2020 6th IEEE Conference on Network Softwarization (NetSoft)最新文献

On the Security of Permissioned Blockchain Solutions for IoT Applications 关于物联网应用许可区块链解决方案的安全性

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165480

Sotirios Brotsis, N. Kolokotronis, Konstantinos Limniotis, S. Shiaeles

{"title":"On the Security of Permissioned Blockchain Solutions for IoT Applications","authors":"Sotirios Brotsis, N. Kolokotronis, Konstantinos Limniotis, S. Shiaeles","doi":"10.1109/NetSoft48620.2020.9165480","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165480","url":null,"abstract":"The blockchain has found numerous applications in many areas with the expectation to significantly enhance their security. The Internet of things (IoT) constitutes a prominent application domain of blockchain, with a number of architectures having been proposed for improving not only security but also properties like transparency and auditability. However, many blockchain solutions suffer from inherent constraints associated with the consensus protocol used. These constraints are mostly inherited by the permissionless setting, e.g. computational power in proof-of-work, and become serious obstacles in a resource-constrained IoT environment. Moreover, consensus protocols with low throughput or high latency are not suitable for IoT networks where massive volumes of data are generated. Thus, in this paper we focus on permissioned blockchain platforms and investigate the consensus protocols used, aiming at evaluating their performance and fault tolerance as the main selection criteria for (in principle highly insecure) IoT ecosystem. The results of the paper provide new insights on the essential differences of various consensus protocols and their capacity to meet IoT needs.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"105 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120827126","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: 3

IoT Malware Network Traffic Classification using Visual Representation and Deep Learning 使用视觉表示和深度学习的物联网恶意软件网络流量分类

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165381

G. Bendiab, S. Shiaeles, Abdulrahman Alruban, N. Kolokotronis

{"title":"IoT Malware Network Traffic Classification using Visual Representation and Deep Learning","authors":"G. Bendiab, S. Shiaeles, Abdulrahman Alruban, N. Kolokotronis","doi":"10.1109/NetSoft48620.2020.9165381","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165381","url":null,"abstract":"With the increase of IoT devices and technologies coming into service, Malware has risen as a challenging threat with increased infection rates and levels of sophistication. Without strong security mechanisms, a huge amount of sensitive data are exposed to vulnerabilities, and therefore, easily abused by cybercriminals to perform several illegal activities. Thus, advanced network security mechanisms that are able of performing a real-time traffic analysis and mitigation of malicious traffic are required. To address this challenge, we are proposing a novel IoT malware traffic analysis approach using deep learning and visual representation for faster detection and classification of new malware (zero-day malware). The detection of malicious network traffic in the proposed approach works at the package level, reducing significantly the time of detection with promising results due to the deep learning technologies used. To evaluate our proposed method performance, a dataset is constructed which consists of 1000 pcap files of normal and malware traffic that are collected from different network traffic sources. The experimental results of Residual Neural Network (ResNet50) are very promising, providing a 94.50% accuracy rate for detection of malware traffic.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"39 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":"123410937","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: 39

Spider: Parallelizing Longest Prefix Matching with Optimization for SIMD Instructions 蜘蛛:并行最长前缀匹配与优化SIMD指令

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165306

Yukito Ueno, Ryo Nakamura, Yohei Kuga, H. Esaki

{"title":"Spider: Parallelizing Longest Prefix Matching with Optimization for SIMD Instructions","authors":"Yukito Ueno, Ryo Nakamura, Yohei Kuga, H. Esaki","doi":"10.1109/NetSoft48620.2020.9165306","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165306","url":null,"abstract":"Longest prefix matching (LPM) is a fundamental process in IP routing used not only in traditional hardware routers but also in modern software middleboxes such as the applications of Network Function Virtualization. However, the performance of recent LPM methods in software routers is insufficient for high-speed packet processing such as two or more 100 Gbps throughput. To improve the performance of LPM, we propose Spider, a new LPM method that achieves a fully parallelized LPM procedure using single instruction, multiple data (SIMD) instructions in a CPU. The evaluation shows that the proposed method has 1.8-1.9 times faster LPM performance compared with the state-of-the-art methods in this study area. We describe the Spider's lookup procedure fully parallelized by SIMD instructions and the design of the routing table efficiently processed by the procedure. We also report the following three evaluations: (1) The effect of parallelization by SIMD instructions on the performance of Spider; (2) the scalability of Spider with the number of CPU cores; and (3) the performance comparison with the previous methods in terms of randomly generated and real-trace traffic patterns.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"22 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":"125436817","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: 2

Orchestrating SDN Control Plane towards Enhanced IoT Security 编排SDN控制平面，增强物联网安全性

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165424

Hasan Tooba, Adnan Akhunzada, Thanassis Giannetsos, Jahanzaib Malik

{"title":"Orchestrating SDN Control Plane towards Enhanced IoT Security","authors":"Hasan Tooba, Adnan Akhunzada, Thanassis Giannetsos, Jahanzaib Malik","doi":"10.1109/NetSoft48620.2020.9165424","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165424","url":null,"abstract":"The Internet of Things (IoT) is rapidly evolving, while introducing several new challenges regarding security, resilience and operational assurance. In the face of an increasing attack landscape, it is necessary to cater for the provision of efficient mechanisms to collectively detect sophisticated malware resulting in undesirable (run-time) device and network modifications. This is not an easy task considering the dynamic and heterogeneous nature of IoT environments; i.e., different operating systems, varied connected networks and a wide gamut of underlying protocols and devices. Malicious IoT nodes or gateways can potentially lead to the compromise of the whole IoT network infrastructure. On the other hand, the SDN control plane has the capability to be orchestrated towards providing enhanced security services to all layers of the IoT networking stack. In this paper, we propose an SDN-enabled control plane based orchestration that leverages emerging Long Short-Term Memory (LSTM) classification models; a Deep Learning (DL) based architecture to combat malicious IoT nodes. It is a first step towards a new line of security mechanisms that enables the provision of scalable AI-based intrusion detection focusing on the operational assurance of only those specific, critical infrastructure components,thus, allowing for a much more efficient security solution. The proposed mechanism has been evaluated with current state of the art datasets (i.e., N_BaIoT 2018) using standard performance evaluation metrics. Our preliminary results show an outstanding detection accuracy (i.e., 99.9%) which significantly outperforms state-of-the-art approaches. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security does not hinder the deployment of intelligent IoT-based computing systems.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"467 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":"114891905","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: 7

Automated Provisioning of Cloud-Native Network Functions in Multi-Cloud Environments 多云环境下云原生网络功能的自动发放

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/netsoft48620.2020.9165343

Shiku Hirai, Takuya Tojo, S. Seto, S. Yasukawa

引用次数: 8

An Integrated Instrumentation and Insights Framework for Holistic 5G Slice Assurance 全面5G切片保证的集成仪器和洞察框架

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165431

P. Veitch, John J. Browne, Jonas Krogell

引用次数: 1

Techno-economic evaluation of a brokerage role in the context of integrated satellite-5G networks 卫星- 5g综合网络背景下中介作用的技术经济评估

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165508

Asma Chiha, M. V. D. Wee, K. Briggs, D. Colle

引用次数: 0

Linking QoE and Performance Models for DASH-based Video Streaming 链接QoE和性能模型的基于dash的视频流

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165339

Susanna Schwarzmann, T. Zinner

{"title":"Linking QoE and Performance Models for DASH-based Video Streaming","authors":"Susanna Schwarzmann, T. Zinner","doi":"10.1109/NetSoft48620.2020.9165339","DOIUrl":"https://doi.org/10.1109/NetSoft48620.2020.9165339","url":null,"abstract":"HTTP Adaptive Streaming (HAS) is the de-facto standard for video delivery over the Internet. Splitting the video clip into small segments and providing multiple quality levels per segment allows the client to dynamically adapt the quality to current network conditions. The performance of HAS, and as a consequence the user Quality of Experience (QoE), is influenced by a multitude of parameters. This includes adjustable settings like quality switching thresholds, the initial buffer level, or the maximum buffer, as well as video characteristics like segment duration or the variation of segment sizes along the video. Recently, a couple of analytical models for video streaming have been proposed, allowing to compare these input parameters and derive their impact on QoE-relevant metrics for HAS-based video delivery. The outcome of these models are typically asymptotic probabilities, distribution functions, or centralized and standardized moments. For instance, these models do not yield any temporal information in terms of stalling events or requested video quality. This contradicts to QoE prediction models like P.1203, which compute the QoE based on the chronological sequence of a specific video playback. So far, it is unclear how and to which extent the generalized results of analytical models can be utilized to derive sequence-based QoE values or the QoE distribution for a set of sequences for similar input parameters with stochastic variations. To address this problem, we compare testbed measurements with the output of a GI/GI/1 model with pq-policy and buffer-based quality switching capability to conclude to which extent the results still allow to approximate the video QoE.","PeriodicalId":239961,"journal":{"name":"2020 6th IEEE Conference on Network Softwarization (NetSoft)","volume":"203 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":"114644215","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

Shortest Path Tour Problem Based Integer Linear Programming for Service Chaining in NFV Networks 基于最短路径漫游问题的NFV网络业务链整数线性规划

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165364

Masahiro Sasabe, Takanori Hara

引用次数: 3

PolKA: Polynomial Key-based Architecture for Source Routing in Network Fabrics 网络结构中基于多项式密钥的源路由体系结构

2020 6th IEEE Conference on Network Softwarization (NetSoft) Pub Date : 2020-06-01 DOI: 10.1109/NetSoft48620.2020.9165501

C. Dominicini, D. Mafioletti, A. Locateli, R. Villaça, M. Martinello, M. Ribeiro, A. Gorodnik

引用次数: 7