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10 March 2022, Volume 22 Issue 3 Previous Issue    Next Issue

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Crowd Spectrum Sensing Reinforcement Scheme Against Primary-secondary Collusive Attack in Smart Grid FENG Jingyu, SHI Yifei, WANG Teng 2022, 22 (3):  1-9.  doi: 10.3969/j.issn.1671-1122.2022.03.001 Abstract ( 361 )   HTML ( 32 )   PDF (1069KB) ( 141 )   Spurious data injection is regarded as one of the most serious threats in the crowd spectrum sensing of smart grid. To combat such threats, this paper proposed a two-level defense reinforcement scheme against primary-secondary collusive attack. Primary user(PU) authentication was adopted to construct the first layer of defense reinforcement, in which the identity-based cryptography signature was designed to prevent attackers from impersonating a PU. Meanwhile, the trust value of PU was introduced to detect the initiator of primary-secondary collusive attack. The MAD cluster analysis algorithm was designed to realize the construction of the second layer of defense reinforcement, the secondary user(SU) trust should be calculated by different PUs. The result of SU trust evaluation was no longer a single value, but a set of individual SU trust values. For an SU, its individual trust values could compose a trust vector. By adopting the distance among trust vectors to perform cluster analysis and detect primary-secondary collusive attack conspirators, simulation results show that the two-level defense reinforcement scheme can enhance the accuracy of SU trust evaluation, and successfully reducing the malicious responses of primary-secondary collusive attack. Figures and Tables | References | Related Articles | Metrics

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The Security Reference Model of the Multi-rotor UAV System LI Guoqi, HONG Sheng, LAN Xueting, ZHANG Hong 2022, 22 (3):  10-19.  doi: 10.3969/j.issn.1671-1122.2022.03.002 Abstract ( 432 )   HTML ( 29 )   PDF (1974KB) ( 225 )   In recent years, the information security of UAV has attracted much attention, but there is still no complete reference model. This paper selected multi-rotor UAV system as the research object. Firstly, according to the method of deriving the security reference model of Internet of things, the information security reference model framework of multi-rotor UAV system was derived. Secondly, on the basis of comprehensively analysis on the system composition and information security risks of multi-rotor UAV, the effect of security attacks on flight safety was divided into four categories and marked on the reference model. The obtained information security reference model could be used as the basis and reference for malicious attack oriented safety design, analysis and verification of multi-rotor UAV system. The research method ology introduced in this paper also contributes to the information security research of other types of UAV and other complex CPS or Internet of things systems. Figures and Tables | References | Related Articles | Metrics

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A Lightweight Cross-domain Mutual Authentication Scheme in V2G Networks SHI Runhua, WANG Shuhao, LI Kunchang 2022, 22 (3):  20-28.  doi: 10.3969/j.issn.1671-1122.2022.03.003 Abstract ( 320 )   HTML ( 10 )   PDF (1161KB) ( 346 )   Considering the problem of identity privacy leakage during charging and discharging between vehicles and grids, this paper proposes a cross-domain identity authentication scheme for vehicles in V2G. In this paper, elliptic curve encryption(ECC) algorithm and elliptic curve digital signature algorithm(ECDSA) are used to ensure the privacy of data and the authenticity of identities among grid servers, and use the blockchain to host the server public key certificate. For the authentication between the charging pile and the grid server, the faster symmetric encryption algorithm(AES) and message authentication code(MAC) are used to ensure the privacy and authenticity of the data. The scheme also uses the physical unclonable technology PUF lightweight and anti-physical attack characteristics to achieve the practicability and effectiveness of the scheme. Finally, compared with other schemes and experimental simulations, this scheme has better security, integrity, light weight and efficiency. Figures and Tables | References | Related Articles | Metrics

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System Attack Surface Modeling Method in Network GU Zhaojun, YANG Rui, SUI He 2022, 22 (3):  29-38.  doi: 10.3969/j.issn.1671-1122.2022.03.004 Abstract ( 344 )   HTML ( 29 )   PDF (1334KB) ( 218 )   Aiming at the problems that the air traffic control information system is isolated from the Internet and the use of public released vulnerability information cannot effectively reflect its network security, this paper proposed a risk measurement model of air traffic management information system at the network level. The dimension of attack surface modeling had ports, protocols, data for each resource component. This model used Bayesian network to represent the relationship among resources to establish resource graph. Each resource component’s attack surface and vulnerability severity based on resource graph were fused into network attack surface triple. It represented the threat level of three dimensions and calculated the overall risk of the network architecture. Simulation experiments were carried out in the air traffic management automation system. Experiments quantified the threat situation of the system in different attack paths and dimensions. Besides, the network structure risk was analyzed from different angles and levels. Experimental results demonstrate the rationality and practical effectiveness of the proposed system attack surface risk assessment method. The attack surface model provides guidance for network security measures of air traffic management information system. Thus, security administrator can maximize system security under finite conditions. Figures and Tables | References | Related Articles | Metrics

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Key Technologies and Advances in the Research on Automated Exploitation of Computer System Vulnerabilities FENG Guangsheng, ZHANG Yizhe, SUN Jiayu, LYU Hongwu 2022, 22 (3):  39-52.  doi: 10.3969/j.issn.1671-1122.2022.03.005 Abstract ( 585 )   HTML ( 70 )   PDF (1058KB) ( 657 )   The security situation of cyberspace is becoming more and more complex. Security vulnerabilities exploded in the past few decades with the acceleration of software iteration. Facing with the challenge of hidden and numerous vulnerabilities, traditional methods relying on security experts to conduct assessments often requires huge manpower and material resources. Thus, how to efficiently find software vulnerabilities automatically, generate corresponding EXP (exploit) and make subsequent usage have become a hot spot which attracts widespread attention. This paper aims to summarize the latest developments in the automated exploitation of vulnerabilities. First, this paper refines the related technologies for software vulnerabilities automated exploiting. Second, this paper reviews mainstream software vulnerability automated exploitation systems. Finally, this paper analyzes and summarize the current problems and prospect the future research. Figures and Tables | References | Related Articles | Metrics

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FPGA Realization of Physical Unclonable Function Based on Cross-coupling Circuit LI Li, LI Zequn, LI Xuemei, SHI Guozhen 2022, 22 (3):  53-61.  doi: 10.3969/j.issn.1671-1122.2022.03.006 Abstract ( 233 )   HTML ( 8 )   PDF (1299KB) ( 86 )   With the rapid increase in number of IoT devices and the continuous expansion of the applications range, the issue of information security of IoT devices has attracted more and more attention. PUF provided new ideas for solving data security issues in the operation of IoT devices. In order to solve the problem of insufficient number of challenge-response pairs in weak PUF and excessive resource consumption in strong PUF, a strong PUF consisting of the weak PUF, BCH code and LFSR is proposed, which has the advantages of high reliability, high uniqueness and less resources. The strong PUF with 128-bit response was implemented on a 40nm Alinx FPGA. With a 128-bit BCH code structure, the reliability of the strong PUF output response reaches 100%, and the uniqueness reaches 49.83%. Compared with L-PUF, the reliability of this PUF is increased by 3.7%, and the uniqueness is increased by 0.08%. Figures and Tables | References | Related Articles | Metrics

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An Improved JSMA Algorithm against Sample Attack Based on Logits Vector HU Wei, ZHAO Wenlong, CHEN Lu, FU Wei 2022, 22 (3):  62-69.  doi: 10.3969/j.issn.1671-1122.2022.03.007 Abstract ( 279 )   HTML ( 8 )   PDF (2203KB) ( 143 )   This paper studied the current typical JSMA against sample attack algorithm based on saliency graph, and proposes an improved JSMA against sample attack algorithm L-JSMA based on Logits vector. The algorithm proves that the attack effect is positively correlated with Logits ranking on MNIST data set and CIFAR-10 data set. In order to further verify the theory, attack the targets according to Logits on the Alexnet model and Inception-v3 model, and the conclusion is further proved. Through experimental analysis, it is found that the stronger the attack ability of JSMA derivative algorithm, the more it can make full use of the linear characteristics of neural network, and the stronger the linear correlation in the experimental results. Because neural networks have both linear and nonlinear characteristics, the attack effect is not strictly positively correlated with Logits. By discussing the nature of neural network of white box attack, it is helpful to understand the essential characteristics of neural network, and also referential for black box attack. Figures and Tables | References | Related Articles | Metrics

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A Defense Method against Adversarial Attacks Based on Neural Architecture Search ZHENG Yaohao, WANG Liming, YANG Jing 2022, 22 (3):  70-77.  doi: 10.3969/j.issn.1671-1122.2022.03.008 Abstract ( 228 )   HTML ( 13 )   PDF (1862KB) ( 219 )   Aiming at the problem that the neural networks are easy to misclassify under the attack of adversarial examples in the task of image classification, which leads to the unreliability of deep learning models, this paper proposed a defense method against adversarial attacks based on neural architecture search. This method used reinforcement learning to model the search of defense network as the behavior of the agent. Through the definition of search space, the design of search strategy, and the evaluation of subnetwork performance, the search network can automatically obtain the best performance network to reconstruct adversarial images and restore them to natural images, achieving the purpose of defense against adversarial attacks. The experimental results show that the method can effectively reconstruct illegal examples, and make them lose aggressiveness, and consequently ensure the classification accuracy of the classifier. Figures and Tables | References | Related Articles | Metrics

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Blockchain Abnormal Transaction Detection with Privacy-preserving Based on KNN CHEN Binjie, WEI Fushan, GU Chunxiang 2022, 22 (3):  78-84.  doi: 10.3969/j.issn.1671-1122.2022.03.009 Abstract ( 346 )   HTML ( 21 )   PDF (965KB) ( 294 )   With the development of blockchain, the consortium blockchain technology represented by Hyperledger has been applied widely, and its abnormal transaction detection needs have become prominent gradually. The current anomaly detection technology focuses on public blockchain, which neglects the privacy protection requirements of the consortium blockchain. In order to realize efficient anomaly detection and privacy protection of the consortium blockchain, this paper proposed a privacy-preserving abnormal transaction detection scheme based on KNN. The accounting nodes of this scheme used the matrix method to randomize the transaction data, and cloud server used KNN to test the randomized transaction data and feed back the result to accounting nodes for validation. The experimental results show that the scheme has little effect on the efficiency of the consortium blockchain, and has a good detection performance. The recall rate, precision and F1 value can reach 85.3%, 87.7% and 86.5% respectively. Figures and Tables | References | Related Articles | Metrics

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Internet Hirelings Semi-supervised Detection of Weibo Based on Affinity Propagation Algorithm LIN Yijun, WU Yu, LI Hongbo 2022, 22 (3):  85-96.  doi: 10.3969/j.issn.1671-1122.2022.03.010 Abstract ( 356 )   HTML ( 23 )   PDF (1749KB) ( 234 )   The research on the Internet hirelings accounts in Weibo contributes to purify cyberspace and maintain social stability. First of all, in view of the continuous evolution of the Internet hirelings in Weibo, the traditional feature set cannot cover the existing features of it. Therefore, the new features are constructed combined with the definition of the Internet hirelings and its original features. Then, in view of the difficulty of account annotation and the insufficient utilization of no annotation data, a semi-supervised recognition method of the Internet hirelings in Weibo (APDHW) is proposed, based on Affinity Propagation arithmetic. In this method, the recognition of the Internet hirelings in Weibo can be implemented through bringing Euclidean distance Radius threshold in Affinity Propagation arithmetic and combining support vector machine classification arithmetic. Through a number of experiments and empirical research, the results show that the recognition method of the Internet hirelings in Weibo proposed in this paper achieves a better recognition effect under the expense of a small amount of arithmetic time, and improves the accuracy and recall rate of the Internet hirelings recognition. Figures and Tables | References | Related Articles | Metrics