDF （532KB）（79）       Knowledge map    Save Related Articles | Metrics

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“Internet Plus” Mobile Power: Analysis the Network Security of ZTE Journal of Information Security Research    2016, 2 (4): 288-298.   Abstract （995）      PDF （1637KB）（1353）       Knowledge map    Save Related Articles | Metrics

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Evidence Extraction of USB Storage Device Accessing Traces under the Windows 7 System Journal of Information Security Research    2016, 2 (4): 333-338.   Abstract （406）      PDF （5162KB）（848）       Knowledge map    Save With the rapid development and popularization of computer technology, cyber crimes come one after another，there are a lot of computer evidences existing in the USB storage device. When USB storage device has access to computers, registry keys and computer log will record the accessing traces. Therefore, computer forensic investigators can accordingly confirm which USB device has connected to the computer at what time. This paper introduces the position of accessing traces and extraction methods, providing great support and help for certain evidence factors in judicial activities. Reference | Related Articles | Metrics

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Study of Atomic Spin Entanglement in Optical Lattices Journal of Information Security Research    2017, 3 (1): 53-59.   Abstract （319）      PDF （6006KB）（465）       Knowledge map    Save Multipartite entanglement is the key resource for quantum computation. Ultracold atoms in optical lattices provide a clean and tunable platform for generating scalable entangled states. We report the experimental progress on the creation and detection of atomic spin entanglement. Our experiment represents a fundamental step towards quantum computation with ultracold atoms in optical lattices. Related Articles | Metrics

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An Overview of Application and Technology of Artificial Intelligence in Cybersecurity Journal of Information Security Reserach    2022, 8 (2): 110-.   Abstract （2108）      PDF （1142KB）（1442）       Knowledge map    Save Compared with the developed countries, the basic research and technology application in the field of artificial intelligence in China started later, especially the application of artificial intelligence in the important field of network security. Domestic and abroad disparity is still very obvious, which seriously affects the improvement of China's cybersecurity capability. This paper elaborates the relationship between artificial intelligence, network attack and network defense, and widely investigates the application status of artificial intelligence in major information security companies at home and abroad. It points out that APT detection, 0day vulnerability mining and cloud security are three core areas that affect the level of cybersecurity capability, This paper deeply analyzes the key technologies of artificial intelligence technology applied in these three fields, and puts forward the safety risks of artificial intelligence technology, and points out that artificial intelligence technology is not a panacea for all diseases, This Paper provides a scientific reference for the further research and application of artificial intelligence technology in China's information security industry. Reference | Related Articles | Metrics

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Evolution Research of Network Security Technology in Big Data Era Journal of Information Security Research    2019, 5 (5): 406-413.   Abstract （188）      PDF （1284KB）（552）       Knowledge map    Save With the advent of the era of big data, information systems have exhibited some new features, including boundary obfuscation, system virtualization, unstructure and diversification, and the low coupling degree of function and data. These features not only lead to a big difference between big data technology (DT) and information technology (IT), but also promote the upgrading and evolution of network security technology. In response to these changes, in this paper we compare the characteristics between IT era and DT era, and then propose four DT security principles: privacy, integrity, traceability, and controllability, as well as active and dynamic defense strategy based on “propagation prediction, tracking audit, dynamic management and control”. We further discusses the security challenges faced by DT and the corresponding assurance strategies. On this basis, the big data security technologies can be divided into four levels: “elimination, continuation, improvement, and innovation”, and we provide analyzation, combination and explaination for these technologies according to six categories: access control, identification and authentication, data encryption, data privacy, intrusion prevention, security audit and disaster recovery. These results will offer important assistance for the evolution of security technologies in the DT era, the construction of big data platform, the designation of security assurance strategies, and technology suitable for big data. Reference | Related Articles | Metrics

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Journal of Information Security Reserach    2025, 11 (E1): 171-.   Abstract （74）      PDF （612KB）（23）       Knowledge map    Save 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 （68）      PDF （2173KB）（54）       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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Study of Finger Vein Recognition Application Journal of Information Security Research    2016, 2 (1): 86-92.   Abstract （595）      PDF （5765KB）（720）       Knowledge map    Save With the national attention on public safety and information security, biometric technology has been gradually integrated into every aspect of peoples work and life. Based on the lots of advantages, such as natural living, difficult theft, difficult imitation and etc., fingervein recognition technology becomes the research focus for the research institutions and enterprises. With the development of technology, Chinas finger vein recognition technology has reached the world firstclass level.Based on the research resultsr on finger vein recognition for years, the paper has described the theory, advantage, system and terminal equipment of finger vein recognition, compared current development of the domestic and foreign finger vein recognition technology, and pointed out the future application direction of finger vein recognition. It can be predicted that the finger vein recognition can be more applied to peoples work and life. Reference | Related Articles | Metrics

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Differential Privacy and Applications Journal of Information Security Research    2015, 1 (3): 224-229.   Abstract （1238）      PDF （5750KB）（1238）       Knowledge map    Save As the emergence and development of application requirements such as data analysis and data publication, a challenge to those applications is to protect private data and prevent sensitive information from disclosure. With the highspeed development of information and network, big data has become a hot topic in both the academic and industrial research, which is regarded as a new revolution in the field of information technology. However, it brings about not only significant economic and social benefits, but also great risks and challenges to individuals` privacy protection and data security. People on the Internet leave many data footprint with cumulatively and relevance. Personal privacy information can be found by gathering data footprint in together.Malicious people use this information for fraud. It brings many trouble or economic loss to personal life.Privacy preserving, especially in data release and data mining, is a hot topic in the information security field. Differential privacy has grown rapidly recently due to its rigid and provable privacy guarantee. We analyze the advantage of differential privacy model relative to the traditional ones, and review other applications of differential privacy in various fields and discuss the future research directions. Following the comprehensive comparison and analysis of existing works, future research directions are put forward. Reference | Related Articles | Metrics

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Overview on SM9 Identity Based Cryptographic Algorithm Journal of Information Security Research    2016, 2 (11): 1008-1027.   Abstract （3695）      PDF （13949KB）（6204）       Knowledge map    Save SM9 identitybased cryptographic algorithm is an identitybased cryptosystem with bilinear pairings. In such a system the user s private key and public key may be extracted from user s identity and key generation centers parameters. The most common cryptographic uses of SM9 are with digital signature, data encryption, key exchange protocol and key encapsulation mechanism etc. The application and management of SM9 will not require digital certificate, certificate base, and key base. The key length of the SM9 cipher algorithm is 256b. SM9 cryptographic algorithm was issued as the cryptography standard in 2015. This paper will summarize the design, algorithm, software and hardware implementation and cryptanalysis of SM9 cryptographic algorithm. We also give some concrete examples in appendix. 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 （1426）      PDF （1395KB）（1345）       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 ECDSA Key Recovery Attacks Based on the Extended  Hidden Number Problem Journal of Information Security Reserach    2026, 12 (2): 174-.   Abstract （66）      PDF （797KB）（36）       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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Wang Gang Journal of Information Security Research    2015, 1 (1): 86-91.   Abstract （338）      PDF （4279KB）（576）       Knowledge map    Save Related Articles | Metrics

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Survey of Hash Functions Wang Xiaoyun1,2 and Yu Hongbo3 Journal of Information Security Research    2015, 1 (1): 19-30.   Abstract （1802）      PDF （11279KB）（3887）       Knowledge map    Save One of the fundamental primitives in modern cryptography is the cryptographic hash functions, often informally called hash functions. They are used to compress messages of arbitrary length to fixed length hash values which are also called hash codes, message digests or digital fingerprints. A primary motivation for cryptographic hash functions is that they serve as compact representative images of input messages, which they can uniquely identify. Changing a single letter will change most of the digits in the hash code. The most common cryptographic uses of hash functions are with digital signature and for data integrity. Hash functions are frequently used in digital signature schemes to compress large messages for processing by public-key cryptosystems such as RSA. They are also used to design message authentication codes (MACs) and many secure cryptographic protocols. Hash functions occur as components in various cryptographic applications (e.g. protection of pass-phrases, protocols for payment, broadcast authentication etc.), where usually their property as a computational one-way function is used. So the study of the hash functions is of great significance in the cryptanalysis field. 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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Smartphone Image Recovery and Forensics Based on WinHex Journal of Information Security Research    2016, 2 (4): 328-332.   Abstract （463）      PDF （4459KB）（725）       Knowledge map    Save Smartphone has gradually become one of important sources of information in the current electronic forensics investigation. Aiming at the difficult problem of information acquisition when the picture of the Android smartphone was deleted or damaged, a file recovery method based on WinHex tools is provided. In experiments, by creating a cell phone store image and the header and tail sign of file, the phone's image files were extracted. Reference | Related Articles | Metrics

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Management and Directed Study of Internet Public Opinion in the Age of Big Data Journal of Information Security Research    2016, 2 (4): 356-360.   Abstract （502）      PDF （4303KB）（711）       Knowledge map    Save As we step into the age of big data，Internet Public Opinion has undergone great changes in terms of data volume，complexity and production speed. In big data Era, its internal features and potential rules during the changing process should be controlled correctly. This paper has important theoretical significance and practical value in guiding internet public opinion and protecting cyber security under the new circumstances. In the Internet era of big data, with the help of computer technology, timely, comprehensive monitoring network public opinion is imminent. We would first discuss the new changes of network public opinion brought by big data, public opinion then elaborated coping strategies, At last, the paper introduces the design idea of the network public opinion monitoring system based on Crawler Web and Lucene. Reference | Related Articles | Metrics