MEC-enabled 5G use cases : a survey on security vulnerabilities and countermeasures |
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Author: | Ranaweera, Pasika1; Jurcut, Anca1; Liyanage, Madhusanka1,2 |
Organizations: |
1University College Dublin, Ireland 2University of Oulu, Oulu, Finland |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 14.9 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe202301112370 |
Language: | English |
Published: |
Association for Computing Machinery,
2022
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Publish Date: | 2023-01-11 |
Description: |
AbstractThe future of mobile and internet technologies are manifesting advancements beyond the existing scope of science. The concepts of automated driving, augmented-reality, and machine-type-communication are quite sophisticated and require an elevation of the current mobile infrastructure for launching. The fifth-generation (5G) mobile technology serves as the solution, though it lacks a proximate networking infrastructure to satisfy the service guarantees. Multi-access Edge Computing (MEC) envisages such an edge computing platform. In this survey, we are revealing security vulnerabilities of key 5G-based use cases deployed in the MEC context. Probable security flows of each case are specified, while countermeasures are proposed for mitigating them. see all
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Series: |
ACM computing surveys |
ISSN: | 0360-0300 |
ISSN-E: | 1557-7341 |
ISSN-L: | 0360-0300 |
Volume: | 54 |
Issue: | 9 |
Pages: | 1 - 37 |
DOI: | 10.1145/3474552 |
OADOI: | https://oadoi.org/10.1145/3474552 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Funding: |
This work is partly supported by the Academy of Finland under the 6Genesis (Grant No. 318927) project. |
Academy of Finland Grant Number: |
318927 |
Detailed Information: |
318927 (Academy of Finland Funding decision) |
Copyright information: |
© 2021 Association for Computing Machinery. This is the author's version of the work. The definitive Version of Record was published in ACM Computing Surveys, https://doi.org/10.1145/3474552.
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