Self-Aware Networks That Optimize Security, QoS, and Energy

Gelenbe, Erol; Domańska, Joanna; Fröhlich, Piotr; Nowak, Mateusz; Nowak, Sławomir

doi:10.1109/jproc.2020.2992559

Cited by 44 publications

(39 citation statements)

References 117 publications

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“…How does our work compare with MUD [ 21 ] (RFC8520)? As already mentioned in Section 2 , Autopolicy was developed independently for edge security in a larger SerIoT project [ 5 ], and as such we consider our proposal complementary, not contrary. We believe it can foster the IETF standardization process and in general encourage better network operation practices.…”

Section: Discussionmentioning

confidence: 99%

“… Notifying about violations of traffic profiles, for their analysis by additional SDN controller logic or operator action. In such a case, it is possible to include this information in the routing mechanism, influencing the selection of the packet route [ 5 ]. …”

Section: Discussionmentioning

confidence: 99%

“…Autopolicy was designed for the needs of the SerIoT project [ 5 ], as one of its edge security components, securing the network from potentially malicious endpoints. SerIoT aims at managing information security of IoT platforms and networks in a holistic, cross-layer manner—integrating IoT sensors, devices, honeypots, Software-Defined Networking (SDN) routers, and controllers.…”

Section: Introductionmentioning

confidence: 99%

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Autopolicy: Automated Traffic Policing for Improved IoT Network Security

Foremski

Nowak

Fröhlich

et al. 2020

Sensors

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A 2.3Tbps DDoS attack was recently mitigated by Amazon, which is a new record after the 2018 GitHub attack, or the famous 2016 Dyn DNS attack launched from hundreds of thousands of hijacked Internet of Things (IoT) devices. These attacks may disrupt the lives of billions of people worldwide, as we increasingly rely on the Internet. In this paper, we tackle the problem that hijacked IoT devices are often the origin of these attacks. With the goal of protecting the Internet and local networks, we propose Autopolicy: a system that automatically limits the IP traffic bandwidth—and other network resources—available to IoT devices in a particular network. We make use of the fact that devices, such as sensors, cameras, and smart home appliances, rarely need their high-speed network interfaces for normal operation. We present a simple yet flexible architecture for Autopolicy, specifying its functional blocks, message sequences, and general operation in a Software Defined Network. We present the experimental validation results, and release a prototype open source implementation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Autopolicy: Automated Traffic Policing for Improved IoT Network Security

Foremski

Nowak

Fröhlich

et al. 2020

Sensors

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“…The path congestion metric is the maximum of the link load metric, the port haven paths with the least congestion is selected. In [97], the authors propose a Smart Service Manager that uses RNN and reinforcement learning. The routing and server allocations decisions use measurement data based on machine learning.…”

Section: Distributed Load Balancingmentioning

confidence: 99%

A Taxonomy of Load Balancing Mechanisms in Centralized and Distributed SDN Architectures

Chahlaoui

Dahmouni

2020

SN COMPUT. SCI.

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Recent Research have shown that software-defined networking (SDN) drastically improves network resource utilization, manages today's complex networks and reduces cost. The rapid development of technology and the explosively growing information services as well as the increasing number of users, have made the load distribution a huge issue that could eventually impact the network's performance and its quality of service. The need for SDN comes from the load-balancing problematic which could reduce the availability of network applications, resource utilization and QoS indicators such as latency, throughput and response time. In this paper, we analyze the impact of software-defined networks design and the architecture of its control plane on the load-balancing methods efficiency. We present a detailed analysis of some load-balancing algorithms and metrics in centralized and distributed SDN architectures. We also introduce some of the load-balancing mechanisms applied in 5G networks in particular.

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“…However, it creates raises risks that go way beyond the individal technologies such as the Internet, wireless networks and machine to machine systems [4], [5]. In addition to risks related to system malfunctions [6], quality of service (QoS) failures, and excessive energy consumption, the theft and tampering of data, conventional network attacks and attacks that deplete the energy of autonomous sensors and actuators also need to be considered [7]- [13]. Since IoT devices can carry out real-time measurements and controls much faster than human reaction times, we must design IoT networks that both detect and mitigate security risks automatically and adaptively, while preserving Quality of Service (QoS), and energy efficiency [6], [14].…”

Section: Introductionmentioning

confidence: 99%

IoT Network Attack Detection and Mitigation

Gelenbe¹,

Fröhlich²,

Nowak³

et al. 2020

2020 9th Mediterranean Conference on Embedded Computing (MECO)

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Cyberattacks on the Internet of Things (IoT) can cause major economic and physical damage, and disrupt production lines, manufacturing processes, supply chains, impact the physical safety of vehicles, and damage the health of human beings. Thus we describe and evaluate a distributed and robust attack detection and mitigation system for network environments where communicating decision agents use Graph Neural Networks to provide attack alerts. We also present an attack mitigation system that uses a Reinforcement Learning driven Software Defined Network to process the alerts generated by the attack detection sysem, together with Quality of Service measurements, so as to reroute sensitive traffic away from compromised network paths using. Experimental results illustrate both the detection and rerouting scheme.

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Self-Aware Networks That Optimize Security, QoS, and Energy

Abstract: In this article, self-awareness in networking is discussed. Examples of advantages of self-aware networks with respect to quality of service, energy, and security are presented.

Cited by 44 publications

References 117 publications

Autopolicy: Automated Traffic Policing for Improved IoT Network Security

Autopolicy: Automated Traffic Policing for Improved IoT Network Security

A Taxonomy of Load Balancing Mechanisms in Centralized and Distributed SDN Architectures

IoT Network Attack Detection and Mitigation

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