Given the Parallel Wireless solution includes an Open RAN Aggregator that resides between a RAN and the Core network, it quite easily enables MOCN, by having the ability to interrogate the traffic and route to the proper core for 4G, 3G or 2G traffic. This then allows RAN sharing to happen without complication to any of the home networks, the software platform simply requires connections to each core and handles the heavy lifting of routing of the traffic properly. In turn, each core network manages their users as if they are on the home network. This allows services such as RCS, VoLTE, LI, etc. to remain viable regardless of the fact that the User is not in effect on a Home network.
At a basic level, an IMSI catcher consists of two main parts: a radio frontend for sending and receiving radio waves and a network backend for simulating a cellular core network. Today, anyone with a software-defined radio (SDR) and a computing device running an open-source base station program (like OpenBTS) can effectively operate an IMSI catcher.
This paper presents a method to configure the SIDF function using GPU to speed up 5G AKA in the mMTC environment. The functions of the 5G core network are implemented the in software to freely configure the network. Therefore, in this paper, when the 5G home network SIDF performs the ECIES decryption operation, a new approach is introduced to quickly perform the 5G key agreement process.
In Open5gs , an open-source 5G network project, SIDF is not implemented separately but is included in the UDM function. Moreover, there was no separate implementation of public-key cryptography, except for the implementation (embedded) of the null type. Looking at the SIDF implementation in Free5GC , another 5G network open-source project, the SIDF function was not implemented separately, similar to Open5gs. However, it differed from Open5gs regarding the ECC algorithm implementation for SUCI profiles A and B, which was implemented in UDM to deconceal SUCI. Because Free5GC is a 5G network-based open-source project, it has a format that is called every time a single HTTP message is transmitted. Particularly, the encryption algorithm was implemented in Go Language with no specific high-speed technique applied . Looking at OpenAirInterface5g , another 5G network open-source project, the OpenAirInterface5g project is divided into 5G RAN and 5G CN. In particular, the OpenAirInterface5g CN project was aimed at making a CN stack fully compatible with 3gpp. The OpenAirInterface5g CN project is currently in progress up to version 1.3 and includes various 5G NFs such as AMF, AUSF, and NRF. The most prominent feature with other open sources is that C and C++ are used as the major languages, so there is an advantage for 5G network configurators to use these open sources in the actual 5G environment. However, as in the above two open-source projects, the SIDF function is not implemented separately; in particular, the method of handling SUCI within AUSF and UDM is not specified, and it is hard coded in the 5G RAN project. Like [25, 26, 28], the 5G core network has the characteristic of freely configuring the network by implementing each NF in the software. This is not only a 5G design idea but has several advantages. However, when composing SIDF with software alone, it was judged that the ECIES operation speed was slow like the two open sources, or it could not satisfy the mMTC requirements. Subsequently, in our study, when the 5G home network SIDF performs the ECIES decryption operation, instead of using the methods introduced in the abovementioned studies, we introduce a method that quickly performs the 5G key agreement process with a novel approach.
In addition, as suggested in this paper, when cryptographic algorithms and cryptographic systems are newly installed in the system, they should be evaluated through various evaluation methods by comparing operation time, power consumption, flexibility, financial cost, etc., with other commercial equipment. This is because these evaluation methods are items to consider when an encryption algorithm or system is operated in actual equipment. Firstly, I would like to compare it with other 5G commercial products in terms of power consumption. Power consumption of cryptographic algorithms becomes particularly important in IoT equipment, embedded equipment, and 5G UE that are currently used in various environments. IoT equipment, embedded equipment, 5G UE, etc., are equipment in which equipment is operated through batteries, not in an environment in which power is generally supplied at all times. Therefore, power consumption when a cryptographic algorithm or cryptographic system operation is added to the device is a very critical issue. However, the 5G core network environment that this paper focuses on does not require low-power computation and low-power cryptographic algorithms. 5G core network is an environment that requires more high security level (depending cryptographic algorithm key length) and compatibility of cryptographic algorithms than the advantages obtained by using low-power computation and low-power cryptographic algorithms . In addition, the maximum power consumption of device B and device C used in the SIDF configuration method using GPU presented in this paper is about 260 watts [42, 43]. This value is not an absolute comparison because it is the maximum consumption of the GPU device, not the power consumption of the cryptographic algorithm, but it does not show a big difference when compared with the maximum power consumption of 5G equipment.
3GPP has defined 5G Core to utilize cloud virtualisation, service-based architecture (SBA) across all 5G functions and procedures, including authentication, security, session management and aggregation of traffic from end devices. The 5G core network supports the Virtualization of software functions to use NFVI in design 5G Networks, including MEC infrastructure. The new architecture has adopted separation of user plane and control plane functions, which enables independent scaling of the control and user plane functions, e.g. a Mobile Network Operator (MNO) can add more user plane functions without adding more control plane and vice versa depending on deployment strategies. User plane functions could be distributed geographically close to 5G RAN to minimise user plane latency, while control plane functions could be centralised to get benefits of Virtualization.
Addressing vulnerabilities plays a central role in 5G security risk management. In addition to procuring software and hardware from trusted vendors, Verizon has established a robust vulnerability management process, outlined in Figure 4 below. These processes will continue to evolve and will play an increasingly central role through the transition to Stand Alone 5G, with its virtualized, software-defined 5G core. 2b1af7f3a8