检索结果-内蒙古大学图书馆

Vulnerability Digging for Software-Defined Network Controller Using Event Flow Graph Analysis

Security and Communication Networks 2022年第0期2022卷

作者： Wu, Zehui Zhang, Wenbin Wang, Yunchao Yan, Chenyu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Software-defined network (SDN) controllers, the core of SDN network architecture, need to deal with network events of the whole network, which has huge program state space and complex logic dependency, with security issues related. Vulnerabilities in the SDN controller can paralyze the whole network. Existing controller testing methods are difficult to dig into the hidden logic vulnerability for their ignorance of the complex events interactions among controllers, apps, and data plane inputs. Different from file processing software, network software is driven by events, and the event flow can more accurately and comprehensively reflect the execution process. In this work, we propose an SDN controller vulnerability digging method based on event flow graph analysis. The proposed method consists of three main steps: first, we execute the instrumented controller in a normal environment and generate event flow graphs and then extract their features as reference. Second, we generate and execute test cases using the fuzzing method and dig the newly built event flow graphs with potential vulnerabilities. Finally, we manually examine and validate the potential vulnerabilities. To accurately discover abnormal subgraphs, we utilize graph feature extraction and analysis technologies, such as graph mining and clustering, to distinguish the normal graph and abnormal graph. We implement our method on the Ryu controller and compare it with other SDN testing methods, such as BEADS and Delta. The evaluation indicates that our method uncovered three new vulnerabilities that other methods failed to find. © 2022 Zehui Wu et al.

关键词： Controllers

来源：评论

学校读者我要写书评

暂无评论

Association Analysis of User Promiscuous Traffic Based on Convolutional Neural Network 4

Association Analysis of User Promiscuous Traffic Based on Co...

引用

4th IEEE advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021

作者： Li, Yonglin Liu, Yan Zhengzhou University Zhong Yuan Network Security Research Institute Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781728185347

Analyzing user behavior from promiscuous network traffic, digging out user characteristics, and analyzing user behavior patterns are the main purposes of user association analysis. Existing methods start from the traffic generated by users and manually select the features that need to be extracted with the help of expert knowledge, the effect of the model depends to a certain extent on the quality of the selected features. This paper proposes a convolutional neural network-based user promiscuous traffic association analysis method Convolutional Neural Networks Based Association Analysis (CNNBAA). First, the traffic generated by users surfing the internet is preprocessed, such as segmentation, anonymization, and an interception, and then mapped into RGB map as the input data of Convolutional Neural Networks (CNN), and then use Residual Networks (ResNet) train the generated images to obtain a network model that can independently learn the characteristics of user online behavior. This method does not require manual selection of features and uses a convolutional neural network to learn features autonomously. We collected the network traffic in the true environment, constructed the experimental data set, and obtained the best traffic segmentation method and the best image conversion resolution through experiments. The experimental results show that the accuracy of the model is above 88%, which achieves the expected effect. © 2021 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

SPAFuzz: Web Security Fuzz Testing Tool Based on Fuzz Testing and Genetic Algorithm 4

SPAFuzz: Web Security Fuzz Testing Tool Based on Fuzz Testin...

引用

4th International Conference on Consumer Electronics and Computer engineering, ICCECE 2024

作者： Lin, Jiang Dong, Weiyu School of Computer Science and Artificial Intelligence Zhengzhou University Zhengzhou China Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9798350384062

Fuzzing is one of the most effective methods currently available for detecting web vulnerabilities. However, traditional fuzzing suffers from issues such as low coverage and limited diversity in test cases. To address these issues, we propose a way to generate test cases based on dynamic feature libraries and attack models by analysing the characteristics of SQL and XSS. Additionally, we introduce a genetic algorithm to guide the population's evolution by monitoring the state changes of the web application. Furthermore, we improved the selection phase of the genetic algorithm to optimally deform multiple iterations for use cases with low fitness values in order to preserve the population diversity to expand the attack capability of the test cases and based on this the SPAFuzz fuzzy testing tool was implemented. Experimental results show that SPAFuzz is able to detect more network vulnerabilities than Sqlmap and Powerfuzzer. © 2024 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

VulD-CodeBERT: CodeBERT-Based Vulnerability Detection Model for C/C++ Code 6

VulD-CodeBERT: CodeBERT-Based Vulnerability Detection Model ...

引用

6th International Conference on Communications, Information System and Computer engineering, CISCE 2024

作者： Xiong, Zhe Dong, Weiyu School of Computer Science and Artificial Intelligence Zhengzhou University Zhengzhou China Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9798350353174

Recently, deep learning techniques have received widespread attention in code vulnerability and vulnerability detection. However, there are some problems with current vulnerability detection techniques, firstly, because of the non-homogeneity of vulnerability categories and quantities, there are omission false positives and overfitting problems for vulnerabilities with a small amount of data. Second, the existing detection methods have limited ability to characterize the code, there is insufficient depth of characterization, does not contain all of its vulnerability characteristics or is interspersed with useless information. Finally, the current research does not use the powerful feature mining capability of pre-trained models and does not employ model fusion to increase the effectiveness of model vulnerability detection. To solve the above problems, this paper proposes a new deep learning based pre-trained model for code vulnerability detection tool VulD-CodeBERT. By fine-tuning CodeBERT, a code adaptation extension for pre-trained models developed by Microsoft, the CodeBERT model can solve the problem of not being able to learn the vulnerability patterns due to insufficient data, thus resulting in missed false alarms. The sequence output from the CodeBERT model are added to a BiLSTM network with an attention mechanism to mine the local key features of the vulnerabilities combined with the global features of the pooler output from the CodeBERT model to deeply mine the dependencies between the vulnerability statements and derive the probability of the existence of the vulnerability. For vulnerability types that are difficult to uncover captured features or the number of samples is not enough, a polynomial plain Bayesian classifier is used for detection, and finally the two models are combined to deeply mine the vulnerability features, thus solving the problem of difficult and small samples, and reducing the leakage rate and false alarm rate. Experimental results sh

关键词： C++ (programming language)

来源：评论

学校读者我要写书评

暂无评论

Directed Association-based User Identification Algorithm 2

Directed Association-based User Identification Algorithm

引用

2nd International Conference on Computer, Big Data and Artificial Intelligence, ICCBDAI 2021

作者： Jiang, Qiuyan Gong, Daofu Liu, Fenlin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China College of Science and Information Qingdao Agricultural University Qingdao266001 China

This paper studies the social network with directed association semantics, and proposes an unsupervised user identification algorithm (DAUM-P). The algorithm construct a user associations graph based on multiple types of directed user behaviors, and define directed associations;then, walk based on directed associations to obtain a walking sequence, and then combine the network embedding model to learn user characteristics vector representation;finally, the identification result is given based on the representation vector distance. Finally, the experiments show that the user identification effect is better than that of the baseline method. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Malicious Traffic Detection Model Refactor Method Based on Adaptive Sample Generation 5

Malicious Traffic Detection Model Refactor Method Based on A...

引用

5th IEEE advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2022

作者： Jiao, Liang Fei, Jinlong Zhao, Min State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Tianjin University of Science and Technology School of Electronic Information and Automation Tianjin China

ISBN: (纸本)9781665479677

As machine learning models are widely used in malicious traffic detection, model security has become an important research topic. Aiming at the problems that the model refactor attack methods need a large amount of prior knowledge of the target model, rely on a large amount of real data, and have a narrow scope of application, a model refactor method based on adaptive sample generation was proposed. By means of an adaptive sample generation algorithm based on graph retrieval, a small number of real samples are used to quickly generate generated samples uniformly distributed in the input domain. The boundary of the refactored model is corrected according to the decision of the target model, the refactored model is iteratively trained by combining the network traffic feature selection method and the model hyperparameter optimization method, and the model refactor attack is finally realized. The refactor attack experiment against five malicious traffic detection machine learning models shows that the refactor rate and accuracy of the refactored model increase gradually with the increase of iteration rounds, and the refactor rate is more than 90%, using only the target model output label. © 2022 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

IP geolocation base on local delay distribution similarity 9th

IP geolocation base on local delay distribution similarity

引用

9th International Symposium on Cyberspace Safety and Security, CSS 2017

作者： Zhao, Fan Luo, Xiangyang Gan, Yong Zu, Shuodi Liu, Fenlin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou450001 China

ISBN: (纸本)9783319694702

IP geolocation technology can be used to obtain the real-time locations of target Internet hosts especially mobile computers, which can help law enforcement to quickly get the criminal evidence or arrest criminals. Among existing numerous geolocation methods, SLG (Street-Level Geolocation) method can achieve geolocation result with relative higher precision for a target host. However, the geolocation accuracy will be significantly reduced once the common routers that play an important role in geolocation are anonymous, which often happens in paths detection. To solve this problem, this paper proposes an IP geolocation algorithm base on local delay distribution similarity. Firstly, the target’s location at city-level granularity is obtained based on traditional SLG method. Secondly, the landmarks connected with the target by common routers are found out by topology analysis. The target’s local delay between the nearest common router and the target is gained by multi-measurement and calculation, so do the landmarks’. Thirdly, their local delay distribution is obtained by statistical analysis. Lastly, the landmark whose local delay distribution is the most similar with the target’s is selected as the estimated location of the target. Experimental results show that the proposed algorithm obviously improves the geolocation accuracy compared with traditional SLG when the common routers are anonymous. © 2017, Springer International Publishing AG.

关键词： Routers

来源：评论

学校读者我要写书评

暂无评论

Multi Association Semantics-Based User Matching Algorithm Without Prior Knowledge

Multi Association Semantics-Based User Matching Algorithm Wi...

引用

International Conference on Image, Vision and Intelligent Systems, ICIVIS 2021

作者： Jiang, Qiuyan Gong, Daofu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China College of Science and Information Qingdao Agricultural University Qingdao266001 China

ISBN: (纸本)9789811669620

Cross-network user matching is one of the basic issues for realizing social network data integration. Existing research based on structure features provides a good matching method for nodes with high-degree, but ignores the matching of nodes with low values. This paper proposes an unsupervised cross-network user matching algorithm based on association semantics to solve the problem of cross-network user matching. It can effectively solve the low-degree user matching problem when the quality of the text type attributes of network users cannot be guaranteed. First, build a social network graph based on multiple types of user behaviors, and define different association semantics according to different behaviors;then, walk based on the association semantics to obtain user node sequences with association semantics, and then combine the network embedding model to learn the user feature vector representation is obtained;finally, the user similarity is measured based on the user vector similarity, and then cross-network user matching is realized. The highlights of this paper are two folds. (1) We treat the association as nodes. (2) Social network user graphs with association semantics can enrich structure feature;walks based on association semantics can obtain walks that are closer to natural language short sentences. The experimental results show that the proposed method can effectively match user with similar behavior characteristics without any prior knowledge, and can effectively achieve the matching of low-degree nodes in heterogeneous networks. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

A Data Assured Deletion Scheme in Cloud Storage

引用

China Communications 2014年第4期11卷 98-110页

作者： LI Chaoling CHEN Yue ZHOU Yanzhou PLA Information Engineering University Zhengzhou 450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 China

In order to provide a practicable solution to data confidentiality in cloud storage service,a data assured deletion scheme,which achieves the fine grained access control,hopping and sniffing attacks resistance,data dynamics and deduplication,is *** our scheme,data blocks are encrypted by a two-level encryption approach,in which the control keys are generated from a key derivation tree,encrypted by an All-OrNothing algorithm and then distributed into DHT network after being partitioned by secret *** guarantees that only authorized users can recover the control keys and then decrypt the outsourced data in an ownerspecified data *** confidentiality,data dynamics and deduplication are also achieved separately by adjustment of key derivation tree and convergent *** analysis and experimental results show that our scheme can satisfy its security goal and perform the assured deletion with low cost.

关键词： cloud storage data confidentiality secure data assured deletion data dynamics

来源：评论

学校读者我要写书评

暂无评论

Computation Offloading for Multi-user Sequential Tasks in Heterogeneous Mobile Edge computing 17th

Computation Offloading for Multi-user Sequential Tasks in He...

引用

17th EAI International Conference on Collaborative computing: Networking, Applications, and Worksharing, CollaborateCom 2021

作者： Xu, Huanhuan Zhou, Jingya Gu, Fei School of Computer Science and Technology Soochow University Suzhou215006 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi214125 China

ISBN: (纸本)9783030926342

Currently, many computation offloading studies in Mobile Edge computing (MEC) mainly focus on the multi-user and multi-task offloading, where the tasks are independent and inseparable. However, nowadays many mobile applications, such as Augmented Reality (AR) glasses, face recognition, etc., can be classified into sequential tasks. Dependencies among tasks and resource competition among multiple users in the heterogeneous edge environment make the offloading problem very challenging. In this paper, we propose a new multi-user sequential task (MUST) framework to address the above challenge. Specifically, we present a comprehensive analysis of the time cost of the task offloading process in the MUST framework and define the multi-user sequential task offloading problem. Moreover, we prove the problem is NP-hard and propose a reMUST algorithm based on regular expression to obtain the approximate optimal solution. Numerous experiments have shown that the proposed method is superior to existing alternatives in terms of cost and system scalability. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： computation offloading

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：