2020 6th IEEE Conference on Network Softwarization (NetSoft)最新文献_第7页

Cloud-Native Threat Detection and Containment for Smart Manufacturing 面向智能制造的云原生威胁检测和遏制

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165321

M. Müller, D. Behnke, Patrick-Benjamin Bök, Stefan Schneider, Manuel Peuster, H. Karl

{"title":"Cloud-Native Threat Detection and Containment for Smart Manufacturing","authors":"M. Müller, D. Behnke, Patrick-Benjamin Bök, Stefan Schneider, Manuel Peuster, H. Karl","doi":"10.1109/NetSoft48620.2020.9165321","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165321","url":null,"abstract":"Softwarization facilitates the introduction of smart manufacturing applications in the industry. Manifold devices such as machine computers, Industrial IoT devices, tablets, smartphones and smart glasses are integrated into factory networks to enable shop floor digitalization and big data analysis. To handle the increasing number of devices and the resulting traffic, a flexible and scalable factory network is necessary which can be realized using softwarization technologies like Network Function Virtualization (NFV). However, the security risks increase with the increasing number of new devices, so that cyber security must also be considered in NFV-based networks. Therefore, extending our previous work, we showcase threat detection using a cloud-native NFV-driven intrusion detection system (IDS) that is integrated in our industrial-specific network services. As a result of the threat detection, the affected network service is put into quarantine via automatic network reconfiguration. We use the 5GTANGO service platform to deploy our developed network services on Kubernetes and to initiate the network reconfiguration. Our focus is on demonstrating the automatic network reconfiguration that is triggered by the IDS.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134494861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Attestation of Trusted and Reliable Service Function Chains in the ETSI-NFV Framework ETSI-NFV框架中可信和可靠服务功能链的认证

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/netsoft48620.2020.9165316

Antonio Suriano, D. Striccoli, G. Piro, Raffele Bolla, G. Boggia

{"title":"Attestation of Trusted and Reliable Service Function Chains in the ETSI-NFV Framework","authors":"Antonio Suriano, D. Striccoli, G. Piro, Raffele Bolla, G. Boggia","doi":"10.1109/netsoft48620.2020.9165316","DOIUrl":"https://doi.org/10.1109/netsoft48620.2020.9165316","url":null,"abstract":"The new generation of digital services are natively conceived as an ordered set of Virtual Network Functions, deployed across boundaries and organizations. In this context, security threats, variable network conditions, computational and memory capabilities and software vulnerabilities may significantly weaken the whole service chain, thus making very difficult to combat the newest kinds of attacks. It is thus extremely important to conceive a flexible (and standard-compliant) framework able to attest the trustworthiness and the reliability of each single function of a Service Function Chain. At the time of this writing, and to the best of authors knowledge, the scientific literature addressed all of these problems almost separately. To bridge this gap, this paper proposes a novel methodology, properly tailored within the ETSI-NFV framework. From one side, Software-Defined Controllers continuously monitor the properties and the performance indicators taken from networking domains of each single Virtual Network Function available in the architecture. From another side, a high-level orchestrator combines, on demand, the suitable Virtual Network Functions into a Service Function Chain, based on the user requests, targeted security requirements, and measured reliability levels. The paper concludes by further explaining the functionalities of the proposed architecture through a use case.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134621064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Adaptive & Learning-aware Orchestration of Content Delivery Services 内容交付服务的自适应和学习意识编排

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165475

S. V. Rossem, Thomas Soenen, W. Tavernier, D. Colle, M. Pickavet, P. Demeester

引用次数: 1

Towards a Unified In-Network DDoS Detection and Mitigation Strategy 统一网络内DDoS检测与防范策略

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165336

Kurt Friday, Elie F. Kfoury, E. Bou-Harb, J. Crichigno

{"title":"Towards a Unified In-Network DDoS Detection and Mitigation Strategy","authors":"Kurt Friday, Elie F. Kfoury, E. Bou-Harb, J. Crichigno","doi":"10.1109/NetSoft48620.2020.9165336","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165336","url":null,"abstract":"Distributed Denial of Service (DDoS) attacks have terrorized our networks for decades, and with attacks now reaching 1.7 Tbps, even the slightest latency in detection and subsequent remediation is enough to bring an entire network down. Though strides have been made to address such maliciousness within the context of Software Defined Networking (SDN), they have ultimately proven ineffective. Fortunately, P4 has recently emerged as a platform-agnostic language for programming the data plane and in turn allowing for customized protocols and packet processing. To this end, we propose a first-of-a-kind P4-based detection and mitigation scheme that will not only function as intended regardless of the size of the attack, but will also overcome the vulnerabilities of SDN that have characteristically been exploited by DDoS. Moreover, it successfully defends against the broad spectrum of currently relevant attacks while concurrently emphasizing the Quality of Service (QoS) of legitimate end-users and overall SDN functionality. We demonstrate the effectiveness of the proposed scheme using a software programmable P4-switch, namely, the Behavorial Model version 2 (BMv2), showing its ability to withstand a variety of DDoS attacks in real-time via three use cases that can be generalized to most contemporary attack vectors. Specifically, the results substantiate that the mechanism herein is orders of magnitude faster than traditional polling techniques (e.g., NetFlow or sFlow) while minimizing the impact on benign traffic. We concur that the approach's design particularities facilitate seamless and scalable deployments in high-speed networks requiring line-rate functionality, in addition to being generic enough to be integrated into viable network topologies.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133104596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 19

Reinforcement Learning for Attack Mitigation in SDN-enabled Networks 在支持sdn的网络中用于缓解攻击的强化学习

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165383

M. Zolotukhin, Sanjay Kumar, T. Hämäläinen

{"title":"Reinforcement Learning for Attack Mitigation in SDN-enabled Networks","authors":"M. Zolotukhin, Sanjay Kumar, T. Hämäläinen","doi":"10.1109/NetSoft48620.2020.9165383","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165383","url":null,"abstract":"With the recent progress in the development of low-budget sensors and machine-to-machine communication, the Internet-of-Things has attracted considerable attention. Unfortunately, many of today's smart devices are rushed to market with little consideration for basic security and privacy protection making them easy targets for various attacks. Unfortunately, organizations and network providers use mostly manual workflows to address malware-related incidents and therefore they are able to prevent neither attack damage nor potential attacks in the future. Thus, there is a need for a defense system that would not only detect an intrusion on time, but also would make the most optimal real-time crisis-action decision on how the network security policy should be modified in order to mitigate the threat. In this study, we are aiming to reach this goal relying on advanced technologies that have recently emerged in the area of cloud computing and network virtualization. We are proposing an intelligent defense system implemented as a reinforcement machine learning agent that processes current network state and takes a set of necessary actions in form of software-defined networking flows to redirect certain network traffic to virtual appliances. We also implement a proof-of-concept of the system and evaluate a couple of state-of-art reinforcement learning algorithms for mitigating three basic network attacks against a small realistic network environment.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116109844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

Towards Cross-Slice Communication for Enhanced Service Delivery at the Network Edge 面向网络边缘增强业务交付的横片通信

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165442

Ioakeim Fotoglou, George Papathanail, Angelos Pentelas, Panagiotis Papadimitriou, V. Theodorou, Dimitrios Dechouniotis, S. Papavassiliou

{"title":"Towards Cross-Slice Communication for Enhanced Service Delivery at the Network Edge","authors":"Ioakeim Fotoglou, George Papathanail, Angelos Pentelas, Panagiotis Papadimitriou, V. Theodorou, Dimitrios Dechouniotis, S. Papavassiliou","doi":"10.1109/NetSoft48620.2020.9165442","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165442","url":null,"abstract":"The increasing resource demand and diversity of network services is taken under serious consideration by the various stakeholders, driving the architecture design of 5G (and beyond) networks. Network slicing, as a prominent aspect of next-generation network architectures, aims at satisfying the diverse service requirements in terms of throughput, latency, reliability, and/or security. However, the prevailing way of slice provisioning, i.e., in the form of isolated bundles of computing, storage, and network resources, makes cross-slice communication inefficient, especially at the network edge. This inevitably hinders opportunities for Business-to-Business (B2B) synergies at the event of service co-location. In this paper, we study this novel aspect of network slicing, i.e., cross-slice communication (CSC). We particularly promote a form of optimized CSC, at which two co-located slices can establish peering in a secure and controlled manner, by confining peering traffic within the boundaries of the datacenter, while still preserving the important aspect of resource isolation. Such optimized CSC can foster synergies between service providers without additional latency or traffic in the backhaul/transport network. In this context, we investigate various ways to establish optimized CSC at edge computing infrastructures, based on functionalities offered by state-of-the-art management and orchestration (MANO) frameworks, such as OpenSourceMANO.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":" 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120932091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Performance Modelling Approach for SLA-Aware Resource Recommendation in Cloud Native Network Functions 云原生网络功能中sla感知资源推荐的性能建模方法

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/netsoft48620.2020.9165482

Michel Gokan Khan, J. Taheri, M. Khoshkholghi, A. Kassler, Carolyn Cartwright, M. Darula, Shuiguang Deng

{"title":"A Performance Modelling Approach for SLA-Aware Resource Recommendation in Cloud Native Network Functions","authors":"Michel Gokan Khan, J. Taheri, M. Khoshkholghi, A. Kassler, Carolyn Cartwright, M. Darula, Shuiguang Deng","doi":"10.1109/netsoft48620.2020.9165482","DOIUrl":"https://doi.org/10.1109/netsoft48620.2020.9165482","url":null,"abstract":"Network Function Virtualization (NFV) becomes the primary driver for the evolution of 5G networks, and in recent years, Network Function Cloudification (NFC) proved to be an inevitable part of this evolution. Microservice architecture also becomes the de facto choice for designing a modern Cloud Native Network Function (CNF) due to its ability to decouple components of each CNF into multiple independently manageable microservices. Even though taking advantage of microservice architecture in designing CNFs solves specific problems, this additional granularity makes estimating resource requirements for a Production Environment (PE) a complex task and sometimes leads to an over-provisioned PE. Traditionally, performance engineers dimension each CNF within a Service Function Chain (SFC) in a smaller Performance Testing Environment (PTE) through a series of performance benchmarks. Then, considering the Quality of Service (QoS) constraints of a Service Provider (SP) that are guaranteed in the Service Level Agreement (SLA), they estimate the required resources to set up the PE. In this paper, we used a machine learning approach to model the impact of each microservice's resource configuration (i.e., CPU and memory) on the QoS metrics (i.e. serving throughput and latency) of each SFC in a PTE. Then, considering an SP's Service Level Objectives (SLO), we proposed an algorithm to predict each microservice's resource capacities in a PE. We evaluated the accuracy of our prediction on a prototype of a cloud native 5G Home Subscriber Server (HSS). Our model showed 95%-78% accuracy in a PE that has 2–5 times more computing resources than the PTE.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128935273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Pythia: Scheduling of Concurrent Network Packet Processing Applications on Heterogeneous Devices 异构设备上并发网络包处理应用程序的调度

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/netsoft48620.2020.9165447

Giannis Giakoumakis, Eva Papadogiannaki, G. Vasiliadis, S. Ioannidis

{"title":"Pythia: Scheduling of Concurrent Network Packet Processing Applications on Heterogeneous Devices","authors":"Giannis Giakoumakis, Eva Papadogiannaki, G. Vasiliadis, S. Ioannidis","doi":"10.1109/netsoft48620.2020.9165447","DOIUrl":"https://doi.org/10.1109/netsoft48620.2020.9165447","url":null,"abstract":"Modern commodity computing systems are composed of a number of heterogeneous processing units, each one with its own unique performance and energy characteristics. However, the majority of current network packet processing frameworks targets only one device (either the CPU or an accelerator), leaving the remaining computational resources underutilized or even idle. In this paper, we propose an adaptive scheduling approach for network packet processing applications that exploits any heterogeneous architecture that can be found in a commodity high-end hardware setup. Our scheduler not only distributes the workloads to the appropriate devices in the system to achieve the desired performance results, but also enables the multiplexing of diverse, concurrently executed network packet processing applications, eliminating the interference effects introduced at run-time. The evaluation results show that our scheduler is able to tackle any interference in the shared hardware resources as well to respond quickly to dynamic fluctuations (e.g., application overloads, traffic bursts, infrastructural changes, etc.) that may occur at real time.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"293 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123740760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Enabling Autonomous and Connected Vehicles at the 5G Network Edge 在5G网络边缘实现自动驾驶和联网汽车

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165444

Estefanía Coronado, G. Cebrián-Márquez, R. Riggio

引用次数: 6

Machine Learning Approaches to Early Fault Detection and Identification in NFV Architectures NFV架构中早期故障检测与识别的机器学习方法

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165361

Arij Elmajed, A. Aghasaryan, É. Fabre

引用次数: 6