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Building In-the-Cloud network functions: Security and Privacy Challenges

PROCEEDINGS OF THE IEEE 2021年第12期109卷 1888-1919页

作者： Jiang, Peipei Wang, Qian Huang, Muqi Wang, Cong Li, Qi Shen, Chao Ren, Kui Wuhan Univ Sch Cyber Sci & Engn Key Lab Aerosp Informat Secur & Trusted Comp Minist Educ Wuhan 430072 Hubei Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Wuhan Univ Sch Cyber Sci & Engn Wuhan 430072 Hubei Peoples R China Wuhan Univ Sch Comp Sci Wuhan 430072 Hubei Peoples R China Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol BNRis Inst Network Sci & Cyberspace Beijing 100084 Peoples R China Xi An Jiao Tong Univ Sch Cyber Sci & Engn Xian 710049 Peoples R China Zhejiang Univ Coll Comp Sci & Technol Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Inst Cyber Sci & Technol Hangzhou 310027 Zhejiang Peoples R China

network function virtualization (NFV) has been promising to improve the availability, programmability, and flexibility of network function deployment and communication facilities. Meanwhile, with the advancements of cloud technologies, there has been a trend to outsource network functions through virtualization to a cloud service provider, so as to alleviate the local burdens on provisioning and managing such hardware resources. Promising as it is, redirecting the communication traffic to a third-party service provider has drawn various security and privacy concerns. Traditional end-to-end encryption can protect the traffic in transmit, but it also hinders data usability. This dilemma has raised wide interests from both industry and academia, and great efforts have been made to realize privacy-preserving network function outsourcing that can guarantee the confidentiality of network communications while preserving the ability to inspect the traffic. In this article, we conduct a comprehensive survey of the state-of-the-art literature on network function outsourcing, with a special focus on privacy and security issues. We first give a brief introduction to NFV and pinpoint its challenges and security risks in the cloud context. Then, we present detailed descriptions and comparisons of existing secure network function outsourcing schemes in terms of functionality, efficiency, and security. Finally, we conclude by discussing possible future research directions.

关键词： Privacy Cloud computing Privacy Outsourcing network function virtualization Encryption Market research Telecommunication traffic network function outsourcing network function virtualization (NFV) privacy preservation

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Verticals in 5G MEC-Use Cases and Security Challenges

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IEEE ACCESS 2021年 9卷 87251-87298页

作者： Nowak, Tomasz W. Sepczuk, Mariusz Kotulski, Zbigniew Niewolski, Wojciech Artych, Rafal Bocianiak, Krzysztof Osko, Tomasz Wary, Jean-Philippe Warsaw Univ Technol Fac Elect & Informat Technol PL-00661 Warsaw Poland Orange Polska SA PL-02326 Warsaw Poland Orange Labs F-92020 Chatillon France

5G is the fifth-generation cellular network satisfying the requirements IMT-2020 (International Mobile Telecommunications-2020) of the International Telecommunication Union. Mobile network operators started using it worldwide in 2019. Generally, 5G achieves exceptionally high values of performance parameters of access and transmission. The application of edge servers has been proposed to facilitate implementing such requirements of 5G, resulting in 5G MEC (Multi-access Edge Computing) technology. Moreover, to optimize services for specific business applications, the concept of 5G vertical industries has been proposed. In this article, we study how the application of the MEC technology affects the functioning of 5G MEC-based services. We consider twelve representative vertical industries of 5G MEC by presenting their essential characteristics, threats, vulnerabilities, and known attacks. Furthermore, we analyze their functional properties, give efficiency patterns and identify the effect of applying the MEC technology in 5G on the resultant network's quality parameters to determine the expected security requirements. As a result of the research, we identify the impact of classified threats on the 5G empowered vertical industries and identify the most sensitive cases to focus on their protection against network attacks in the first place.

关键词： 5G mobile communication Security Industries Edge computing Communication system security Cloud computing network function virtualization 5G mobile communication communication system security MEC mobile computing network servers next generation networking performance parameters software protection telecommunication computing telecommunication services vertical industries

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Traffic Engineering Based on Reinforcement Learning for Service function Chaining With Delay Guarantee

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IEEE ACCESS 2021年 9卷 121583-121592页

作者： Tuan-Minh Pham Phenikaa Univ Fac Comp Sci Hanoi 12116 Vietnam Phenikaa Univ Phenikaa Inst Adv Study PIAS Hanoi 12116 Vietnam A&A Phoenix Grp JSC Phenikaa Res & Technol Inst PRATI Hanoi 11313 Vietnam

network function virtualization (NFV) is an approach that provides a network service provider with agility and cost-efficiency in managing 6G network services. Standard traffic engineering rules are known limited in assuring a very stringent delay requirement in NFV when a traffic flow is required to follow a sequence of network functions scattered in data center networks. This paper proposes an innovative model and algorithm of traffic engineering for service function chaining (SFC) to maximize cost-efficiency under a delay-guarantee constraint. We first formulate the problem as a mixed-integer linear programming model for obtaining the optimal solution. We then propose an algorithm based on the reinforcement learning principles for finding an approximation solution in a large-scale problem with the dynamics of service demands. Numerical results under both real-world datasets and synthetic network topologies demonstrate that our proposed model and algorithm allow an NFV service provider (NSP) to place a virtual network function and steer a traffic flow efficiently in terms of energy cost for a delay-guarantee SFC. Importantly, the results provide an insight into the optimal and approximation solutions for an NSP to select a suitable traffic engineering approach with regard to network dynamics.

关键词： Routing Delays Optimization Resource management network function virtualization Heuristic algorithms Reinforcement learning network function virtualization optimization reinforcement learning service function chaining traffic engineering

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On the Fly Orchestration of Unikernels: Tuning and Performance Evaluation of Virtual Infrastructure Managers

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2021年第2期9卷 710-723页

作者： Ventre, Pier Luigi Lungaroni, Paolo Siracusano, Giuseppe Pisa, Claudio Schmidt, Florian Lombardo, Francesco Salsano, Stefano Univ Roma Tor Vergata I-00133 Rome 50 Italy CNIT I-43100 Parma Italy NEC Labs Europe D-69115 Heidelberg Germany

network operators are facing significant challenges meeting the demand for more bandwidth, agile infrastructures, innovative services, while keeping costs low. network functions virtualization (NFV) and Cloud Computing are emerging as key trends of 5G network architectures, providing flexibility, fast instantiation times, support of Commercial Off The Shelf hardware and significant cost savings. NFV leverages Cloud Computing principles to move the data-plane network functions from expensive, closed and proprietary hardware to the so-called Virtual network functions (VNFs). In this paper we deal with the management of virtual computing resources (Unikernels) for the execution of VNFs. This functionality is performed by the Virtual Infrastructure Manager (VIM) in the NFV MANagement and Orchestration (MANO) reference architecture. We discuss the instantiation process of virtual resources and propose a generic reference model, starting from the analysis of three open source VIMs, namely OpenStack, Nomad and Open VIM. We improve the aforementioned VIMs introducing the support for special-purpose Unikernels and aiming at reducing the duration of the instantiation process. We evaluate some performance aspects of the VIMs, considering both stock and tuned versions. The VIM extensions and performance evaluation tools are available under a liberal open source licence.

关键词： network function virtualization open source virtual infrastructure manager virtual network function performance tuning openstack nomad OpenVIM ClickOS unikernel

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Softwarized Internet of Things network Monitoring

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IEEE SYSTEMS JOURNAL 2021年第1期15卷 826-834页

作者： Bekri, Wiem Jmal, Rihab Fourati, Lamia Chaari Univ Sfax Lab Technol Smart Syst Digital Res Ctr Sfax Sfax 3021 Tunisia

Softwarizing a network can improve its overall resilience. A softwarized network is based on software-defined networking (SDN), network function virtualization (NFV), and network virtualization. It is well known that SDN controllers provide a wide vision of the whole network. It grants the programmability of the network, which is complementary to the NFV functioning. SDN/NFV aims to make the physical equipment used versatile. In this article, we present the monitoring module of our approach for Internet of Things (IoT) environment using the Open network Operating System (ONOS) controller. This article presents the first step for our next softwarized management framework that would investigate the important input information collected from this monitoring approach.

关键词： Monitoring network function virtualization Internet of Things Computer architecture virtualization Data centers Hardware Internet of Things (IoT) monitoring network function virtualization (NFV) software-defined networking (SDN) softwarized

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Virtual IoT Service Slice functions for Multiaccess Edge Computing Platform

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IEEE INTERNET OF THINGS JOURNAL 2021年第14期8卷 11233-11248页

作者： Nkenyereye, Lionel Hwang, Jaeyoung Pham, Quoc-Viet Song, Jaeseung Sejong Univ Deprtment Comp & Informat Secur Seoul 15600 South Korea Pusan Natl Univ Res Inst Comp Informat & Commun Busan 46241 South Korea

With the advancement of the Internet of Things (IoT), different use cases, such as smart factories, smart cities, and smart cars are being developed. Technologies, such as multiaccess edge computing (MEC) and network slicing are being researched to support various vertical use cases. However, simply utilizing network slicing and MEC is insufficient when providing a specific IoT service. Accordingly, there is a need for a method of arranging and operating common service functions (CSFs) used in the IoT platform at the edge of the network. In addition, it is necessary not only to deliver virtual CSFs but also to implement autoscaling policies of these virtual common service resources. This study extends the idea of resource slicing technologies for the IoT service layer. The IoT service layer exposes the virtual IoT CSFs as an IoT slice service to be provided in the form of virtual network functions (VNFs) with MEC applications on top of the network function virtualization infrastructure (NFVI) at the edge of the network. We propose a framework architecture for virtual IoT slice service orchestration, and illustrate how to instantiate the virtual IoT service functions in the existing centralized cloud to the MEC platform. We also propose an elastic computing algorithm of virtual IoT slice services functions(vIoT-SSFs) resources at the NFVI so that the IoT applications and underlying IoT resources can access vIoT-SSFs at the edge of the network.

关键词： Internet of Things 5G mobile communication network slicing Edge computing Quality of service Computer architecture network function virtualization Autoscaling policies Internet of Things (IoT) multiaccess edge computing (MEC) network slicing oneM2M standard virtual network function (VNF) virtualization of IoT service layer

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Age of Information Aware VNF Scheduling in Industrial IoT Using Deep Reinforcement Learning

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2021年第8期39卷 2487-2500页

作者： Akbari, Mohammad Abedi, Mohammad Reza Joda, Roghayeh Pourghasemian, Mohsen Mokari, Nader Erol-Kantarci, Melike ICT Res Inst Commun Dept Tehran *** Iran Tarbiat Modares Univ Fac Elect & Comp Engn ECE Tehran 14115111 Iran Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON K1N 6N5 Canada

In delay-sensitive industrial internet of things (IIoT) applications, the age of information (AoI) is employed to characterize the freshness of information. Meanwhile, the emerging network function virtualization provides flexibility and agility for service providers to deliver a given network service using a sequence of virtual network functions (VNFs). However, suitable VNF placement and scheduling in these schemes is NP-hard and finding a globally optimal solution by traditional approaches is complex. Recently, deep reinforcement learning (DRL) has appeared as a viable way to solve such problems. In this paper, we first utilize single agent low-complex compound action actor-critic RL to cover both discrete and continuous actions and jointly minimize VNF cost and AoI in terms of network resources under end-to-end Quality of Service constraints. To surmount the single-agent capacity limitation for learning, we then extend our solution to a multi-agent DRL scheme in which agents collaborate with each other. Simulation results demonstrate that single-agent schemes significantly outperform the greedy algorithm in terms of average network cost and AoI. Moreover, multi-agent solution decreases the average cost by dividing the tasks between the agents. However, it needs more iterations to be learned due to the requirement on the agents' collaboration.

关键词： Industrial Internet of Things Delays Measurement Information age Reinforcement learning Quality of service Resource management Industrial Internet of Things network function virtualization age of information deep reinforcement learning compound actions multi-agent

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NFV Platforms: Taxonomy, Design Choices and Future Challenges

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2021年第1期18卷 30-48页

作者： Zhang, Tianzhu Qiu, Han Linguaglossa, Leonardo Cerroni, Walter Giaccone, Paolo Telecom Paris Dept Network & Comp Sci F-91120 Paris France Nokia Bell Labs F-91620 Nozay France Telecom Paris Dept Network & Comp Sci F-91120 Paris France Univ Bologna Dept Elect Elect & Informat Engn Guglielmo Marcon I-40136 Bologna Italy Consorzio Nazl Interuniv Telecomunicaz I-43124 Parma Italy Politecn Torino Dept Elect & Telecommun I-10138 Turin Italy

Due to the intrinsically inefficient service provisioning in traditional networks, network function virtualization (NFV) keeps gaining attention from both industry and academia. By replacing the purpose-built, expensive, proprietary network equipment with software network functions consolidated on commodity hardware, NFV envisions a shift towards a more agile and open service provisioning paradigm. During the last few years, a large number of NFV platforms have been implemented to facilitate the development, deployment, and management of Virtual network functions (VNFs). Nonetheless, just like any complex system, such platforms commonly consist of abounding software and hardware components and usually incorporate disparate design choices based on distinct motivations or use cases. This broad collection of convoluted alternatives makes it extremely arduous for network operators to make proper choices. Although numerous efforts have been devoted to investigating different aspects of NFV, none of them specifically focused on NFV platforms or attempted to explore their design space. In this article, we present a comprehensive survey on the NFV platform design. Our study solely targets existing NFV platform implementations. We begin with a top-down architectural view of the standard reference NFV platform and present our taxonomy of existing NFV platforms based on what features they provide in terms of a typical network function life cycle. Then we thoroughly explore the design space and elaborate on the implementation choices each platform opts for. We also envision future challenges for NFV platform design in the incoming 5G era. We believe that our study gives a detailed guideline for network operators or service providers to choose the most appropriate NFV platform based on their respective requirements. Our work also provides guidelines for implementing new NFV platforms.

关键词： Hardware Software Middleboxes Space exploration Monitoring Switches virtualization network function virtualization service function chaining service management and orchestration NFV infrastructure VNF life cycle

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A community detection based approach for Service function Chain online placement in data center network

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COMPUTER COMMUNICATIONS 2021年 169卷 168-178页

作者： Zu, Jiachen Hu, Guyu Yan, Jiajie Tang, Siqi Army Engn Univ Inst Command & Control Engn Nanjing Jiangsu Peoples R China

With the emerging paradigm of network function virtualization (NFV), the Internet Service Provider (ISP) can outsource their service functions to the cloud data center (DC) to reduce Operating Expenditures (OPEX) and Capital Expenditures (CAPEX). In this paper, we study the virtual network function (VNF) online placement and migration problem in DC considering user's Service function Chain (SFC). In order to solve the practical problems, we take the data center topology, Basic Resource Consumption, multi-tenancy, flow characteristics, and VNF relationship into consideration. Firstly, we formulate this problem into a dynamic programming model with the aim to minimize the average operational cost in a long term. To reduce the complexity of the online decision, an online two-stage heuristic (OTSH) algorithm is designed to optimally place SFCs. The OTSH consists of a community detection based differentiated greedy algorithm for SFC mapping and an offline iterative migration algorithm for VNF migrating. At last, the joint online heuristic algorithm is proven to make intelligent predictions based on the historical traffic and provide good performance guarantees by simulation.

关键词： Service function Chain network function virtualization Cloud computing Intelligent network management

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A Hybrid Virtual network function Placement Strategy for Maximizing the Profit of network Service Deployment Over Time-Varying Workloads

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IEEE ACCESS 2021年 9卷 99983-99994页

作者： Yang, Chi-Chen Padhy, Satyajit Chou, Jerry Natl Tsing Hua Univ Dept Comp Sci Hsinchu 300044 Taiwan Natl Tsing Hua Univ Inst Informat Syst & Applicat Hsinchu 300044 Taiwan

The emergence of network function virtualization (NFV) has revolutionized the infrastructure and service management of network architecture. It allows network operators to reduce costs and improve the agility of network service deployment. But finding the best VNF placement is a well-known NP-complete problem. Hence, many previous studies either formulate the problem as an Integer Linear Programming (ILP) Problem or propose greedy algorithms. However, solving ILP is time-consuming, while greedy algorithms could be far from optimal solutions. As a result, neither ILP nor greedy can make quick and accurate placement decisions for dynamic traffic workloads. Therefore, we propose a hybrid method that uses less time to maximize the overall profit of network service deployment. Our evaluations based on real backbone network traffic and topology show that our hybrid approach can achieve up to 36% profit improvement compared to a pure greedy approach, while achieving x30 times computation time speedup over a pure ILP approach.

关键词： Noise measurement Routing Greedy algorithms network function virtualization Service function chaining Optimization Licenses Virtual network function service function chain time-varying workload placement optimization integer linear programming

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