SDNFV Based Threat Monitoring and Security Framework for Multi-Access Edge Computing Infrastructure

Krishnan, Prabhakar; Duttagupta, Subhasri; Achuthan, Krishnashree

doi:10.1007/s11036-019-01389-2

Cited by 30 publications

(18 citation statements)

References 40 publications

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“…In the decision making approach, the probability of attack is identified using an Improved Support Vector Machine (ISVM) based classification technique and the training data is obtained from the samples given in [28]. The training data comprises of a binary labeled data which indicates attack probability of with both low and high chances for attack.…”

Section: Decision Making Approachmentioning

confidence: 99%

“…Hence, to protect the network, a light weight security mechanism has to be applied and, thereby the Intrusion Detection System (IDS) acts as a protective wall in securing the WSN. The IDS helps to identify the misbehaving sensor nodes, which violates the security mechanism and notify the report to the administrator for further countermeasures [28]. However, most of the IDS system works only on a particular type of attack (i.e.)…”

Section: Introductionmentioning

confidence: 99%

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Cross Layer Security Based Intrusion Detection System (CLS-IDS) For Securing Wireless Sensor Network (WSN)

Nandala¹,

Sumalatha²

2021

DSA

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The Wireless Sensor Network (WSN) consists of large number of tiny sensor nodes that are deployed randomly in the harsh or unattended environment. Generally, the sensor nodes are prone to unexpected failures and faults as they are resource constrained. Therefore, to maximize the network lifetime and to meet the QoS requirements by analyzing faults, cross layer design is considered to be best optimization technique to improve overall network performance. Previous research work developed a cross layer security based intrusion detection system (CLS-IDS) framework that has improved network performance, minimal energy consumption and to prolong network life, meeting QoS requirements. However, this CLS-IDS method cannot detect the faults happening at various places at the same time. In addition, when the cross layer design method focuses only on the inter-layer interaction and the change of the node, it may not be able to adjust to dynamic change in network conditions. This cross layer design is predominantly vulnerable to various types of attacks at various protocol stack layers. This proves that it is essential to provide effective security based intrusion detection system and fault monitoring techniques. The proposed work focuses on the Cross Layer Security based Intrusion Detection System (CLS-IDS) framework, which is considered to be a vital constraint in escalating the network performance. The security framework considers both the trust value and the fault value to identify the malicious nodes based on the pre-defined trust threshold value. The fault monitoring system uses the Improved Support Vector Machine (ISVM) classifier to isolate and remove fault nodes. The experimental results show that proposed CLS-IDS perform better when compared to existing cross layer protocol designs.

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Section: Decision Making Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cross Layer Security Based Intrusion Detection System (CLS-IDS) For Securing Wireless Sensor Network (WSN)

Nandala¹,

Sumalatha²

2021

DSA

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“…In [32] a new approach to network threats utilizing three pillars of 5G is proposed. It integrates multi-layer collective security intelligence to a converged SDN/NFV architecture in standard MEC technology.…”

Section: Introductionmentioning

confidence: 99%

Verticals in 5G MEC-Use Cases and Security Challenges

et al. 2021

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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 facilitated the implementation of such requirements of 5G, which resulted 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 paper, 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. Next, 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 identify the expected security requirements. Finally, 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.

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“…However, there are some challenges in the distributed control structure of SDN-enable MEC architecture, such as DDoS attacks [3][4][5] and load balancing [6][7][8]. In wireless networks, the peer-to-peer quality of service in the network needs to be optimized [9] and control plane scalability of distributed networks [10].…”

Section: Introductionmentioning

confidence: 99%

A MECS redistribution algorithm for SDN-enable MEC using response time and transmission overhead

Fan

et al. 2021

Wireless Netw

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The software-defined networks-enable mobile edge computing (SDN-enable MEC) architecture, which integrates SDN and MEC technologies, realizes the flexibility and dynamic management of the underlying network resources by the MEC, reduces the distance between the access terminal and computing resources and network resources, and increases the terminal's access to resources. However, the static distribution relationship between MEC servers (MECSs) and controllers in the multi-controller architecture may result in unbalanced load distribution among the controllers, which would degrade network performance. In this paper, a multi-objective optimization MECS redistribution algorithm (MOSRA) is proposed to decrease the response time and overhead. A controller response time model and link transmit overhead model are introduced as basis of an evolutionary algorithm which is proposed to optimize MECS redistribution. The proposed algorithm aims to select an available sub-optimizes individual by using a strategy based coordination transformation from Pareto Front. That is, when the master controller of the MECS is redistributed, both of the network overhead of the MECS to the controller and the response time of the controller to the MECS processing request are optimized. Finally, the simulation results demonstrate that the MOSRA can solve the redistribution problem in different network load levels and different network sizes within the effective time, and has a lower control plane response time, while making the edge network plane transmission overhead lower, compared with other algorithms .

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SDNFV Based Threat Monitoring and Security Framework for Multi-Access Edge Computing Infrastructure

Cited by 30 publications

References 40 publications

Cross Layer Security Based Intrusion Detection System (CLS-IDS) For Securing Wireless Sensor Network (WSN)

Cross Layer Security Based Intrusion Detection System (CLS-IDS) For Securing Wireless Sensor Network (WSN)

Verticals in 5G MEC-Use Cases and Security Challenges

A MECS redistribution algorithm for SDN-enable MEC using response time and transmission overhead

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