LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Side Channel Attack-Aware Resource Allocation for URLLC and eMBB Slices in 5G RAN

Photo by vita_belvita from unsplash

Network slicing is a key enabling technology to realize the provisioning of customized services in 5G paradigm. Due to logical isolation instead of physical isolation, network slicing is facing a… Click to show full abstract

Network slicing is a key enabling technology to realize the provisioning of customized services in 5G paradigm. Due to logical isolation instead of physical isolation, network slicing is facing a series of security issues. Side Channel Attack (SCA) is a typical attack for slices that share resources in the same hardware. Considering the risk of SCA among slices, this paper investigates how to effectively allocate heterogeneous resources for the slices under their different security requirements. Then, a SCA-aware Resource Allocation (SCA-RA) algorithm is proposed for Ultra-reliable and Low-latency Communications (URLLC) and Enhanced Mobile Broadband (eMBB) slices in 5G RAN. The objective is to maximize the number of slices accommodated in 5G RAN. With dynamic slice requests, simulation is conducted to evaluate the performance of the proposed algorithm in two different network scenarios. Simulation results indicate that compared with benchmark, SCA-RA algorithm can effectively reduce blocking probability of slice requests. In addition, the usage of IT and transport resources is also optimized.

Keywords: embb slices; channel attack; side channel; resource allocation; attack; aware resource

Journal Title: IEEE Access
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.