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25 March 2025

A Survey of 5G Core Network User Identity Protections, Concerns, and Proposed Enhancements for Future 6G Technologies

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Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
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Future Internet2025, 17(4), 142;https://doi.org/10.3390/fi17040142
This article belongs to the Special Issue Moving Towards 6G Wireless Technologies—2nd Edition
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Abstract

Fifth-Generation (5G) cellular networks extensively utilize subscriber identifiers throughout the protocol stack, thereby linking subscribers to their activities on the network. With the inherent use of linked identifiers comes the potential capability to track subscribers’ location and behavior, which poses critical challenges for user identity protections and privacy in sensitive applications like military or healthcare operating over public 5G infrastructure. The reliance on such personal identifiers threatens a user’s right to privacy and brings to light the importance of proper mechanisms to mitigate these risks for current and future cellular network technologies. In this paper, we explore the 5G specifications to understand the most important list of identifiers and their use across Virtual Network Functions (VNF), and points of exposure within the Core Network (CN). We also examine the existing literature regarding identity protections and efforts to mitigate privacy concerns targeted in the CN. Findings include the need for a trust relationship between users and their network providers to protect and safeguard their identity. While 5G technology has greater user identity protections compared to previous cellular generations, our analysis shows that several areas of concern remain, particularly in the exchange of subscriber metadata. This work also finds that new technologies adopted in 5G networks add further complexity to maintaining a strict posture for safeguarding user identity and privacy protections. This paper also reviews the scientific community’s proposed enhancements for future 6G networks’ user identity and privacy protections, with a focus on emerging Artificial Intelligence (AI) and Machine Learning (ML) applications. The ethical implications of private or anonymous communications are also carefully weighed and examined to understand the multifaceted nature of this topic. Our work is concluded by proposing important further research to reduce the prevalence and reliance on personal identifiers such as the SUPI (Subscription Permanent Identifier) within 5G Core operations to help better protect user identity. We also propose replacing the widespread use of the SUPI between VNFs with ephemeral identifiers, building upon efforts by 3GPP aiming for 5G to protect the SUPI from eavesdroppers.

1. Introduction

1.1. Technological Privacy in the Modern Day

Throughout everyday life, a person may expect a basic amount of privacy: locks on doors, shades on windows, fenced-in yards, lack of surveillance, etc. In our modern information society, however, there is also an increasing awareness that privacy expectations may be reduced in public environments and online activities. Categorizing these two philosophical systems could lead to an interpretation with two main privacy ‘spaces’: personal and public. The approach to one’s personal privacy space may be more commonly seen as influenced by current cultural norms along with individual preferences, thereby shaping expectations. The same applies to the public privacy space, where it has been agreed upon for societies to at least retain a basic amount of privacy per person. With the inclusion of technological devices, networks, and utilities in daily life, the problem of maintaining privacy and trust grows to large proportions.
In the context of 5G networks, users have a basic expectation that their communications are secured by the network of their choice. Network operators have an important role in safeguarding users’ data and privacy by properly deploying networks that strictly follow 3GPP standards while ensuring that all efforts are made to protect their end users. A user’s ‘data’ can have different definitions depending on the context. In one sense, ‘data’ means the packets that users send across the service, such as between websites, cloud services, or other users, as well as text messages and phone calls. In other definitions, ‘data’ may refer to metadata, which can include analytics around usage, conversations, location, personally identifiable data, connection and disconnections, IP addresses, hardware identifiers, etc. This paper focuses on how 5G networks handle users’ metadata, specifically their identity, and efforts underway aiming to achieve a more anonymous user experience for users connected to public or private 5G infrastructure. Anonymous connections in public infrastructure have many real-world applications in healthcare and secure military and government operations. However, they also give rise to potential abuse by malicious parties or for unlawful activities. As such, a balanced approach is needed that both protects regular users and helps to enforce applicable laws to prevent unlawful activity. As the standards for 5G networks are region agnostic, they require adherence to local laws and regulations, meaning user identity protections could vary around the world.
Basic concepts around secure and anonymous internet systems can be modeled after the Tor project [1]. Tor is a decentralized network of machines that route and encrypt user information while hiding the user’s true identity. Tor users who interact with internet systems while connected to the Tor network can maintain an anonymous profile through the many mechanisms implemented to protect user identity and ensure their privacy. While the usage of Tor brings multiple ethical and political implications, it has been proven over time to be an effective mechanism for maintaining anonymity while connecting to online services [2].

1.2. Focus of This Paper

Our study of the identifiers used in 5G networks and proposed methods for future 6G networks is focused on operations within the Core Network. Furthermore, our study looks at the specific implications of how these identifiers are used within the 5G standard to strengthen user identity protections while also raising discussions around vendor and network operator trust. Other works in the realm of 5G privacy and security give insight into the vast landscape of 5G technologies and may briefly touch on the topic of user identity protections [3,4,5,6,7,8,9,10]. These works give much needed background for many different avenues of current research on 5G networks and aspects of maintaining strict guidelines for user identity protections. We look to utilize the information in these surveys alongside more focused approaches around personal identifiers to strengthen the need for further protections as 6G networks anticipate massive heterogeneous connectivity of devices.
The remainder of our study will review user identity and privacy through the lens of 5G Standalone (SA) systems as 5G SA systems tend to resolve some concerns from previous generations [11], with a specific focus on the Core Network. We look into the identifiers used in 5G technology that could be traced back to users, followed by a review of the privacy impacts from new technologies adopted into 5G networks, a look at proposed schemes to heighten privacy, the impacts of lawful interception policies, and what these findings, challenges, and opportunities mean for future 6G networks. Our survey also presents our conclusions regarding the impact of 5G systems on user identity and privacy.

3. Privacy Enhancement Proposals for 5G Core Networks

With the understanding that 5G technology comprises a powerful and complex system, and the goal of maintaining user identity and privacy protections within these systems is an increasingly important and complex issue, researchers have made strides in suggesting mechanisms to create a more private experience for users of 5G networks. For example, the study shown in [38] presents different proposed solutions to conceal the long-term identity of a user across network operations, especially communications between the UE Roaming Network and the HN. The work reviews the schemes using various technologies: pseudonyms [39,40,41,42], Certificate-Based Public-Key Cryptography, Root-Key-Based Encryption, and Identity-Based Encryption. Privacy Enhanced Fast Mutual Authentication (PEFMA) is introduced as a way to conceal the user’s identity over time in normal and roaming scenarios. This approach is similar to how the SUPI is encrypted over the air but differs in that it uses different cryptographic principles. However, both solutions still require trust in the HN. The authors in [43] present mechanisms to protect privacy in Vehicular Networks, giving users conditional anonymity. Traceability to identities is possible via threshold cryptography, requiring collaboration between authorities only for misbehavior or legal abuses. In this mechanism, the HN is considered to be the Trusted Authority, which is responsible for generating and managing the cryptographic secrets. In [44], a pseudonym approach is presented that enhances the 5G-AKA (Authentication and Key Agreement) protocol to never utilize the subscriber’s personal identifier, even during the first attachment. Research conducted in [45] breaks down the vulnerabilities to user privacy in the 5G-AKA protocol. This occurs when a UE has initial authentication communications with the CN. The authors state that the AKA protocol is vulnerable to ‘guess’ and ‘replay’ attacks. An attacker that successfully completes these attacks could generate SUCIs using the HN’s public key, testing these against the network’s response of success or failure, thus leading to the possibility of an attacker tracking a user. The authors of [45] propose three methods to strengthen the 5G-AKA protocol, with the recommended solution relying on the user’s secret key stored in the SIM card, along with using the UE’s ephemeral public key that is generated during the creation of the SUCI. In their approach, the SUPI guess attack is thwarted by including a hash of the user’s secret key into the HMAC (Hash-Based Message Authentication Code), which stops hackers from replicating the HMAC process for guessed SUPIs. The replay attack is patched by storing the user’s ephemeral public key in the CN’s database, allowing for replayed SUCIs to be rejected if their public key already exists. Research in [46,47] covers aspects of anonymous IoT data in a cloud network environment. The devices are associated into groups, and each group’s elected leader is responsible for aggregating the collected data and abstracting individual identities. However, all of the 5G-specific studies still rely on the existence of a trust relationship with the 5G Core Network. No research has yet addressed the scenarios arising when the trust between users and the 5G CN is eroded.

Lawful Interception

Lawful interception (LI) refers to the standardized approaches and technical mechanisms that allow law enforcement agencies to legally monitor a user’s voice, data, and metadata on public 5G infrastructures specified in 3GPP TS 33.106 [48]. These mechanisms are designed specifically and solely for these agencies to collect information on users for high-stakes scenarios: warrants, national security, public safety, etc. These standards, while useful for lawful surveillance, require strict policy enforcement to prevent misuse against innocent and law-abiding users. These policies could lead an individual to lose trust in 5G infrastructure as their implementations and usage are not always public knowledge. In a more technical sense, as these mechanisms are built into the system, they leave potential backdoor access for attackers who are looking to gather data on specific users. Having mechanisms in place to collect user data makes these attacks more realistic and attainable compared to in the scenarios where this type of technology access is not already implemented. Research carried out in [49] shows how 5G roaming security, built to prevent billing fraud, results in unprotected attack surfaces for state-sponsored attackers. The authors argue that there is no way for a user’s smartphone to verify roaming decisions around the underlying trust assumptions in specific CNs. They tested their theories on an open-source 5G repository, Open5GS [50], which could not prevent these attacks.

4. A Look Toward Privacy in 6G Core Networks

The next generation of 6G cellular networks will inherit technologies from 5G technology, as well as multiple new additions to create even more services for users, including ultra-low-latency communications and extreme throughput in mobile applications. Advances across the protocol stack, and through further proliferation and integration with cloud infrastructure for 6G operations, will yet again revolutionize the experience for consumers and will allow for more widespread coverage and connection. A comprehensive survey covering expected 6G technologies is shown in [51]. The authors of this research condense their findings and juxtapose current 5G technologies with emerging 6G advancements. An illustration of the authors’ proposed application sectors from their findings in 6G research is presented beside the three current 5G application sectors, URLLC (Ultra-Reliable Low-Latency Communications), eMBB (Enhanced Mobile Broadband), and mMTC (Massive Machine Type Communications), in Figure 4. Further comprehensive studies of the proposed Key Performance Indicators (KPI), such as the massive increase in connected devices with network heterogeneity, and open research questions for 6G technology are outlined in [52,53]. Furthermore, notable open research areas in terms of identity protection and privacy are listed below:
Figure 4. Proposed application sectors for 6G technology extrapolated from the findings in [51].
  • Network Anomaly Detection: With the anticipated massive number of connected devices in 6G networks, there will a significant rise in the need for sophisticated network monitoring. A big contender for addressing this challenge is the use of FL for real-time, automated anomaly detection. However, evaluating and ensuring the accuracy, precision, and recall of these automated threat detection systems are important research questions.
  • Regulatory Compliance: Sixth-Generation networks will be connected across geographical borders. This brings with it the need to address differing approaches, laws, and viewpoints regarding privacy and data handling between different countries.
  • Security and Privacy in Edge Computing: With the diversity of 6G technology’s targeted use cases, there will be an inherent risk from edge computing to privacy and security. Since edge nodes may serve numerous devices at once, using shared resources, isolation of tasks will be vital for user privacy.
  • Risk Assessment Frameworks for 6G Technology: A formal risk assessment framework must be created for 6G technology, as previous models may not fully capture the expansiveness and novel network capabilities of 6G technology. This model must also serve to explain privacy threats and their impact, as well as potential mitigation strategies.
  • Privacy Concerns in Smart City and Health Services: Sixth-Generation networks will be handling a variety of potentially sensitive data, across domains such as healthcare, public services, self-driving cars, distributed energy resources, etc. Thus, in order to maintain privacy, there is a critical need for standards on data de-identification.
  • Secure IoT Protocols and Energy Efficiency: Sixth-Generation technology aims to become even more efficient in terms of energy use compared to 5G technology and also improve cryptographic security. IoT devices are considered to be resource constrained, however, which means these devices need the ability to be energy efficient without jeopardizing their security by using less secure cryptographic schemes to save power.
Regarding data collection and analytics, a comprehensive survey on utilizing the data analytics functionality within 5G technology, and expanding on this service with ML in 6G technology, is discussed in [54]. In their study, the authors reveal some open research questions around privacy and how this specific core service gathers user data. One concern raised is that O-RAN (Open-RAN) specifications currently do not outline privacy-by-design architectures, which can cause significant issues regarding untrusted cloud operators. Such considerations are seemingly left up to system designers, which is a cause for concern. This mirrors our concerns about the assumptive trustworthiness of activities within the 5G core environment with regard to user privacy protections and data handling.
The authors in [51] bring to light three new sectors that could be introduced in 6G technology that are the intersections of the current 5G applications: mULC (Massive Ultra-Reliable Low-Latency Communication), ULBC (Ultra-Reliable Low-Latency Broadband Communication), and uMBB (Ubiquitous Mobile Broadband). One of the driving factors in the innovations sought by 6G technology is the amalgamation of intelligent systems in cellular networks.

4.1. Sixth-Generation Identity Protections

Sixth-Generation technology will incorporate many new technologies into the cellular ecosystem, all while inheriting methods from the 5G. User identity protections must be a major focus in shaping 6G protocols and architectures. Ref. [55] covers comprehensive topics regarding expected technologies within 6G technology, such as visible light communications, physical layer security, healthcare AI, homomorphic encryption, etc. Specific to identity protections, it states that improvements to AKA are imperative, along with improved management of subscriber identities. End-to-end encryption in 6G networks, on the user and control plane, is needed to resist eavesdropping and tracing attacks. While adding these technologies is vital, the authors do mention the technical issues and limitations that could arise due to heightened latencies, which goes against the goal of ultra-low-latency 6G networks. Various 6G use cases are also outlined in [56,57] which show the necessity for there to be a clear definition of de-identified datasets. The lack of a standard for the architecture of these user datasets may cause privacy leaks, jeopardizing user identity protections. Federated blockchain usage is proposed in [58] as a way to manage the identities of the expected billions of connected devices. The authors present a lightweight Hardware Security Module (HSM) to store cryptographic secrets, instilling trust in devices at a fraction of the cost of traditional HSMs and enhancing security, scalability, and privacy. The presented HSMs allow for end-to-end encryption on the 6G network, and fortified security in the instance of a threat actor inside the serving network, as the HSMs exclusively control the creation and storage of the private keys. This decentralized approach to key storage elevates user identity protections and aims to ensure tamper-proof operations.

4.2. Implications of AI for Identity Protections in 6G Technology

Artificial Intelligence (AI) and Machine Learning (ML) are tools that will be integrated ubiquitously into 6G networks and operations. As these tools require large numbers of data to be trained and will operate in monitoring and system management, there are concerns about how this could affect user identity privacy protections. The researchers who conducted a large study on the effects of ML on privacy in 6G technology present multiple points on how AI and ML could be used by an adversary to erode privacy protections within 6G networks, most notably through Inference of Private Information, Large-Scale Data Collection, and Stenographic Data Generation [59]. The authors mention a core aspect of AI and ML: that it can be a double-edged sword. Takeaways from this observation are that the inclusion of these systems will require the correct people along with strict guidelines in order to protect user privacy. On the other hand, work carried out in [60] brings a positive outlook to privacy protections in 6G networks, revealing how AI systems can be used to help conceal and anonymize user data. A major concern with AI in 6G networks is its possible ability to categorize users by gathering personal and non-personal information. Researchers in [61] bring together their findings in a study on the applicability of privacy solutions discovered against the found issues. Table 4 illustrates their discoveries and conclusions, which bring to light the most important privacy concerns in 6G networks. Table 4 shows the two major issues, similar to those discussed above for 5G technology, with understanding what a private system truly means: it is difficult to resolve defining levels and indicators for privacy and to determine the border between personal and non-personal data. Table 5 provides a select compilation of recent research publications related to 6G AI applications, with descriptions of each paper and their respective privacy focus areas.
Table 4. The privacy solutions and applicability addressing concerns in personal and non-personal data [61]. The privacy solution is labeled in the far-left column, and the abbreviated privacy issues are presented in the columns on the right.
Table 5. Comparison of the current literature regarding AI, user identity protections, and privacy in 6G technology.
  • P1—Privacy attacks on AI models and private data
  • P2—IoT (Internet of Things) edge network and edge AI privacy attacks
  • P3—Privacy limitations in cloud computing and storage environments
  • P4—Cost of privacy enhancements
  • P5—Privacy differences based on location
  • P6—Difficulty in defining levels and indicators for privacy
  • N1—Difficulty determining the border between personal and non-personal data
  • N2—Mixing personal data with non-personal data
  • N3—Utility vs. privacy of anonymized data
  • N4—Privacy attacks on anonymized and synthetic data
  • N5—Data Localization Laws vs. free flow of data.

4.3. Trustworthiness in 6G Networks

As discussed previously, trust in the serving cellular network is a major factor that must be considered by consumers and operators alike. Trustworthiness in 6G technology ranges across many different topics regarding AI, along with user privacy and identity ramifications. The work carried out in [70] shares how trustworthiness is a multidisciplinary topic covering technology, regulation, techno-economics, politics, and ethics. Pertaining to privacy, the authors state that blockchain technologies can aid in 6G technologies while offering immutability, transparency, verifiability, anonymity, and pseudonyms in data sharing mechanisms, authentication, and network access control. FL is also noted as a privacy-focused method for training larger 6G ML models. Ethical aspects are also presented as a vital focus for a user’s trust in the network as 6G technology plans to bring more cyber–physical systems into the cellular ecosystem [71]. The ethics of data privacy is noted as an ever more important topic around the world, as standards creators and vendors must consider how data are processed and protected to uphold the rights of users. The authors raise open questions regarding automated or AI systems and where liability will be placed during malfunctions that could directly affect customers. Figure 5 outlines the core aspects of network trustworthiness in 6G technology, and the need for further privacy and identity protections.
Figure 5. The core tenets of trustworthiness in a 6G network ecosystem.
Other aspects of 6G communications that add to the trustworthiness and performance of the network are discussed in [72]. The main topic included in this work is trustworthy Task-Oriented Semantic Communication (ToSC), which advocates for only sending pertinent information within the network. This technique potentially increases user identity protection and privacy and also increases the efficiency of the network if less information is being processed. In mMTC, this strategy could be incorporated to relieve stress on the interfaces between devices, freeing up resources while still maintaining privacy. Deep learning (DL) is discussed as the foundation of their approach to ToSC, extracting only the pertinent information in a query, and the inclusion of differential privacy to the communication contents. It is also mentioned that a balance between utility, efficiency, and privacy is important in 6G networks to maintain extremely high bandwidth and ultra-low latency. Sensors are another area where 6G network interfaces will be impacted by new types of data and strict performance requirements, especially within the context of self-driving vehicles, autonomous robotics, etc. The authors in [73] address how sensor data integration into 6G technology causes many more attack vectors, along with furthering privacy concerns. They bring forward the idea of adding a Sensing Policy, Consent, and Transparency Management (SPCTM) function. The SPCTM function would manage privacy policies, user consent, and transparency, ensuring compliance and awareness. An approach that adds a network function is usually an accepted method for additional functionality and extensibility, but it can also act as a double-edged sword by increasing the size of the attack surface. A survey on trust anchor technologies [74] addresses the importance of the terms and visions of trust as a resource in 6G systems alongside the usage of AI technologies and cooperation with third-party vendors. The concept of “trust anchors” as a foundational service in 6G networks has the following functional and architectural requirements, such as are brought forward to ensure a trustworthy network ecosystem:
  • Non-Repudiation;
  • Immutability;
  • Transparency;
  • Programmability;
  • Modularity;
  • Integration.
In the example of Core-to-Core communications in 6G networks, where multiple independent network providers require the establishment of a trusted platform, a third party needs to provide a trust anchor to all parties. In similar approaches where a network provider utilizes a third party for enhancements in a specific VNF, the network itself provides the trust foundation to all application providers and consumers. This creates a two-way agreement for unified trust management in 6G interfaces. The authors believe their work can be a starting point for creating Trusted Infrastructure architectures for trust anchors in 6G communications.

5. Conclusions

Fifth-Generation technology has enabled numerous new applications and advanced end user experiences. It also advanced use cases for consumers due to its new approaches in connectivity, scalability, and operability. Finally, 5G technology also provides the foundation upon which future generations of cellular networks will be built. With new opportunities, however, come new risks. User identity privacy in 5G and future 6G networks must be a core consideration for the operators of networks, standards organizations, and the research community. We have reviewed the most important aspects of user identity within 5G CNs, ranging from anonymous network technology, SBA, PII in 5G technology, and the impacts of newly adopted technology to privacy enhancement proposals and lawful interception, concluding in a roadmap for privacy in 6G networks. It was found that user identity and privacy are complex topics within 5G systems due to the newly adopted software-defined solutions that this technology deploys.
Privacy is also a topic that is not always well defined, which creates difficulties in creating models that can be standardized in complex systems. Furthermore, with its political implications and the wide variety of privacy laws around the world, it makes it more difficult for standards to be created that ensure that a user’s connections are private.
Trust in the system is inherently the most important factor for a user to consider while connecting to any 5G network, as the HN ultimately controls all of the encryption processes and thus the ability to gather data on users if protections are not in place. Truly anonymous communications within 5G applications could have real-world benefits for areas such as the healthcare sector, along with government and military operations.
Our final insights and key takeaways for further research in this realm are listed below:
  • There exists a strong need to reduce the prevalence and reliance on personal identifiers such as the SUPI (Subscription Permanent Identifier) within 5G/6G Core operations to help better protect user identity. This has the potential to be achieved by replacing the widespread usage of the SUPI between VNFs with decentralized ephemeral identifiers, thereby maintaining 3GPP standard operations, billing and fraud prevention capabilities, and customer service expectations. This would add a layer of identity abstraction for the user on the network to better protect the SUPI and other identifiers from eavesdroppers and unauthorized behavioral tracking and metadata collection.
  • Systems can also be designed to leverage the powerful nature of AI to bring enhanced services, experiences, and threat deterrence for users. User datasets must be de-identified to prevent privacy leaks. Continual training methods such as FL preserve user identity protections, as PII is not transmitted to central servers. Concerns may arise from metadata exposure, which may facilitate linkage attacks.
  • The creation of a standardized trust architecture between users, providers, and third-party vendors would provide visibility and transparency to 5G/6G operations with regard to the data shared or collected by different network elements. Furthermore, adherence to a strict privacy-by-design rationale for newly developed specifications would help to alleviate issues resulting from untrusted third-party vendors or cloud providers.
  • The incorporation of HSMs into 5G/6G infrastructure to enhance the physical-layer security of cryptographic secrets and to enable end-to-end encryption is a further recommendation for enhancing the privacy and data protection capabilities of these systems.
As efforts in 6G conceptualization and technology development continue, it is vital that user identity protections, such as limiting PII metadata within CNs, and privacy considerations are prioritized throughout these efforts in designing future mobile cellular protocols and architectures.

Author Contributions

Investigation, P.S., M.H., and H.S.; writing—original draft preparation, P.S. and M.H.; writing—review and editing, P.S., M.H., and H.S.; supervision, H.S. and M.H.; project administration, H.S. and M.H.; funding acquisition, H.S. and M.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially funded by the University of Nebraska–Lincoln’s Nebraska Center for Energy Sciences Research (NCESR) under Cycle 16 Grant# 20-706. It was also partially funded by the Advanced Telecommunications Engineering Lab (TEL) at the University of Nebraska–Lincoln under TEL’s 5G Student Innovation Grant program.

Data Availability Statement

This study did not report any data.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
5GFifth Generation
VNFVirtual Network Function
SBAService-Based Architecture
CNCore Network
NFNetwork Function
SAStandalone
SSNSocial Security Number
5G-GUTIGlobally Unique Temporary ID
NASNon-Access Stratum
RNTIRadio Network Temporary Identifier
MACMedium Access Control
HNHome Network
AKMAAuthentication and Key Management
TSNTime-Sensitive Network
AMFAccess and Mobility Function
RESTfulRepresentational State Transfer Application Programming Interfaces
PIIPersonally Identifiable Information
UEUser Equipment
SUPISubscription Permanent Identifier
QoSQuality of Service
PDUProtocol Data Unit
UDMUnified Data Management
UDRUnified Data Repository
IMSIInternational Mobile Subscriber Identity
LTELong-Term Evolution
SUCISubscriber Concealed Identity
PEIPersonal Equipment Identifier
IMEIInternational Mobile Equipment Identity
IMEISVInternational Mobile Equipment Identity Software Version
5G-GUAMIGlobally Unique AMF ID
FQDNFully Qualified Domain Name
DNNData Network Name
APNAccess Point Name
SMFSession Management Function
UPFUser Plane Function
GPSIGeneric Public Subscription Identifier
NGAPNext-Generation Application Protocol
RANRadio Access Network
SDNSoftware-Defined Networking
NISTNational Institute of Science and Technology
NSANon-Standalone
PEFMAPrivacy Enhanced Fast Mutual Authentication
5G-AKAAuthentication and Key Agreement
HMACHash-Based Message Authentication Code
LILawful Interception
URLLCUltra-Reliable Low-Latency Communications
eMBBEnhanced Mobile Broadband
mMTCMassive Machine Type Communications
mULCMassive Ultra-Reliable Low-Latency Communication
ULBCUltra-Reliable Low-Latency Broadband Communication
uMBBUbiquitous Mobile Broadband
KPIKey Performance Indicators
HSMHardware Security Module
FLFederated Learning
ZTAZero-Trust Architectures
AIArtificial Intelligence
MLMachine Learning
IoTInternet of Things
LLMLarge Language Model
XAIExplainable AI
ToSCTask-Oriented Semantic Communication
DLDeep Learning
SPCTMSensing Policy, Consent, and Transparency Management

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