Secure northbound interface for SDN applications with NTRU public key infrastructure

Natanzi, Seyed Bagher Hashemi; Majma, Mohammad Reza

doi:10.1109/kbei.2017.8325020

Cited by 8 publications

(4 citation statements)

References 2 publications

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“…Finally, in [53], the authors generate an architecture that only provides data to trusted third-party applications. For this purpose, the architecture makes use of the northbound interface with the NSS digital signature implementation and the NTRU encryption algorithm.…”

Section: A Northbound Interface and Application Planementioning

confidence: 99%

“…Behavior-based access control method + IDS [48] API abuse, DoS, Malicious apps Publish/Subscribe model [49] Lack of authentication mechanisms between the app and the Controller Independent mechanism [50] Lack of authentication mechanisms between the app and the Controller Floodlight-based mechanism [51] [52] Nonencrypted communication between app and controller Lack of management over reliability Lack of access control Use of REST-like functions [53] Lack of third-party app authentication NTRU encryption algorithm and NSS digital signatures [54] Malicious apps NTRU encryption algorithm S=spoofing, T=tampering, R=repudiation, I= information disclosure, D=denial of service, E=elevation of privilege…”

Section: B East/westbound Interface and Control Planementioning

confidence: 99%

“…However, there are other algorithms that could be used, such as NTRU or ECC, depending on the deployment. Thus, it has been observed that NTRU has high performance in smaller-scale environments [53]. However, ECC, given its shorter key length, works faster [75].…”

Section: B Regarding Sdn Interfacesmentioning

confidence: 99%

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A Survey of the Main Security Issues and Solutions for the SDN Architecture

et al. 2021

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The software-defined networking (SDN) paradigm proposes the decoupling of control and data planes and a centralized software-oriented management approach based on a central controller, easing the development of new applications and services. These design principles pave the way for a more flexible, fast, and dynamic software-controlled network. However, in terms of security, the elements that comprise the SDN architecture present several vulnerabilities, which could be exploited by attackers to carry out malicious actions and thus affect the network and its services. Although for several years, some studies have already focused on identifying the weaknesses of the SDN layer structure, the nature of the attacks, and possible solutions for this paradigm, the literature contains few contributions that review and discuss this topic in an integral fashion. This paper provides a comprehensive, updated, and detailed review of the main security issues and mitigating measures for all layers and interfaces of the SDN architecture, classifying the contributions according to the STRIDE threat modeling methodology categories. Finally, this manuscript identifies, discusses, and synthesizes open challenges and future research directions in this area.

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Section: A Northbound Interface and Application Planementioning

confidence: 99%

Section: B East/westbound Interface and Control Planementioning

confidence: 99%

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A Survey of the Main Security Issues and Solutions for the SDN Architecture

et al. 2021

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“…Southbound interface connects the data and the control planes [11]. In addition, there is an application plane that composes of end user applications which interact with the SDN controllers via the northbound interface to perform specific tasks such as mobility management, routing, access control, security, file transfer, and supervising [12], [13], [14].…”

Section: Introductionmentioning

confidence: 99%

A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

Alablani

Arafah²

2023

IEEE Access

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Heterogeneous ultra-dense networks (HUDNs) are one of the key enabling technologies for the fifth-generation (5G) networks. They aim to provide high capacity, low installation cost, and distributed traffic loads. The cell selection is a challenging issue in HUDNs, due to the different characteristics of base stations (BSs) and the existence of a large number of them. Thus, the traditional cell selection scheme is not applicable in such a network. In this paper, a novel adaptive cell selection strategy is proposed, called adaptive two-tier based on adaptive boosting (A2T-Boost). It can adapt to the various characteristics of base stations, as well as the different movement features of mobile stations such as vehicles and pedestrian. It is a software-defined networking (SDN)/machine learning (ML)-based scheme. A real-world case is considered in the downtown of Los Angeles city. Simulation results demonstrate that A2T-Boost achieves high prediction performance and it outperforms other related schemes in terms of average number of handovers (HOs) by up to 50%. Moreover, it enhances the average achievable downlink sum-rates and network energy efficiency achieved by vehicles by up to 33.76%. Furthermore, the average packet delay is decreased using the proposed scheme by up to 12.87%.

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