Uplifting Healthcare Cyber Resilience with a Multi-access Edge Computing Zero-Trust Security Model

Ali, Belal; Gregory, Mark A; Li, Shuo

doi:10.1109/itnac53136.2021.9652141

Cited by 15 publications

(16 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are consistent message flows between the eNodeB and UEs. We have discussed the details in our previous work 34 . Our PoC experiments aim to evaluate the practicality and promise of our proposal in upholding the ZTS guiding principles for offloading tasks between trusted and reliable MEC servers.…”

Section: Trust‐aware Authentication and Task Load Balancing In Mecmentioning

confidence: 99%

“…Therefore, the user needs access to a specific service from the MEC server to meet its stringent performance requirements via computational offloading. The computational model can be defined in three steps following the models introduced in related works 9,25,34 . First the UE requests access by uploading a specific size of data that needs to be processed by the MEC server through the radio access network.…”

Section: Trust‐aware Authentication and Task Load Balancing In Mecmentioning

confidence: 99%

See 1 more Smart Citation

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

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Trust‐aware Authentication and Task Load Balancing In Mecmentioning

confidence: 99%

Section: Trust‐aware Authentication and Task Load Balancing In Mecmentioning

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

Self Cite

View full text Add to dashboard Cite

show abstract

“…e proposed model is constructed in three layers: UE, edge, and cloud, as depicted in Figure 2. e layers and their capabilities are discussed in our previous work [3]. e MEC ZTS architecture consists of the following entities:…”

Section: Proposed Systemmentioning

confidence: 99%

“…In [3], we have incorporated the fundamental ZTS model into the MEC reference architecture. e ZTS model in the MEC host layer is not supposed to trust any user due to increasing insider threats.…”

Section: Proposed Systemmentioning

confidence: 99%

See 1 more Smart Citation

A Maturity Framework for Zero-Trust Security in Multiaccess Edge Computing

Ali

Hijjawi

Campbell

et al. 2022

Security and Communication Networks

View full text Add to dashboard Cite

Multiaccess Edge Computing (MEC) has been adopted to provide an environment that supports cloud computing capabilities and IT services at the network edge. The open architecture of cloud computing and network access at the edge provides malicious actors with many attack vectors. The MEC system entities cannot be permanently trusted due to the dynamic and shareable nature of MEC deployments. This paper presents a classification of MEC entities that can be used to define security controls based on the Zero-Trust Security approach. The security controls are organised into a maturity framework that can be used to guide the systematic development of trust and security in an MEC environment. In this framework, a Minimum Viable Security posture defines the first operational step towards full implementation of Zero-Trust Security in an MEC environment.

show abstract