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A Solution Supporting Secure Transmission of Big Data

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Tsinghua Science and Technology 2023年第5期28卷 838-848页

作者： Haonan Ling Yan Gao Huibin Wang Ming Chen Institute of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China China Electronic Systems Engineering Corporation Beijing 100840China College of Computer and Information Engineering Chuzhou UniversityChuzhou 239000

Traditional Internet protocol networks cannot provide the service of selecting a secure path to transmit various types of data with specific security constraints.First,to solve the“secure path transmission”problem,this paper first proposes a search-transmit model for secure network path transmission,i.e.,to find a multi-attribute optimized path that meets the specific security requirements in the search phase,and then transmit the packets along the optimized path in the transmission phase.Second,we propose a solution to the search-transmit model.The idea of the solution is to use the particle swarm optimization algorithm to search for a secure path that meets the multi-attribute requirements and then set the source route on the router to control the packet transmission.Finally,a prototype system based on Network function virtualization is developed to evaluate the feasibility and performance of the proposed solution.Experimental results show that the proposed solution outperforms existing algorithms in terms of performance.

关键词： network secure path search-transmit model multi-attribute path optimization segment routing Network function virtualization

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

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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 manufacturers.Yet 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 devices.In 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 technique.We 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 devices.NDFuzz obtains an average 36%coverage improvement in comparison with its black-box counterparts.NDFuzz discovers 2 O-Day vulnerabilities and 11-Day vulnerability with coverage guidance while the black-box fuzzer can find only one of them.All discovered vulnerabilities are confirmed by corresponding vendors.

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

Dynamic Backup Sharing Scheme of Service function Chains in NFV

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China Communications 2022年第5期19卷 178-190页

作者： Dong Zhang Zhifan Zheng Xiang Lin Xiang Chen Chunming Wu College of Computer and Data Science Fuzhou UniversityFuzhou 350108China College of Computer Science and Technology Zhejiang UniversityHangzhou 310058China

Service function chains(SFC)mapping takes the responsibility for managing virtual network functions(VNFs).In SFC mapping,existing solutions duplicate VNFs with redundant instances to provide high availability in response to failures.However,as a compromise,these solutions result in high resource consumption due to device maintenance.In this paper,we propose a novel method named dynamic backup sharing(DBS)that allows SFCs to dynamically share backups to reduce resource consumption.DBS formulates the problem of sharing backups among different VNFs as an integer linear programming(ILP).Thereafter,we design a novel online algorithm based on dynamic programming to solve the problem.The experimental results indicate that DBS outperforms state-ofthe-art works by reducing resource consumption and improving the number of accepted requests.

关键词： Network function virtualization service function chain mapping reliability backup sharing

Towards privacy-preserving dynamic deep packet inspection over outsourced

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High-Confidence Computing

High-Confidence Computing 2022年第1期2卷 1-8页

作者： Chunxiao Li Yu Guo Xia Wang School of Artificial Intelligence Beijing Normal UniversityBeijingChina School of Statistics and Data Science Beijing University of TechnologyBeijingChina

The prosperity of Network function virtualization(NFV)pushes forward the paradigm of migrating in-house middleboxes to third-party providers,i.e.,software(virtualized)middlebox services.A lot of enterprises have outsourced traffic processing such as deep packet inspection(DPI),traffic classification,and load balancing to middleboxes provided by cloud providers.However,if the traffic is forwarded to the cloud provider without careful processing,it will cause privacy leakage,as the cloud provider has all the rights to access the data.To solve the security issue,recent efforts are made to design secure middleboxes that can directly conduct network functions over encrypted traffic and middlebox rules.However,security concerns from dynamic operations like dynamic DPI and rule updates are still not yet fully addressed.In this paper,we propose a privacy-preserving dynamic DPI scheme with forward privacy for outsourced middleboxes.Our design can enable cloud side middlebox to conduct secure packet inspection over encrypted traffic data.Besides,the middlebox providers cannot analyze the relationship between the newly added rules and the previous data.Several recent papers have proven that it is a strong property that resist adaptive attacks.Furthermore,we design a general method to inspect stateful packets while still ensuring the state privacy protection.We formally define and prove the security of our design.Finally,we implement a system prototype and analyze the performance from experimental aspects.The evaluation results demonstrate our scheme is effective and efficient.

关键词： DPI outsourcing Network function virtualization Dynamic searchable symmetric encryption

Hyper-Convergence Storage Framework for EcoCloud Correlates

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Computers, Materials & Continua 2022年第1期70卷 1573-1584页

作者： Nadia Tabassum Tahir Alyas Muhammad Hamid Muhammad Saleem Saadia Malik Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Statistics and Computer Science University of Veterinary and Animal SciencesLahore54000Pakistan Department of Industrial Engineering Faculty of EngineeringRabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology-RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia

Cloud computing is an emerging domain that is capturing global users from all walks of life—the corporate sector,government sector,and social arena as well.Various cloud providers have offered multiple services and facilities to this audience and the number of providers is increasing very swiftly.This enormous pace is generating the requirement of a comprehensive ecosystem that shall provide a seamless and customized user environment not only to enhance the user experience but also to improve security,availability,accessibility,and latency.Emerging technology is providing robust solutions to many of our problems,the cloud platform is one of them.It is worth mentioning that these solutions are also amplifying the complexity and need of sustenance of these rapid solutions.As with cloud computing,new entrants as cloud service providers,resellers,tech-support,hardware manufacturers,and software developers appear on a daily basis.These actors playing their role in the growth and sustenance of the cloud ecosystem.Our objective is to use convergence for cloud services,software-defined networks,Network function virtualization for infrastructure,cognition for pattern development,and knowledge repository.In order to gear up these processes,machine learning to induce intelligence to maintain ecosystem growth,to monitor performance,and to become able to make decisions for the sustenance of the ecosystem.Workloads may be programmed to“superficially”imitate most business applications and create large numbers using lightweight workload generators that merely stress the storage.In today’s current IT environment,when many enterprises use the cloud to service some of their application demands,a different performance testing technique that assesses more than the storage is necessary.Compute and storage are merged into a single building block with HCI(Hyper-converged infrastructure),resulting in a huge pool of compute and storage resources when clustered with other building blocks.The novelty of thiswork to design and test cloud sto

关键词： Virtual cloud software define network Network function virtualization hyper-convergence virtualization

Security Monitoring and Management for the network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

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Computer Systems Science & Engineering 2024年第2期48卷 363-394页

作者： Nasser Alshammari Shumaila Shahzadi Saad Awadh Alanazi Shahid Naseem Muhammad Anwar Madallah Alruwaili Muhammad Rizwan Abid Omar Alruwaili Ahmed Alsayat Fahad Ahmad Department of Computer Science College of Computer and Information SciencesJouf UniversitySakakaAl Jouf72341Saudi Arabia Department of Computer Sciences Kinnaird College forWomenLahorePunjab54700Pakistan Department of Information Sciences Division of Sciences and TechnologyUniversity of EducationLahore54770Pakistan Department of Computer Engineering and networks College of Computer and Information SciencesJouf UniversitySakaka72341Saudi Arabia Computer Science Florida Polytechnic UniversityLakelandFlorida33805USA Delta3T LahorePunjab54700Pakistan Department of Basic Sciences Common First YearJouf UniversitySakaka72341Saudi Arabia

Software Defined network(SDN)and Network function virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.network vulnerabilities try to modify services provided by Network function virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized network function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

关键词： Software defined network Network function virtualization Network function virtualization management and orchestration virtual infrastructure manager virtual network function Kubernetes Kubectl artificial intelligence machine learning

Machine Learning Empowered Security Management and Quality of Service Provision in SDN-NFV Environment

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Computers, Materials & Continua 2021年第3期66卷 2723-2749页

作者： Shumaila Shahzadi Fahad Ahmad Asma Basharat Madallah Alruwaili Saad Alanazi Mamoona Humayun Muhammad Rizwan Shahid Naseem Department of Computer Sciences Kinnaird College for WomenLahore54000Pakistan College of Computer and Information Sciences Jouf UniversitySakaka72341Saudi Arabia Division of Computer Science&Information Technology University of EducationLahore54000Pakistan

With the rising demand for data access,network service providers face the challenge of growing their capital and operating costs while at the same time enhancing network capacity and meeting the increased demand for access.To increase efficacy of Software Defined network(SDN)and Network function virtualization(NFV)framework,we need to eradicate network security configuration errors that may create vulnerabilities to affect overall efficiency,reduce network performance,and increase maintenance cost.The existing frameworks lack in security,and computer systems face few abnormalities,which prompts the need for different recognition and mitigation methods to keep the system in the operational state proactively.The fundamental concept behind SDN-NFV is the encroachment from specific resource execution to the programming-based structure.This research is around the combination of SDN and NFV for rational decision making to control and monitor traffic in the virtualized environment.The combination is often seen as an extra burden in terms of resources usage in a heterogeneous network environment,but as well as it provides the solution for critical problems specially regarding massive network traffic issues.The attacks have been expanding step by step;therefore,it is hard to recognize and protect by conventional methods.To overcome these issues,there must be an autonomous system to recognize and characterize the network traffic’s abnormal conduct if there is any.Only four types of assaults,including HTTP Flood,UDP Flood,Smurf Flood,and SiDDoS Flood,are considered in the identified dataset,to optimize the stability of the SDN-NFVenvironment and security management,through several machine learning based characterization techniques like Support Vector Machine(SVM),K-Nearest Neighbors(KNN),Logistic Regression(LR)and Isolation Forest(IF).Python is used for simulation purposes,including several valuable utilities like the mine package,the open-source Python ML libraries Scikit-learn,NumPy,SciPy,Matplotlib.Few Flood assaults and

关键词： Software defined network Network function virtualization machine learning support vector machine K-nearest neighbors logistic regression isolation forest anomaly detection attacks

Recent advances and future challenges for mobile network virtualization

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Science China(Information Sciences) 2017年第4期60卷 5-16页

作者： Xiaofeng TAO Yan HAN Xiaodong XU Ping ZHANG Victor C.M.LEUNG National Engineering Lab for Mobile network Technologies Beijing University of Posts and Telecommunications State Key Lab of networking & Switching Technology Beijing University of Posts and Telecommunications Department of Electrical and Computer Engineering The University of British Columbia

Recently, Network function virtualization(NFV) was proposed as a paradigm shift in the telecommunication industry. Both industry and academia have drawn significant attention in mobile network virtualization.NFV decouples the software implementation of network functions from the underlying hardware, leading to considerable reductions in operating expenses(OPEX) and capital expenses(CAPEX), and facilitating the network deployment. However, as an emerging technology, NFV brings both challenges and opportunities in developing new architectures, applying and deployment. In this paper, we first survey the related work of NFV, and then propose promising research directions in this area.

关键词： Network function virtualization mobile networks software defined networking network functions 5G network slicing

VNF-FG design and VNF placement for 5G mobile networks

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Science China(Information Sciences) 2017年第4期60卷 17-31页

作者： Jiuyue CAO Yan ZHANG Wei AN Xin CHEN Jiyan SUN Yanni HAN State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Sciences

Network function virtualization(NFV) is envisioned as one of the critical technologies in 5thGeneration(5G) mobile networks. This paper investigates the virtual network function forwarding graph(VNFFG) design and virtual network function(VNF) placement for 5G mobile networks. We first propose a two-step method composed of flow designing and flow combining for generating VNF-FGs according to network service requests. For mapping VNFs in the generated VNF-FG to physical resources, we then modify the hybrid NFV environment with introducing more types of physical nodes and mapping modes for the sake of completeness and practicality, and formulate the VNF placement optimization problem for achieving lower bandwidth consumption and lower maximum link utilization simultaneously. To resolve this problem, four genetic algorithms are proposed on the basis of the frameworks of two existing algorithms(multiple objective genetic algorithm and improved non-dominated sorting genetic algorithm). Simulation results show that Greedy-NSGA-II achieves the best performance among our four algorithms. Compared with three non-genetic algorithms(random, backtracking mapping and service chains deployment with affiliation-aware), Greedy-NSGA-II reduces 97.04%, 87.76% and88.42% of the average total bandwidth consumption, respectively, and achieves only 13.81%, 25.04% and 25.41%of the average maximum link utilization, respectively. Moreover, using our VNF-FG design method and GreedyNSGA-II together can also reduce the total bandwidth consumption remarkably.

关键词： Network function virtualization VNF-FG design VNF placement multi-objective optimization genetic algorithm