A Native Intelligent and Security 6G Network Architecture

Bao, Shihan; Sun, Wanfei; Xu, Hui

doi:10.1109/icccworkshops55477.2022.9896706

Cited by 4 publications

(1 citation statement)

References 14 publications

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“…Native AI represents a disruptive paradigm where AI capabilities are leveraged to realize or augment the existing capabilities of a system [103]. Security-wise, this provides many advantages for bolstering threat detection and prevention [104][105][106]. AI security mechanisms can facilitate the analysis of user behavior, system interactions, and network traffic [107] within applications to identify anomalies or suspicious activities that may indicate potential security breaches.…”

Section: Native Ai and Security As A Service (Secaas)mentioning

confidence: 99%

Security in Cloud-Native Services: A Survey

Theodoropoulos,

Rosa,

Benzaid

et al. 2023

JCP

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Cloud-native services face unique cybersecurity challenges due to their distributed infrastructure. They are susceptible to various threats like malware, DDoS attacks, and Man-in-the-Middle (MITM) attacks. Additionally, these services often process sensitive data that must be protected from unauthorized access. On top of that, the dynamic and scalable nature of cloud-native services makes it difficult to maintain consistent security, as deploying new instances and infrastructure introduces new vulnerabilities. To address these challenges, efficient security solutions are needed to mitigate potential threats while aligning with the characteristics of cloud-native services. Despite the abundance of works focusing on security aspects in the cloud, there has been a notable lack of research that is focused on the security of cloud-native services. To address this gap, this work is the first survey that is dedicated to exploring security in cloud-native services. This work aims to provide a comprehensive investigation of the aspects, features, and solutions that are associated with security in cloud-native services. It serves as a uniquely structured mapping study that maps the key aspects to the corresponding features, and these features to numerous contemporary solutions. Furthermore, it includes the identification of various candidate open-source technologies that are capable of supporting the realization of each explored solution. Finally, it showcases how these solutions can work together in order to establish each corresponding feature. The insights and findings of this work can be used by cybersecurity professionals, such as developers and researchers, to enhance the security of cloud-native services.

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