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NDFuzz:a non-intrusive coverage-guided fuzzing framework for virtualized network devices

Cybersecurity 2023年第1期6卷 54-74页

作者： Yu Zhang Nanyu Zhong Wei You Yanyan Zou Kunpeng Jian Jiahuan Xu Jian Sun Baoxu Liu Wei Huo Institute of Information Engineering Chinese Academy of SciencesBejingChina School of Cyber Security University of Chinese Academy of SciencesBejingChina Key Laboratory of Network Assessment Technology Chinese Academy of SciencesBeijingChina Beijing Key Laboratory of Network Security and Protection Technology BeijingChina Renmin University of China BeijingChina

Network function virtualization provides programmable in-network middlewares by leveraging virtualization tech-nologies and commodity hardware and has gained popularity among all mainstream network device *** it is challenging to apply coverage-guided fuzzing,one of the state-of-the-art vulnerability discovery approaches,to those virtualized network devices,due to inevitable integrity protection adopted by those *** this paper,we propose a coverage-guided fuzzing framework NDFuzz for virtualized network devices with a novel integrity protec-tion bypassing method,which is able to distinguish processes of virtualized network devices from hypervisors with a carefully designed non-intrusive page global directory inference *** implement NDFuzz atop of two black-box fuzzers and evaluate NDFuzz with three representative network protocols,SNMP,DHCP and NTP,on nine popular virtualized network *** obtains an average 36%coverage improvement in comparison with its black-box *** discovers 2 O-Day vulnerabilities and 11-Day vulnerability with coverage guidance while the black-box fuzzer can find only one of *** discovered vulnerabilities are confirmed by corresponding vendors.

关键词： Coverage-guided fuzzing Network devices Network function virtualization

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Seismic response comparison and sensitivity analysis of pile foundation in liquefiable and non-liquefiable soils

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Earthquake engineering and engineering Vibration 2023年第1期22卷 87-104页

作者： Jia Kemin Xu Chengshun Du Xiuli Cui Chunyi Dou Pengfei Song Jia Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education Beijing University of Technology Beijing 100124China Transportation Engineering College Dalian Maritime University Dalian 116026China North China University of Technology School of Civil Engineering Beijing 100144China

Case history investigations have shown that pile foundations are more critically damaged in liquefiable soils than non-liquefiable *** study examines the differences in seismic response of pile foundations in liquefiable and non-liquefiable soils and their sensitivity to numerical model parameters.A two-dimensional finite element(FE)model is developed to simulate the experiment of a single pile foundation centrifuge in liquefiable soil subjected to earthquake motions and is validated against real-world test *** differences in soil-pile seismic response of liquefiable and non-liquefiable soils are ***,the first-order second-moment method(FOSM)is used for sensitivity analysis of the seismic *** results show significant differences in seismic response for a soil-pile system between liquefiable and non-liquefiable *** seismic responses are found to be significantly larger in liquefiable soil than in non-liquefiable ***,the pile bending moment was mainly affected by the kinematic effect in liquefiable soil,while the inertial effect was more significant in non-liquefiable *** controlling parameters of seismic response were PGA,soil density,and friction angle in liquefiable soil,while the pile bending moment was mainly controlled by PGA,the friction angle of soil,and shear modulus of loose sand in non-liquefiable soil.

关键词： liquefiable non-liquefiable finite element analysis pile foundation seismic response sensitivity analysis

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Analytical solution for longitudinal response of cross-fault mountain tunnels based on foundation beam model

Analytical solution for longitudinal response of cross-fault...

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ITA-AITES World Tunnel Congress, WTC 2024

作者： Tao, Lianjin Qiu, Mingyang Zhang, Haixiang Jia, Zhibo Shi, Cheng The Key Laboratory of Urban Security and Disaster Engineering Ministry of Education Beijing University of Technology Beijing China Beijing Key Laboratory of Earthquake Engineering and Structural Retrofit Beijing University of Technology Beijing China

ISBN: (纸本)9781032800424

Tunnel crossing active fault is a common issue in mountain tunnels. Researching the analytical solutions for the longitudinal response of tunnels under fault dislocation is of great importance for disaster prevention in mountain tunnels. This paper summarizes the mechanical models for analytical solutions of longitudinal responses in tunnels crossing faults, compares the characteristics and applicable conditions of various foundation beam models, analyzes the key factors affecting the accuracy of the analytical solutions of foundation beam models, and finally proposes a general model for calculating longitudinal deformation in foundation beams. The results show that the current analytical solution models for foundation beams crossing faults seldom consider factors such as the form of fault sliding, tunnel joint methods, and external forces on tunnels. The general foundation beam model can introduce new parameters without changing the algorithm and enhance the efficiency of displacement analysis. This study provides guidance for subsequent displacement prediction and disaster prevention in mountain tunnels crossing active faults. © 2024 The Author(s).

关键词： Foundations

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A Survey of security Protection Methods for Deep Learning Model

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1533-1553页

作者： Peng, Haipeng Bao, Shuang Li, Lixiang Beijing University of Posts and Telecommunications Information Security Center State Key Laboratory of Networking and Switching Technology Beijing100876 China Beijing University of Posts and Telecommunications National Engineering Laboratory for Disaster Backup and Recovery Beijing100876 China

In recent years, deep learning (DL) models have attracted widespread concern. Due to its own characteristics, DL has been successfully applied in the fields of object detection, superresolution reconstruction, speech recognition, natural language processing, etc., bringing high efficiency to industrial production and daily life. With the Internet of Things, 6G and other new technologies have been proposed, leading to an exponential growth in data volume. DL models currently suffer from some security issues, such as privacy issues during data collection, defense issues during model training and deployment, etc. The sensitive data of users and special institutions that are directly used as training data of DL models may lead to information leakage and serious privacy problems. In addition, DL models have encountered many malicious attacks in the real world, such as poisoning attack, exploratory attack, adversarial attack, etc., which caused model security problems. Therefore, this article discusses ways of ensuring the security and data privacy of DL models under diversified attack methods and the ways of ensuring the privacy security of edge mobile devices equipped with pretrained deep neural networks. Alternatively, this article analyzes the privacy security of DL models for typical deployment platforms such as server/cloud, edge mobile device, and web browser and, then, summarizes future research direction. © 2020 IEEE.

关键词： Speech recognition

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Utilization of Basalt Saw Mud as a Spherical Porous Functional Aggregate for the Preparation of Ordinary Structure Concrete

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Journal of Wuhan University of technology(Materials Science) 2024年第2期39卷 364-375页

作者：周永祥关青锋 LENG Faguang WANG Jing LI Tianjun Faculty of Architecture Civil and Transportation EngineeringBeijing University of TechnologyBeijing 100124China Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education Beijing University of TechnologyBeijing 100012China School of Materials Science and Engineering Southeast UniversityNanjing 211189China Institute of Building Materials China Academy of Building ResearchBeijing 100013China State Key Laboratory of Building Safety and Built Environment Beijing 100013China Zhejiang Chinavigor E.P.Technology Co. Ltd.Zhejiang 315043China

To promote the production and application of artificial aggregates,save natural sand resources and protect the ecological environment,we evaluated the feasibility of using spherical porous functional aggregates(SPFAs) formed by basalt saw mud under autoclave curing in ordinary structural *** our work,two types of prewetted functional aggregates were taken as replacements for natural aggregates with different volume substitution rates(0%,5%,10%,15%,20%,25%,and 30%) in the preparation of ordinary structural concrete with water-to-binder ratios(W/B) of 0.48 and *** effects of the functional aggregate properties and content,W/B,and curing age on the fluidity,density,mechanical properties and autogenous shrinkage of ordinary concrete were *** experimental results showed that the density of concrete declined at a rate of not more than 5%,and the 28 d compressive strength could reach 31.0-68.2 *** W/B,long curing age and high-quality functional aggregates were conducive to enhancing the mechanical properties of SPFAs *** the rolling effects,SPFAs can optimize the particle gradation of aggregate systems and improve the fluidity of concrete,and the water stored inside SPFAs provides an internal curing effect,which prolongs the cement hydration process and considerably reduces the autogenous shrinkage of *** exhibits high strength and high density,as well as being more cost-effective and ecological,and is expected to be widely employed in ordinary structural concrete.

关键词： lightweight concrete civil concrete building basalt saw mud fly ash internal curing environmentally friendly

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Multi-field Coupling Simulation of Impact of Temperature and Density of Heat Injection Well on Carbon Budget during Hydrate Exploitation in Qilian Mountain Permafrost Region

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Journal of Earth Science 2024年第6期35卷 1934-1943页

作者： Zhenhua Han Ruirui Li Luqing Zhang Jian Zhou Song Wang Key Laboratory of Shale Gas and Geoengineering Institute of Geology and GeophysicsChinese Academy of SciencesBeijing100029China Innovation Academy for Earth Science Chinese Academy of SciencesBeijing100029China Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education Beijing University of TechnologyBeijing100124China

Permafrost regions of Qilian Mountains in China are rich in gas hydrate *** greenhouse gases in deep frozen layer are released into the atmosphere during hydrate mining,a series of negative consequences *** study aims to evaluate the impact of hydrate thermal exploitation on regional permafrost and carbon budgets based on a multi-physical field coupling *** results indicate that the permeability of the frozen soil is anisotropic,and the low permeability frozen layer can seal the methane gas in the natural *** injection mining of hydrates causes the continuous melting of permafrost and the escape of methane gas,which transforms the regional permafrost from a carbon sink to a carbon source.A higher injection temperature concentrates the heat and causes uneven melting of the upper frozen layer,which provides a dominant channel for methane gas and results in increased methane ***,dense heat injection wells cause more uniform melting of the lower permafrost layer,and the melting zone does not extend to the upper low permeability formation,which cannot provide advantageous channels for methane ***,a reasonable and dense number of heat injection wells can reduce the risk of greenhouse gas emissions during hydrate exploitation.

关键词： permafrost gas hydrates carbon budget methane emissions greenhouse gases environmental effects multi-field coupling simulation

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A bitcoin service community classification method based on Random Forest and improved KNN algorithm

IET Blockchain

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IET Blockchain 2024年第3期4卷 276-286页

作者： Gao, Muyun Lin, Shenwen Tian, Xin He, Xi He, Ketai Chen, Shifeng School of Mechanical Engineering University of Science and Technology Beijing Beijing China Internet Financial Security Technology Key Laboratory National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing China

There are service communities with different functions in the Bitcoin transactions system. Identifying community categories helps to further understand the Bitcoin transactions system and facilitates targeted regulation of anonymized Bitcoin transactions. To this end, a Bitcoin service community classification method based on Random Forest and improved K-Nearest Neighbor (KNN) algorithm is proposed. First, the transaction characteristics of different types of communities are analyzed and summarized, and the corresponding transaction features are extracted from the address and entity levels;then multiple classification algorithms are compared, the optimal model to filter the effective features is selected, and the feature vector of entity addresses is constructed. Finally, a classification model is constructed based on Random Forest and improved KNN algorithm to classify the entities. By constructing different classification models for experimental comparison, the accuracy and stability advantages of the proposed method for classification in service community classification research are verified. © 2024 The Authors. IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of engineering and technology.

关键词： Classification (of information)

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Design of a 9-DOF Radiation Resistant Robot for Nuclear Reactors’ Decommissioning 2nd

Design of a 9-DOF Radiation Resistant Robot for Nuclear Reac...

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2nd International Conference on the Frontiers of Robotics and software engineering, FRSE 2024

作者： Wu, Tong Wang, Deying Yang, Haiyan Chen, Xu Zhang, Liang Mi, Zhifeng Beijing100048 China Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education Beijing University of Technology Beijing China

ISBN: (纸本)9789819630127

Due to the expiration of the design service life of some nuclear facilities, a large number of hazardous radioactive devices need to be dismantled. Therefore, special attention needs to be paid to the safety and reliability of the dismantling process to ensure the protection of workers and the environment. In response to this challenge, this article proposes an innovative solution: a 9-DOF (Degrees of Freedom) nuclear decommissioning robot composed of a 3-DOF gantry and a 6-DOF robotic arm. The core of this robot design lies in utilizing its high redundancy of 9 DOFs and the intelligence of machine learning to perform complex dismantling tasks. At the same time, to ensure the accuracy and safety of the operation, a forward and inverse kinematics analysis of the robot is required to gain a detailed understanding of its motion capabilities and limitations, making it more suitable for dismantling work in nuclear facilities. The ultimate goal of this research is to effectively recycle graphite reactors. Experiments show that the method of using this 9-DOF nuclear decommissioning robot combined with the RRT (Rapidly-exploring Random Tree) algorithm for path planning has certain feasibility in practical applications. This not only demonstrates the theoretical effectiveness of this technical solution, but also provides important reference value for future practical applications. Through this method, we can safely and effectively handle decommissioned nuclear facilities, thus reducing the potential threat of nuclear radiation to the environment and human health. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Inverse kinematics

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Robot Path Optimization Method for Nuclear Reactor Decommissioning 2nd

Robot Path Optimization Method for Nuclear Reactor Decommiss...

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2nd International Conference on the Frontiers of Robotics and software engineering, FRSE 2024

作者： Wu, Tong Wang, Deying Chen, Fengjuan Lv, Kefu Wang, Jin Lu, Fan Mi, Zhifeng Beijing100048 China Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education Beijing University of Technology Beijing China

ISBN: (纸本)9789819630127

Addressing the issues of complex demolition environments in nuclear facility decommissioning projects, the difficulty of achieving multi-axis linkage for robotic arms, and low work efficiency, an optimization method that can autonomously reduce the moving joints of robotic arms and autonomously find the best cutting path is proposed. This method can effectively solve for the cutting path that requires the fewest moving joints and improve work efficiency. Firstly, forward and inverse kinematics analysis is conducted on the robotic arm, dividing it into two parts: the pedestal and the arm. The pedestal is responsible for moving and cutting, while the arm adjusts the posture. Secondly, for the arc and straight trajectories during the cutting process, corresponding motion synthesis is performed on the pedestal. The inverse kinematics of the arm is solved using a genetic algorithm based on the principle of minimizing the degree of freedom of motion, achieving cutting with the fewest moving joints. Finally, BP neural network is used to simulate and train the solved data samples, establishing a path optimization model that realizes optimization of the cutting path for the robotic arm. This algorithm provides reference significance for nuclear facility decommissioning robots to autonomously reduce the degrees of freedom required for cutting. Through simulation verification of a certain area inside a reactor, the simulation results show that the algorithm is reasonable and reliable. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Inverse kinematics

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Multivariate Time Series Anomaly Detection Based on Spatial-Temporal Network and Transformer in Industrial Internet of Things

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Computers, Materials & Continua 2024年第8期80卷 2815-2837页

作者： Mengmeng Zhao Haipeng Peng Lixiang Li Yeqing Ren Information Security Center State Key Laboratory ofNetworking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China National Engineering Laboratory for Disaster Backup and Recovery Beijing University of Posts and TelecommunicationsBeijing100876China Department of Information Science and Engineering Zaozhuang UniversityZaozhuang277160China

In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working *** the systems are attacked,timely identification of outliers in time series is critical to ensure *** many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these *** to the superior capability of Transformer in learning time series *** paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved ***,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are ***,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each *** scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each *** interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory *** introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph *** on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.

关键词： Multivariate time series anomaly detection spatial-temporal network Transformer

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