On Sustained Zero Trust Conceptualization Security for Mobile Core Networks in 5G and Beyond

Bello, Yahuza; Refaey, Ahmed; Ulema, Mehmet; Kolipali, Juanita

doi:10.1109/tnsm.2022.3157248

Cited by 26 publications

(8 citation statements)

References 29 publications

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“…The boundary consists of Snort and Suricata intrusion detection and prevention security gateways. Similar to the virtual software defined perimeter (vEPC) proposed by Bello et al [40], this study's zero trust software-based system acts as a security gateway for all distributed servers. Sparkone through Sparkfour are designed to operate securely in most cloud architectures in this model by integrating an SDN security stack on each physically distanced server.…”

Section: B Tests 2-3 Perimeter-less Security Resultsmentioning

confidence: 99%

Next-Generation Intrusion Detection and Prevention System Performance in Distributed Big Data Network Security Architectures

Hart,

Dave,

Richardson

2023

IJACSA

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Big data systems are expanding to support the rapidly growing needs of massive scale data analytics. To safeguard user data, the design and placement of cybersecurity systems is also evolving as organizations to increase their big data portfolios. One of several challenges presented by these changes is benchmarking real-time big data systems that use different network security architectures. This work introduces an eightstep benchmark process to evaluate big data systems in varying architectural environments. The benchmark is tested on realtime big data systems running in perimeter-based and perimeterless network environments. Findings show that marginal I/O differences exist on distributed file systems between network architectures. However, during various types of cyber incidents such as distributed denial of service (DDoS) attacks, certain security architectures like zero trust require more system resources than perimeter-based architectures. Results illustrate the need to broaden research on optimal benchmarking and security approaches for massive scale distributed computing systems.

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Section: B Tests 2-3 Perimeter-less Security Resultsmentioning

confidence: 99%

Next-Generation Intrusion Detection and Prevention System Performance in Distributed Big Data Network Security Architectures

Hart,

Dave,

Richardson

2023

IJACSA

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“…Artificial Intelligence algorithms can deter malicious requests and thwart network performance degradation in real-time or almost real-time [73]. This would be essential in mission-critical sectors such as healthcare, air defense and autonomous vehicle networks [74].…”

Section: Potential Future Workmentioning

confidence: 99%

Security of Zero Trust Networks in Cloud Computing: A Comparative Review

et al. 2022

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Recently, networks have shifted from traditional in-house servers to third-party-managed cloud platforms due to its cost-effectiveness and increased accessibility toward its management. However, the network remains reactive, with less accountability and oversight of its overall security. Several emerging technologies have restructured our approach to the security of cloud networks; one such approach is the zero-trust network architecture (ZTNA), where no entity is implicitly trusted in the network, regardless of its origin or scope of access. The network rewards trusted behaviour and proactively predicts threats based on its users’ behaviour. The zero-trust network architecture is still at a nascent stage, and there are many frameworks and models to follow. The primary focus of this survey is to compare the novel requirement-specific features used by state-of-the-art research models for zero-trust cloud networks. In this manner, the features are categorized across nine parameters into three main types: zero-trust-based cloud network models, frameworks and proofs-of-concept. ZTNA, when wholly realized, enables network administrators to tackle critical issues such as how to inhibit internal and external cyber threats, enhance the visibility of the network, automate the calculation of trust for network entities and orchestrate security for users. The paper further focuses on domain-specific issues plaguing modern cloud computing networks, which leverage choosing and implementing features necessary for future networks and incorporate intelligent security orchestration, automation and response. The paper also discusses challenges associated with cloud platforms and requirements for migrating to zero-trust architecture. Finally, possible future research directions are discussed, wherein new technologies can be incorporated into the ZTA to build robust trust-based enterprise networks deployed in the cloud.

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“…The model used a lightweight PRESENT algorithm with an 80‐bit key size and 64‐bit block size and processed 32 cycles per block. In Reference 22, an authentication‐based approach, a software‐defined virtual perimeter framework, has been proposed to provide secure communications within mobile core networks based on two machine learning classifiers (multilayer perceptron and support vector machine [SVM]). System components are virtualized and placed within a core network to provide a zero‐trust environment where only authenticated and authorized core network elements can access each other.…”

Section: Introductionmentioning

confidence: 99%

Trust‐aware task load balancing in multi‐access edge computing based on blockchain and a zero trust security capability framework

Ali,

Gregory,

2023

Trans Emerging Tel Tech

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The need for low‐latency service support at the network edge has increased due to new applications such as autonomous vehicles, facial recognition, and augmented reality. Multi‐access edge computing (MEC) has emerged as a promising component of next‐generation 5G and 6G networks that provides additional storage and computing capacity at the network edge to enhance application performance, load balancing, and reduce latency. Security challenges remain, and a zero trust security framework has the potential to reduce risk and improve visibility. A zero trust management module is introduced to authenticate users after a successful registration. This article presents a three‐layer MEC model implementing a trust‐aware load balancing decision process. A Q‐learning algorithm is used to estimate trust values. Task trust and indirect trust relationships are recorded using blockchain technology. Blockchain will enable a transparent and secure mechanism that contributes to secure resource management in an MEC environment. The results provided by a framework simulation highlight the improved security outcome.

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On Sustained Zero Trust Conceptualization Security for Mobile Core Networks in 5G and Beyond

Cited by 26 publications

References 29 publications

Next-Generation Intrusion Detection and Prevention System Performance in Distributed Big Data Network Security Architectures

Next-Generation Intrusion Detection and Prevention System Performance in Distributed Big Data Network Security Architectures

Security of Zero Trust Networks in Cloud Computing: A Comparative Review

Trust‐aware task load balancing in multi‐access edge computing based on blockchain and a zero trust security capability framework

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