Attack-aware mMTC slice resource allocation method and apparatus, and electronic device

Abstract

One or more embodiments of the invention provide an attack-aware mMTC slice resource allocation method and apparatus, and an electronic device, an access ring composed of a group of access COs and a main CO and a convergence ring composed of a plurality of main COs and a core CO are constructed between an RRU and the core CO, and resource utilization rate thresholds of the access COs and the main COs are set; the method comprises the following steps: receiving a resource service request sent by an RRU, judging whether the RRU sending the resource service request belongs to the same main CO or not, and selecting a proper access CO or main CO to respond to the service request based on the judgment; searching an access CO with the lowest resource utilization rate on the access ring or a main CO belonging to the same access ring to respond to the resource service request, and carrying out service unloading; and if the main CO does not belong to the same main CO, calling other main COs with the lowest resource utilization rate on the convergence ring to respond to the resource service request to perform service unloading, thereby being beneficial to ensuring network security.

Description

technical field [0001] One or more embodiments of this specification relate to the technical field of resource service request response, and in particular to an attack-aware mMTC slice resource allocation method, device and electronic equipment. Background technique [0002] With the rapid development of 5G technology and the increasingly widespread application of the Internet of Things, massive machine type communication (mMTC) is one of the three typical application scenarios of 5G. The massive and diverse terminals in the 5G era will bring security risks to the 5G network. With the huge Quantified and ubiquitous smart terminals are connected to the Internet of Things. Once these terminals are invaded and used, they will become a new source of high-capacity DDoS attacks. [0003] When a DDoS attack (Distributed Denial of Service, Distributed Denial of Service) occurs, vulnerable IoT terminals are attacked and become zombies. Zombie devices access the network together with ...

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Problems solved by technology

[0005] However, the inventors found that the DDoS mitigation performance of the current solution is limited by specific machine learning algorithms, and most of them are implemented based on cloud computing platforms. This single defense method has risks such as low delay sensitivity and single-point attacks. , it is difficult to detect and take defensive measures in the early stage of DDoS attacks

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