Vertical federated learning security

Abstract

Systems, methods, and instrumentalities are disclosed herein for vertical federated learning (VLF) security. A first network entity may select a wireless device (e.g., wireless transmit / receive unit (WTRU)) for participation in VLF. The device may send a VLF security key to the wireless device. The first network entity may receive information associated with artificial intelligence (Al) training. The information may be encoded based on the VLF security key. The first network entity may perform an authentication check on the information based on the VLF security key. On a condition that the information is authenticated, the first network entity may determine a trained Al model based on the information. The first network entity may send the trained Al model to a second network entity.

Description

VERTICAL FEDERATED LEARNING SECURITYCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63,553,740, filed February 15, 2024, the contents of which is incorporated by reference hereinBACKGROUND

[0002] Mobile communications using wireless communication continue to evolve. A fifth generation may be referred to as 5G. A previous (legacy) generation of mobile communication may be, for example, fourth generation (4G) long term evolution (LTE).SUMMARY

[0003] Systems, methods, devices, and instrumentalities are described herein related to vertical federated learning security.

[0004] An example network entity may select a first vertical federated learning (VFL) device , wherein the first VFL device is associated with a first local identifier. The network entity may determine a second local identifier associated with the first VFL device at a second VFL device, and a third local identifier associated with the first VFL device at a third VFL device. The network entity may generate a global anonymized identifier that is associated with the first local identifier, the second local identifier, and the third local identifier. The network entity may assign the global anonymized identifier to the first VFL device to provide privacy protection for at least the first local identifier. The network entity may send the global anonymized identifier to the second VFL device and the third VFL device, wherein the global anonymized identifier is used in a VFL procedure.

[0005] The first VFL device may be a wireless transmit / receive unit (WTRU) or a network function. The VFL procedure may involve VFL training of an artificial intelligence model.

[0006] The network entity may select a wireless transmit / receive unit device for participation in vertical federated learning (VFL). The network entity may send a VFL security key to the first, second, and third VFL devices. The network entity may receive information associated with artificial intelligence (Al) training, wherein the information is encoded based on the VFL security key. The network entity may perform anauthentication check on the information based on the VFL security key. The network entity may on a condition that the information is authenticated, determine a trained Al model based on the information. The network entity may send results associated with the trained Al model to a second network entity.

[0007] The network entity may determine whether a digital signature in the information ins associated with the VFL security key.

[0008] The network entity may receive local training data from the first VFL device. The network entity may determine a feature based on the local training data and the global anonymized identifier. The network entity may use the feature and the local training data to train an artificial intelligence model.

[0009] The network entity may generate feedback associated with a global model based on an aggregation of a first model locally trained at the first VFL device, a second model locally trained at the second VFL device, and a third model locally trained at the third VFL device.

[0010] The second local identifier and the third local identifier may be associated with different protocol layers. The network entity may subscribe to training data from the first, second, and third VFL devices.

[0011] A first network entity may select a wireless device (e.g., a wireless transmit / receive unit (WTRU)) for participation in vertical federated learning (VLF). The first network entity may send a VLF security key to the wireless device. The first network entity may receive information associated with artificial intelligence (Al) training. The information may be encoded based on the VLF security key. The first network entity may perform an authentication check on the information based on the VLF security key. On a condition that the information is authenticated, the first network entity may determine a trained Al model based on the information. The first network entity may send the trained Al model to a second network entity.

[0012] The information associated with training the Al model may be training data collected by the wireless device, or a trained Al model.

[0013] The first network entity may perform the authentication check on the information based on the VLF security key by determining whether a digital signature in the information in associated with the VLF security key.

[0014] The first network entity may determine whether an identifier in the information is associated with the wireless device to verify that the information is from the wireless device.BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG. 1A is a system diagram illustrating an example communications system in which one or more disclosed embodiments may be implemented.

[0016] FIG. 1 B is a system diagram illustrating an example wireless transmit / receive unit (WTRU) that may be used within the communications system illustrated in FIG. 1A according to an embodiment.

[0017] FIG. 1 C is a system diagram illustrating an example radio access network (RAN) and an example core network (CN) that may be used within the communications system illustrated in FIG. 1 A according to an embodiment.

[0018] FIG. 1 D is a system diagram illustrating a further example RAN and a further example CN that may be used within the communications system illustrated in FIG. 1A according to an embodiment.

[0019] FIG. 2 illustrates an example model of a fifth generation (5G) network.

[0020] FIG. 3 illustrates an example of security key management, security protection, and WTRU identifier anonymization.DETAILED DESCRIPTION

[0021] FIG. 1A is a diagram illustrating an example communications system 100 in which one or more disclosed embodiments may be implemented. The communications system 100 may be a multiple access system that provides content, such as voice, data, video, messaging, broadcast, etc., to multiple wireless users. The communications system 100 may enable multiple wireless users to access such content through the sharing of system resources, including wireless bandwidth. For example, the communications systems 100 may employ one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), single-carrier FDMA (SC-FDMA), zero-tail unique-word DFT-Spread OFDM (ZT UW DTS-s OFDM), unique word OFDM (UW-OFDM), resource block-filtered OFDM, filter bank multicarrier (FBMC), and the like.

[0022] As shown in FIG. 1A, the communications system 100 may include wireless transmit / receive units (WTRUs) 102a, 102b, 102c, 102d, a RAN 104 / 113, a CN 106 / 115, a public switched telephone network (PSTN) 108, the Internet 110, and other networks 112, though it will be appreciated that the disclosed embodiments contemplate any number of WTRUs, base stations, networks, and / or network elements. Each of the WTRUs 102a, 102b, 102c, 102d may be any type of device configured to operate and / or communicate in a wireless environment. By way of example, the WTRUs 102a, 102b, 102c, 102d, any of which may be referred to as a “station” and / or a “STA”, may be configured to transmit and / or receive wireless signals and may include a user equipment (WTRU), a mobile station, a fixed or mobile subscriber unit, a subscription-based unit, a pager, a cellular telephone, a personal digital assistant (PDA), a smartphone, a laptop, a netbook, a personal computer, a wireless sensor, a hotspot or Mi-Fi device, an Internet of Things (loT) device, a watch or other wearable, a head-mounted display (HMD), a vehicle, a drone, a medical device and applications (e.g., remote surgery), an industrial device and applications (e.g., a robot and / or other wireless devices operating in an industrial and / or an automated processing chaincontexts), a consumer electronics device, a device operating on commercial and / or industrial wireless networks, and the like. Any of the WTRUs 102a, 102b, 102c and 102d may be interchangeably referred to as a WTRU.

[0023] The communications systems 100 may also include a base station 114a and / or a base station 114b. Each of the base stations 114a, 114b may be any type of device configured to wirelessly interface with at least one of the WTRUs 102a, 102b, 102c, 102d to facilitate access to one or more communication networks, such as the CN 106 / 115, the I nternet 110, and / or the other networks 112. By way of example, the base stations 114a, 114b may be a base transceiver station (BTS), a Node-B, an eNode B, a Home Node B, a Home eNode B, a gNB, a NR NodeB, a site controller, an access point (AP), a wireless router, and the like. While the base stations 114a, 114b are each depicted as a single element, it will be appreciated that the base stations 114a, 114b may include any number of interconnected base stations and / or network elements.

[0024] The base station 114a may be part of the RAN 104 / 113, which may also include other base stations and / or network elements (not shown), such as a base station controller (BSC), a radio network controller (RNC), relay nodes, etc. The base station 114a and / or the base station 114b may be configured to transmit and / or receive wireless signals on one or more carrier frequencies, which may be referred to as a cell (not shown). These frequencies may be in licensed spectrum, unlicensed spectrum, or a combination of licensed and unlicensed spectrum. A cell may provide coverage for a wireless service to a specific geographical area that may be relatively fixed or that may change over time. The cell may further be divided into cell sectors. For example, the cell associated with the base station 114a may be divided into three sectors. Thus, in one embodiment, the base station 114a may include three transceivers, i.e. , one for each sector of the cell. In an embodiment, the base station 114a may employ multiple-input multiple output (MIMO) technology and may utilize multiple transceivers for each sector of the cell. For example, beamforming may be used to transmit and / or receive signals in desired spatial directions.

[0025] The base stations 114a, 114b may communicate with one or more of the WTRUs 102a, 102b, 102c, 102d over an air interface 116, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, centimeter wave, micrometer wave, infrared (IR), ultraviolet (UV), visible light, etc.). The air interface 116 may be established using any suitable radio access technology (RAT).

[0026] More specifically, as noted above, the communications system 100 may be a multiple access system and may employ one or more channel access schemes, such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, and the like. For example, the base station 114a in the RAN 104 / 113 and the WTRUs 102a, 102b, 102c may implement a radio technology such as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access (UTRA), which may establish the air interface 115 / 116 / 117 usingwideband CDMA (WCDMA). WCDMA may include communication protocols such as High-Speed Packet Access (HSPA) and / or Evolved HSPA (HSPA+). HSPA may include High-Speed Downlink (DL) Packet Access (HSDPA) and / or High-Speed UL Packet Access (HSUPA).

[0027] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as Evolved UMTS Terrestrial Radio Access (E-UTRA), which may establish the air interface 116 using Long Term Evolution (LTE) and / or LTE-Advanced (LTE-A) and / or LTE-Advanced Pro (LTE-A Pro).

[0028] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as NR Radio Access , which may establish the air interface 116 using New Radio (NR).

[0029] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement multiple radio access technologies. For example, the base station 114a and the WTRUs 102a, 102b, 102c may implement LTE radio access and NR radio access together, for instance using dual connectivity (DC) principles. Thus, the air interface utilized by WTRUs 102a, 102b, 102c may be characterized by multiple types of radio access technologies and / or transmissions sent to / from multiple types of base stations (e.g., a eNB and a gNB).

[0030] In other embodiments, the base station 114a and the WTRUs 102a, 102b, 102c may implement radio technologies such as IEEE 802.11 (i.e., Wireless Fidelity (WiFi), IEEE 802.16 (i.e., Worldwide Interoperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 1X, CDMA2000 EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95 (IS-95), Interim Standard 856 (IS-856), Global System for Mobile communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), GSM EDGE (GERAN), and the like.

[0031] The base station 114b in FIG. 1 A may be a wireless router, Home Node B, Home eNode B, or access point, for example, and may utilize any suitable RAT for facilitating wireless connectivity in a localized area, such as a place of business, a home, a vehicle, a campus, an industrial facility, an air corridor (e.g., for use by drones), a roadway, and the like. In one embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.11 to establish a wireless local area network (WLAN). In an embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.15 to establish a wireless personal area network (WPAN). In yet another embodiment, the base station 114b and the WTRUs 102c, 102d may utilize a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR etc.) to establish a picocell or femtocell. As shown in FIG. 1A, the base station 114b may have a direct connection to the Internet 110. Thus, the base station 114b may not be required to access the Internet 110 via the CN 106 / 115.

[0032] The RAN 104 / 113 may be in communication with the CN 106 / 115, which may be any type of network configured to provide voice, data, applications, and / or voice over internet protocol (VoIP) services to one or more of the WTRUs 102a, 102b, 102c, 102d. The data may have varying quality of service (QoS) requirements, such as differing throughput requirements, latency requirements, error tolerance requirements, reliability requirements, data throughput requirements, mobility requirements, and the like. The CN 106 / 115 may provide call control, billing services, mobile location-based services, pre-paid calling, Internet connectivity, video distribution, etc., and / or perform high-level security functions, such as user authentication. Although not shown in FIG. 1A, it will be appreciated that the RAN 104 / 113 and / or the CN 106 / 115 may be in direct or indirect communication with other RANs that employ the same RAT as the RAN 104 / 113 or a different RAT. For example, in addition to being connected to the RAN 104 / 113, which may be utilizing a NR radio technology, the CN 106 / 115 may also be in communication with another RAN (not shown) employing a GSM, UMTS, CDMA 2000, WiMAX, E-UTRA, or WiFi radio technology.

[0033] The CN 106 / 115 may also serve as a gateway for the WTRUs 102a, 102b, 102c, 102d to access the PSTN 108, the Internet 110, and / or the other networks 112. The PSTN 108 may include circuit- switched telephone networks that provide plain old telephone service (POTS). The Internet 110 may include a global system of interconnected computer networks and devices that use common communication protocols, such as the transmission control protocol (TCP), user datagram protocol (UDP) and / or the internet protocol (IP) in the TCP / IP internet protocol suite. The networks 112 may include wired and / or wireless communications networks owned and / or operated by other service providers. For example, the networks 112 may include another CN connected to one or more RANs, which may employ the same RAT as the RAN 104 / 113 or a different RAT.

[0034] Some or all of the WTRUs 102a, 102b, 102c, 102d in the communications system 100 may include multi-mode capabilities (e.g., the WTRUs 102a, 102b, 102c, 102d may include multiple transceivers for communicating with different wireless networks over different wireless links). For example, the WTRU 102c shown in FIG. 1A may be configured to communicate with the base station 114a, which may employ a cellular-based radio technology, and with the base station 114b, which may employ an IEEE 802 radio technology.

[0035] FIG. 1 B is a system diagram illustrating an example WTRU 102. As shown in FIG. 1 B, the WTRU 102 may include a processor 118, a transceiver 120, a transmit / receive element 122, a speaker / microphone 124, a keypad 126, a display / touchpad 128, non-removable memory 130, removable memory 132, a power source 134, a global positioning system (GPS) chipset 136, and / or other peripherals 138, among others. It will be appreciated that the WTRU 102 may include any sub-combination of the foregoing elements while remaining consistent with an embodiment.

[0036] The processor 118 may be a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, any other type of integrated circuit (IC), a state machine, and the like. The processor 118 may perform signal coding, data processing, power control, input / output processing, and / or any other functionality that enables the WTRU 102 to operate in a wireless environment. The processor 118 may be coupled to the transceiver 120, which may be coupled to the transmit / receive element 122. While FIG. 1 B depicts the processor 118 and the transceiver 120 as separate components, it will be appreciated that the processor 118 and the transceiver 120 may be integrated together in an electronic package or chip.

[0037] The transmit / receive element 122 may be configured to transmit signals to, or receive signals from, a base station (e.g., the base station 114a) over the air interface 116. For example, in one embodiment, the transmit / receive element 122 may be an antenna configured to transmit and / or receive RF signals. In an embodiment, the transmit / receive element 122 may be an emitter / detector configured to transmit and / or receive IR, UV, or visible light signals, for example. In yet another embodiment, the transmit / receive element 122 may be configured to transmit and / or receive both RF and light signals. It will be appreciated that the transmit / receive element 122 may be configured to transmit and / or receive any combination of wireless signals.

[0038] Although the transmit / receive element 122 is depicted in FIG. 1 B as a single element, the WTRU 102 may include any number of transmit / receive elements 122. More specifically, the WTRU 102 may employ MIMO technology. Thus, in one embodiment, the WTRU 102 may include two or more transmit / receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals over the air interface 116.

[0039] The transceiver 120 may be configured to modulate the signals that are to be transmitted by the transmit / receive element 122 and to demodulate the signals that are received by the transmit / receive element 122. As noted above, the WTRU 102 may have multi-mode capabilities. Thus, the transceiver 120 may include multiple transceivers for enabling the WTRU 102 to communicate via multiple RATs, such as NR and IEEE 802.11, for example.

[0040] The processor 118 of the WTRU 102 may be coupled to, and may receive user input data from, the speaker / microphone 124, the keypad 126, and / or the display / touchpad 128 (e.g., a liquid crystal display (LCD) display unit or organic light-emitting diode (OLED) display unit). The processor 118 may also output user data to the speaker / microphone 124, the keypad 126, and / or the display / touchpad 128. In addition, the processor 118 may access information from, and store data in, any type of suitable memory, such asthe non-removable memory 130 and / or the removable memory 132. The non-removable memory 130 may include random-access memory (RAM), read-only memory (ROM), a hard disk, or any other type of memory storage device. The removable memory 132 may include a subscriber identity module (SIM) card, a memory stick, a secure digital (SD) memory card, and the like. In other embodiments, the processor 118 may access information from, and store data in, memory that is not physically located on the WTRU 102, such as on a server or a home computer (not shown).

[0041] The processor 118 may receive power from the power source 134, and may be configured to distribute and / or control the power to the other components in the WTRU 102. The power source 134 may be any suitable device for powering the WTRU 102. For example, the power source 134 may include one or more dry cell batteries (e.g., nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel metal hydride (NiMH), lithium-ion (Li-ion), etc.), solar cells, fuel cells, and the like.

[0042] The processor 118 may also be coupled to the GPS chipset 136, which may be configured to provide location information (e.g., longitude and latitude) regarding the current location of the WTRU 102. In addition to, or in lieu of, the information from the GPS chipset 136, the WTRU 102 may receive location information over the air interface 116 from a base station (e.g., base stations 114a, 114b) and / or determine its location based on the timing of the signals being received from two or more nearby base stations. It will be appreciated that the WTRU 102 may acquire location information by way of any suitable locationdetermination method while remaining consistent with an embodiment.

[0043] The processor 118 may further be coupled to other peripherals 138, which may include one or more software and / or hardware modules that provide additional features, functionality and / or wired or wireless connectivity. For example, the peripherals 138 may include an accelerometer, an e-compass, a satellite transceiver, a digital camera (for photographs and / or video), a universal serial bus (USB) port, a vibration device, a television transceiver, a hands free headset, a Bluetooth® module, a frequency modulated (FM) radio unit, a digital music player, a media player, a video game player module, an Internet browser, a Virtual Reality and / or Augmented Reality (VR / AR) device, an activity tracker, and the like. The peripherals 138 may include one or more sensors, the sensors may be one or more of a gyroscope, an accelerometer, a hall effect sensor, a magnetometer, an orientation sensor, a proximity sensor, a temperature sensor, a time sensor; a geolocation sensor; an altimeter, a light sensor, a touch sensor, a magnetometer, a barometer, a gesture sensor, a biometric sensor, and / or a humidity sensor.

[0044] The WTRU 102 may include a full duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for both the UL (e.g., for transmission) and downlink (e.g., for reception) may be concurrent and / or simultaneous. The full duplex radio may include an interference management unit to reduce and or substantially eliminate self-interference via either hardware(e.g., a choke) or signal processing via a processor (e.g., a separate processor (not shown) or via processor 118). In an embodiment, the WRTU 102 may include a half-duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for either the UL (e.g., for transmission) or the downlink (e.g., for reception)).

[0045] FIG. 1 C is a system diagram illustrating the RAN 104 and the CN 106 according to an embodiment. As noted above, the RAN 104 may employ an E-UTRA radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 104 may also be in communication with the CN 106.

[0046] The RAN 104 may include eNode-Bs 160a, 160b, 160c, though it will be appreciated that the RAN 104 may include any number of eNode-Bs while remaining consistent with an embodiment. The eNode-Bs 160a, 160b, 160c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In one embodiment, the eNode-Bs 160a, 160b, 160c may implement MIMO technology. Thus, the eNode-B 160a, for example, may use multiple antennas to transmit wireless signals to, and / or receive wireless signals from, the WTRU 102a.

[0047] Each of the eNode-Bs 160a, 160b, 160c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the UL and / or DL, and the like. As shown in FIG. 1 C, the eNode-Bs 160a, 160b, 160c may communicate with one another over an X2 interface.

[0048] The CN 106 shown in FIG. 1 C may include a mobility management entity (MME) 162, a serving gateway (SGW) 164, and a packet data network (PDN) gateway (or PGW) 166. While each of the foregoing elements are depicted as part of the CN 106, it will be appreciated that any of these elements may be owned and / or operated by an entity other than the CN operator.

[0049] The MME 162 may be connected to each of the eNode-Bs 162a, 162b, 162c in the RAN 104 via an S1 interface and may serve as a control node. For example, the MME 162 may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, bearer activation / deactivation, selecting a particular serving gateway during an initial attach of the WTRUs 102a, 102b, 102c, and the like. The MME 162 may provide a control plane function for switching between the RAN 104 and other RANs (not shown) that employ other radio technologies, such as GSM and / or WCDMA.

[0050] The SGW 164 may be connected to each of the eNode Bs 160a, 160b, 160c in the RAN 104 via the S1 interface. The SGW 164 may generally route and forward user data packets to / from the WTRUs 102a, 102b, 102c. The SGW 164 may perform other functions, such as anchoring user planes during inter- eNode B handovers, triggering paging when DL data is available for the WTRUs 102a, 102b, 102c, managing and storing contexts of the WTRUs 102a, 102b, 102c, and the like.

[0051] The SGW 164 may be connected to the PGW 166, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices.

[0052] The CN 106 may facilitate communications with other networks. For example, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to circuit-switched networks, such as the PSTN 108, to facilitate communications between the WTRUs 102a, 102b, 102c and traditional land-line communications devices. For example, the CN 106 may include, or may communicate with, an IP gateway (e.g., an IP multimedia subsystem (IMS) server) that serves as an interface between the CN 106 and the PSTN 108. In addition, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to the other networks 112, which may include other wired and / or wireless networks that are owned and / or operated by other service providers.

[0053] Although the WTRU is described in FIGS. 1 A-1 D as a wireless terminal, it is contemplated that in certain representative embodiments that such a terminal may use (e.g., temporarily or permanently) wired communication interfaces with the communication network.

[0054] In representative embodiments, the other network 112 may be a WLAN.

[0055] A WLAN in Infrastructure Basic Service Set (BSS) mode may have an Access Point (AP) for the BSS and one or more stations (STAs) associated with the AP. The AP may have an access or an interface to a Distribution System (DS) or another type of wired / wireless network that carries traffic in to and / or out of the BSS. Traffic to STAs that originates from outside the BSS may arrive through the AP and may be delivered to the STAs. Traffic originating from STAs to destinations outside the BSS may be sent to the AP to be delivered to respective destinations. Traffic between STAs within the BSS may be sent through the AP, for example, where the source STA may send traffic to the AP and the AP may deliver the traffic to the destination STA. The traffic between STAs within a BSS may be considered and / or referred to as peer-to- peer traffic. The peer-to-peer traffic may be sent between (e.g., directly between) the source and destination STAs with a direct link setup (DLS). In certain representative embodiments, the DLS may use an 802.11e DLS or an 802.11 z tunneled DLS (TDLS). A WLAN using an Independent BSS (I BSS) mode may not have an AP, and the STAs (e.g., all of the STAs) within or using the IBSS may communicate directly with each other. The IBSS mode of communication may sometimes be referred to herein as an “ad- hoc” mode of communication.

[0056] When using the 802.11 ac infrastructure mode of operation or a similar mode of operations, the AP may transmit a beacon on a fixed channel, such as a primary channel. The primary channel may be a fixed width (e.g., 20 MHz wide bandwidth) or a dynamically set width via signaling. The primary channel may be the operating channel of the BSS and may be used by the STAs to establish a connection with theAP. In certain representative embodiments, Carrier Sense Multiple Access with Collision Avoidance (CSMA / CA) may be implemented, for example in in 802.11 systems. For CSMA / CA, the STAs (e.g., every STA), including the AP, may sense the primary channel. If the primary channel is sensed / detected and / or determined to be busy by a particular STA, the particular STA may back off. One STA (e.g., only one station) may transmit at any given time in a given BSS.

[0057] High Throughput (HT) STAs may use a 40 MHz wide channel for communication, for example, via a combination of the primary 20 MHz channel with an adjacent or nonadjacent 20 MHz channel to form a 40 MHz wide channel.

[0058] Very High Throughput (VHT) STAs may support 20MHz, 40 MHz, 80 MHz, and / or 160 MHz wide channels. The 40 MHz, and / or 80 MHz, channels may be formed by combining contiguous 20 MHz channels. A 160 MHz channel may be formed by combining 8 contiguous 20 MHz channels, or by combining two non-contiguous 80 MHz channels, which may be referred to as an 80+80 configuration. For the 80+80 configuration, the data, after channel encoding, may be passed through a segment parser that may divide the data into two streams. Inverse Fast Fourier Transform (IFFT) processing, and time domain processing, may be done on each stream separately. The streams may be mapped on to the two 80 MHz channels, and the data may be transmitted by a transmitting STA. At the receiver of the receiving STA, the above described operation for the 80+80 configuration may be reversed, and the combined data may be sent to the Medium Access Control (MAC).

[0059] Sub 1 GHz modes of operation are supported by 802.11af and 802.11 ah. The channel operating bandwidths, and carriers, are reduced in 802.11 af and 802.11 ah relative to those used in 802.11 n, and 802.11 ac. 802.11 af supports 5 MHz, 10 MHz and 20 MHz bandwidths in the TV White Space (TVWS) spectrum, and 802.11 ah supports 1 MHz, 2 MHz, 4 MHz, 8 MHz, and 16 MHz bandwidths using non- TVWS spectrum. According to a representative embodiment, 802.11 ah may support Meter Type Control / Machine-Type Communications, such as MTC devices in a macro coverage area. MTC devices may have certain capabilities, for example, limited capabilities including support for (e.g., only support for) certain and / or limited bandwidths. The MTC devices may include a battery with a battery life above a threshold (e.g., to maintain a very long battery life).

[0060] WLAN systems, which may support multiple channels, and channel bandwidths, such as 802.11 n, 802.11 ac, 802.11 af, and 802.11 ah, include a channel which may be designated as the primary channel. The primary channel may have a bandwidth equal to the largest common operating bandwidth supported by all STAs in the BSS. The bandwidth of the primary channel may be set and / or limited by a STA, from among all STAs in operating in a BSS, which supports the smallest bandwidth operating mode. In the example of 802.11 ah, the primary channel may be 1 MHz wide for STAs (e.g., MTC type devices)that support (e.g., only support) a 1 MHz mode, even if the AP, and other STAs in the BSS support 2 MHz, 4 MHz, 8 MHz, 16 MHz, and / or other channel bandwidth operating modes. Carrier sensing and / or Network Allocation Vector (NAV) settings may depend on the status of the primary channel. If the primary channel is busy, for example, due to a STA (which supports only a 1 MHz operating mode), transmitting to the AP, the entire available frequency bands may be considered busy even though a majority of the frequency bands remains idle and may be available.

[0061] In the United States, the available frequency bands, which may be used by 802.11 ah, are from 902 MHz to 928 MHz. In Korea, the available frequency bands are from 917.5 MHz to 923.5 MHz. In Japan, the available frequency bands are from 916.5 MHz to 927.5 MHz. The total bandwidth available for 802.11 ah is 6 MHz to 26 MHz depending on the country code.

[0062] FIG. 1 D is a system diagram illustrating the RAN 113 and the CN 115 according to an embodiment. As noted above, the RAN 113 may employ an NR radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 113 may also be in communication with the CN 115.

[0063] The RAN 113 may include gNBs 180a, 180b, 180c, though it will be appreciated that the RAN 113 may include any number of gNBs while remaining consistent with an embodiment. The gNBs 180a, 180b, 180c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In one embodiment, the gNBs 180a, 180b, 180c may implement MIMO technology. For example, gNBs 180a, 108b may utilize beamforming to transmit signals to and / or receive signals from the gNBs 180a, 180b, 180c. Thus, the gNB 180a, for example, may use multiple antennas to transmit wireless signals to, and / or receive wireless signals from, the WTRU 102a. In an embodiment, the gNBs 180a, 180b, 180c may implement carrier aggregation technology. For example, the gNB 180a may transmit multiple component carriers to the WTRU 102a (not shown). A subset of these component carriers may be on unlicensed spectrum while the remaining component carriers may be on licensed spectrum. In an embodiment, the gNBs 180a, 180b, 180c may implement Coordinated Multi-Point (CoMP) technology. For example, WTRU 102a may receive coordinated transmissions from gNB 180a and gNB 180b (and / or gNB 180c).

[0064] The WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using transmissions associated with a scalable numerology. For example, the OFDM symbol spacing and / or OFDM subcarrier spacing may vary for different transmissions, different cells, and / or different portions of the wireless transmission spectrum. The WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using subframe or transmission time intervals (TTIs) of various or scalable lengths (e.g., containing varying number of OFDM symbols and / or lasting varying lengths of absolute time).

[0065] The gNBs 180a, 180b, 180c may be configured to communicate with the WTRUs 102a, 102b, 102c in a standalone configuration and / or a non-standalone configuration. In the standalone configuration, WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c without also accessing other RANs (e.g., such as eNode-Bs 160a, 160b, 160c). In the standalone configuration, WTRUs 102a, 102b, 102c may utilize one or more of gNBs 180a, 180b, 180c as a mobility anchor point. In the standalone configuration, WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using signals in an unlicensed band. In a non-standalone configuration WTRUs 102a, 102b, 102c may communicate with / connect to gNBs 180a, 180b, 180c while also communicating with / connecting to another RAN such as eNode-Bs 160a, 160b, 160c. For example, WTRUs 102a, 102b, 102c may implement DC principles to communicate with one or more gNBs 180a, 180b, 180c and one or more eNode-Bs 160a, 160b, 160c substantially simultaneously. In the non-standalone configuration, eNode-Bs 160a, 160b, 160c may serve as a mobility anchor for WTRUs 102a, 102b, 102c and gNBs 180a, 180b, 180c may provide additional coverage and / or throughput for servicing WTRUs 102a, 102b, 102c.

[0066] Each of the gNBs 180a, 180b, 180c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the UL and / or DL, support of network slicing, dual connectivity, interworking between NR and E- UTRA, routing of user plane data towards User Plane Function (UPF) 184a, 184b, routing of control plane information towards Access and Mobility Management Function (AMF) 182a, 182b and the like. As shown in FIG. 1 D, the gNBs 180a, 180b, 180c may communicate with one another over an Xn interface.

[0067] The CN 115 shown in FIG. 1 D may include at least one AMF 182a, 182b, at least one UPF 184a, 184b, at least one Session Management Function (SMF) 183a, 183b, and possibly a Data Network (DN) 185a, 185b. While each of the foregoing elements are depicted as part of the CN 115, it will be appreciated that any of these elements may be owned and / or operated by an entity other than the CN operator.

[0068] The AMF 182a, 182b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N2 interface and may serve as a control node. For example, the AMF 182a, 182b may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, support for network slicing (e.g., handling of different PDU sessions with different requirements), selecting a particular SMF 183a, 183b, management of the registration area, termination of NAS signaling, mobility management, and the like. Network slicing may be used by the AMF 182a, 182b in order to customize CN support for WTRUs 102a, 102b, 102c based on the types of services being utilized WTRUs 102a, 102b, 102c. For example, different network slices may be established for different use cases such as services relying on ultra-reliable low latency (URLLC) access, services relying on enhanced massive mobile broadband (eMBB) access,services for machine type communication (MTC) access, and / or the like. The AMF 162 may provide a control plane function for switching between the RAN 113 and other RANs (not shown) that employ other radio technologies, such as LTE, LTE-A, LTE-A Pro, and / or non-3GPP access technologies such as WiFi.

[0069] The SMF 183a, 183b may be connected to an AMF 182a, 182b in the CN 115 via an N11 interface. The SMF 183a, 183b may also be connected to a UPF 184a, 184b in the CN 115 via an N4 interface. The SMF 183a, 183b may select and control the UPF 184a, 184b and configure the routing of traffic through the UPF 184a, 184b. The SMF 183a, 183b may perform other functions, such as managing and allocating WTRU IP address, managing PDU sessions, controlling policy enforcement and QoS, providing downlink data notifications, and the like. A PDU session type may be IP-based, non-IP based, Ethernet-based, and the like.

[0070] The UPF 184a, 184b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N3 interface, which may provide the WTRUs 102a, 102b, 102c with access to packet- switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices. The UPF 184, 184b may perform other functions, such as routing and forwarding packets, enforcing user plane policies, supporting multi-homed PDU sessions, handling user plane QoS, buffering downlink packets, providing mobility anchoring, and the like.

[0071] The CN 115 may facilitate communications with other networks. For example, the CN 115 may include, or may communicate with, an IP gateway (e.g., an IP multimedia subsystem (IMS) server) that serves as an interface between the CN 115 and the PSTN 108. In addition, the CN 115 may provide the WTRUs 102a, 102b, 102c with access to the other networks 112, which may include other wired and / or wireless networks that are owned and / or operated by other service providers. In one embodiment, the WTRUs 102a, 102b, 102c may be connected to a local Data Network (DN) 185a, 185b through the UPF 184a, 184b via the N3 interface to the UPF 184a, 184b and an N6 interface between the UPF 184a, 184b and the DN 185a, 185b.

[0072] In view of Figures 1 A-1 D, and the corresponding description of Figures 1 A-1 D, one or more, or all, of the functions described herein with regard to one or more of: WTRU 102a-d, Base Station 114a-b, eNode-B 160a-c, MME 162, SGW 164, PGW 166, gNB 180a-c, AMF 182a-b, UPF 184a-b, SMF 183a-b, DN 185a-b, and / or any other device(s) described herein, may be performed by one or more emulation devices (not shown). The emulation devices may be one or more devices configured to emulate one or more, or all, of the functions described herein. For example, the emulation devices may be used to test other devices and / or to simulate network and / or WTRU functions.

[0073] The emulation devices may be designed to implement one or more tests of other devices in a lab environment and / or in an operator network environment. For example, the one or more emulation devicesmay perform the one or more, or all, functions while being fully or partially implemented and / or deployed as part of a wired and / or wireless communication network in order to test other devices within the communication network. The one or more emulation devices may perform the one or more, or all, functions while being temporarily implemented / deployed as part of a wired and / or wireless communication network. The emulation device may be directly coupled to another device for purposes of testing and / or may performing testing using over-the-air wireless communications.

[0074] The one or more emulation devices may perform the one or more, including all, functions while not being implemented / deployed as part of a wired and / or wireless communication network. For example, the emulation devices may be utilized in a testing scenario in a testing laboratory and / or a non-deployed (e.g., testing) wired and / or wireless communication network in order to implement testing of one or more components. The one or more emulation devices may be test equipment. Direct RF coupling and / or wireless communications via RF circuitry (e.g., which may include one or more antennas) may be used by the emulation devices to transmit and / or receive data.

[0075] Feature(s) associated with vertical federate learning (VFL) security are provided herein.

[0076] FIG. 2 illustrates an example reference model of a fifth generation (5G) network (e.g., a reference model of a 5G / next generation (NextGen) network). FIG. 2 illustrates a reference model of a potential architecture of a 5G or NextGen network.

[0077] As used herein, the term radio access network (RAN) may refer to a radio access network, such as those described with respect to FIGs. 1 A-D. For example, RAN may refer to a radio access network based on 5G radio access technology (RAT) or evolved universal terrestrial radio access (E-UTRA) that connects to the NextGen core network.

[0078] Example network functions (NFs) are described herein. The access control and mobility management function (AMF) may include one or more of the following functionalities: registration management, connection management, reachability management, mobility management, etc.

[0079] The session management function (SMF) may include one or more of the following functionalities: session management (e.g., including session establishment, modify, and release), WTRU internet protocol (IP) address allocation, selection and control of user plane (UP) function, etc.

[0080] The user plane function (UPF) may include one or more of the following functionalities: packet routing and forwarding, packet inspection, traffic usage reporting, etc.

[0081] Feature(s) associated with network analytic service are provided herein.

[0082] The network data analytics function (NWDAF) (e.g., network data analytics feature) may provide statistics and / or predictions based on requests (e.g., specific requests) from the entities consuming thisinformation. For example, the network data analytics feature may provide (e.g., be capable of providing) information such as statistics and predictions on gNB status information, gNB resource usage, communication and mobility performance in an area of interest, and / or the like. The target of such analytics may be a (e.g., single) WTRU, a group of WTRUs, or any WTRU(s) in an area of interest. Network data analytics may be provided to characterize network function load, and / or network slice load. Network data analytics may provide predictions and / or statistics regarding WTRU mobility, expected WTRU behavior, and / or observed service experience at one or more (e.g., multiple) levels (e.g., including network slice, service experience for a particular application, service experience for a particular application over a particular access type (RAT type or frequency), and / or the like).

[0083] Feature(s) associated with horizontal federated learning are provided herein.

[0084] Federated learning among NWDAFs (e.g., multiple NWDAFs) may be used (e.g., may be specified, for example, by the third generation partnership project (3GPP)). For example, a specification may indicate how the NWDAF (e.g., including a model training function) may leverage federated learning technique(s) to train a machine learning (ML) model.

[0085] For horizontal federated learning, a (e.g., every) NWDAF function enabled for federated learning may register with a network repository function (NRF). For example, the NWDAF may register using the NWDAF’s NF profile, information for supported analytic service(s) (e.g., analytics identifier(s)), address information of the NWDAF, service area, the NWDAF’s capability for federated learning, and / or the like. This registered information may be utilized to find proper NWDAF function(s) to join federated learning for analytics service(s) with candidate ML models and a requested service area.

[0086] Model filter information may indicate (e.g., may be defined to indicate) the condition(s) under which an ML model is requested for analytics service and / or a target of the ML model (e.g., specific WTRU(s), a group of WTRU, etc.).

[0087] For horizontal federated learning, a federated learning (FL) server NWDAF and FL client NWDAF may be defined. If an analytic service is requested, federated learning may be requested to an FL server NWDAF (e.g., with ML model accuracy). The FL server NWDAF may discover and select a (e.g., proper) FL client NWDAF for the (e.g., specific) analytics service(s) with the requested ML model at a service area. The server NWDAF may determine NF type(s) as data source(s) from which the NWDAF collects data for local model training and / or a time period (e.g., an interested time period). The FL server NWDAF may provide the local ML model to the FL client NWDAF. The FL server NWDAF may request that the FL client NWDAF perform the local model training. A (e.g., each) FL client NWDAF may collect its local data. The FL client NWDAF(s) may perform local model training with the (e.g., its own) data. The FL client NWDAF(s) may report the interim local ML model information to the FL server NWDAF. The FL server NWDAF mayupdate a global ML model based on the aggregated local ML models. The FL server NWDAF may provide the (e.g., proper) global ML model for the requested analytics service.

[0088] Vertical federate learning (VFL) may refer to a distributed machine learning technique that trains machine learning models among independent training entities. An entity (e.g., each entity) may have a different subset of training data (e.g., each training entity using its own data set). The global VFL model may be aggregated in a VFL application function (AF) or in an NWDAF (e.g., in the 5G core). One or more (e.g., other) client NWDAF(s) may train the local model using training data from VFL participating NFs / WTRUs (e.g., before delivering the information to the server NWDAF that aggregates local models into the final global model).

[0089] Security key management (e.g., including key derivation, key distribution, key lifetime management, etc.) may be used for VFL participating NFs and WTRUs to protect the training data from selected NFs / WTRUs. The VFL training NF (e.g., NWDAF) may authenticate / authorize WTRUs / NFs. The VFL training NF may authenticate training data and / or perform data encryption / decryption and data integrity protection (e.g., received from the VFL participating NFs / WTRUs). For privacy protection purposes, a WTRU identifier (e.g., the real WTRU identifier) may not be used directly in the VFL training model. For WTRU privacy protection, such user identifier, location, etc. may be protected.

[0090] VFL training data from different NFs and / or across different protocol layer may use different identifiers associated with the same sample (e.g., the same WTRU, the same Network Sliced Assistance Information Instance, etc.). In this case, the training data may be (e.g., may need to be) mapped to the same feature before data pre-processing and using the data for training associated with the same sample (e.g., the same WTRU). An example network function support for the management of feature mapping from different samples (e.g., from different WTRU identifiers across different NFs and different protocol layers) is provided herein.

[0091] Feature(s) described herein may facilitate (e.g., provide) vertical federate learning between an AF and the 5G core (5GC).

[0092] WTRU VFL training data may be protected between (e.g., during transport between) the WTRU and the NWDAF. For example, the training data may be protected using security keys for authentication, authorization, and / or integrity protection of the data.

[0093] The training vectors from different WTRUs / NFs / AFs and / or across different layers with different identifiers may be associated (e.g., aggregated or mapped) to the same feature used for the VFL training.

[0094] The WTRU’s privacy information may be protected.

[0095] Feature(s) associated with VFL security protection are provided herein.

[0096] Feature(s) associated with security key management (e.g., such as key derivation for confidentiality and integrity protection of VFL training data and model) are provided herein. The key may be used to authenticate the VFL participant(s) that are selected and authorized to be engaged in the VFL training.

[0097] Feature(s) associated with WTRU privacy protection (e.g., via an anonymized WTRU identifier as the VFL feature) are provided herein.

[0098] Feature(s) associated with WTRU identifier mapping (e.g., between different NFs and across different protocol layers) are provided herein.

[0099] A core (e.g., 5GC) may provide a list of NFs to be used for (e.g., involved in) ML model training. The VFL AF may collaborate with the core (e.g., 5GC) to select NFs and WTRUs. The VFL AF may collaborate with the core (e.g., 5GC) to configure the selected NFs and WTRUs for the VFL model training (e.g., via a network exposure function (NEF)). The AF and / or the NWDAF may communicate with the NFs directly (or via the NEF) to share the ML model for local training, receive training data and / or the trained ML model, provide feedback, update the ML model, and / or the like.

[0100] The VFL AF may select the VFL participating NFs / WTRUs. The NWDAF in a core (e.g., 5GC) and the VFL management function (VFLM) may derive security keys for the (e.g., each of the) VFL participants and deliver the security keys to the entities (e.g., to each entity). The security keys may be used to protect the communication between the VFL clients and the VFL AF or NWDAF (e.g., including encryption, decryption, integrity protection, etc.). The security keys may be derived using the information associated with the VFL training session (e.g., the mode identifier, NF / WTRU identifier, VFL client identifier, the timestamp and / or a random number, AF identifier, etc.). The security keys may be used to protect the communication from the VFL server to the VFL clients (e.g., to send the training parameters, initial VFL model to the VFL clients).

[0101] For privacy protection purposes, the WTRU identifier (e.g., in the data for VFL model training) may be anonymized. The WTRU identifier mapping may be managed in the identifier management system. For VFL training, one or more (e.g., all) features in participating NFs may (e.g., may need to) map the WTRU identifier in different protocol layers (e.g., physical layer, medium access control (MAC) layer, application layer, etc.) to the same anonymized WTRU identifier. Other privacy information (e.g., WTRU location, etc.) may be privacy-protected in a similar manner.

[0102] During vertical federated learning, the result of local ML training or training data in the core (e.g., 5GC) may be sent to the NWDAF and / or the AF. The NWDAF and / or the AF may update the local ML model. If the VFL participating NFs / WTRUs collect the training data, the NFs / WTRUs may train the local model, or pre-process the training data. The trained local model or training data may be encrypted andintegrity protected by the NFs / WTRUs (e.g., before sending to the AF / NWDAF for global training or aggregation. If the AF / NWDAF receives the local training data / model from the VFL participating NFs / WTRUs, the AF / NWDAF may (e.g., first) verify the integrity of the received data (e.g., to be sure the data was not modified in the transmission and the received data is from the claimed sender). The AF / NWDAF may decrypt the data using keys shared between the NFs / WTRUs and the AF / NWDAF. If the WTRU identifier associated with the training data / local model is not the identifier used for the model training, the identifier management system (IDM) may be consulted to map the WTRU identifier to the WTRU identifier for the training or local model aggregation. The mapped WTRU identifier may be further anonymized for privacy protection purpose before the VFL training or local model aggregation.

[0103] Feature(s) associated with vertical federated learning security are provided herein.

[0104] FIG. 3 illustrates an example of VFL security key management, security protection, and WTRU identifier anonymization.

[0105] At 1 , VFL participating NFs / WTRUs may be selected and configured. The VFL AF may select the VFL participating NFs / WTRUs (e.g., based on requirements, capabilities, availabilities, location, etc.). The NWDAF in 5GC (e.g., via the NEF) and the VFLM may derive security keys for the (e.g., each of the) VFL participants. The VFLM may deliver the security keys to the (e.g., each of the) entities and the NWDAF. The security keys may be used to protect the communication between the VFL clients (e.g., VFL participating NFs / WTRUs and NWDAF) and VFL server (e.g., including encryption, integrity protection). The security keys may be derived using the information associated with the VFL training session (e.g., the model identifier, VFL client identifier, NF / WTRU identifier, the timestamp and / or a random number, AF identifier, etc.).

[0106] For privacy protection purposes, the user privacy information (e.g., the WTRU identifier) may be anonymized. The identifier mapping table may be stored in the IDM. The identifier mapping table may maintain the mapping relation of local WTRU identifiers in samples from different collected training data into a global anonymized WTRU identifier.

[0107] For VFL training, features (e.g., all features) in participating NFs may (e.g., may need to) map the WTRU identifier in different protocol layers (e.g., physical layer, MAC layer, IP layer, transport layer, application layer, etc.) to the same anonymized WTRU identifier. Other privacy information (e.g., WTRU location, etc.) may be privacy-protected in a similar manner. A two-stage mapping may occur at the participating NFs. For example, the protocol identifier may be (e.g., may be first) mapped to a WTRU identifier (e.g., a common WTRU identifier) in the core (e.g., 5GC). The common WTRU identifier may be (e.g., may then be) mapped to the anonymized identifier used for the VFL training.

[0108] After the VFL participant selection, the VFLM my inform the NWDAF of the involved VFL clients.

[0109] The server NWDAF my share model information, feature information, and a list of VFL clients with the VFLM and the VFL AF. The NWDAF (e.g., 5GC NWDAF) may inform the (e.g., each of the) selected VFL clients of the features and configuration information (e.g., before the start of VFL training).

[0110] At 2, the VFL AF may request that the NWDAF At 3, the VFL training data may be subscribed by the VFL client NWDAF or pushed to the VFL client NWDAF. If the VFL participating NFs / WTRUs collect the training data or finish the local training, the training data or the trained model is encrypted and integrity protected by the NFs / WTRUs using the keys received at 1 . The NFs / WTRUs may send the encrypted training data or model to the NWDAF for VFL training or aggregation.

[0111] At 4, if the NWDAF receives the local training data from the VFL participating NFs / WTRUs, the NWDAF may (e.g., may first) verify the integrity of the received data (e.g., to be sure the data was not modified in the transmission and the received data is from the claimed sender). The NWDAF may decrypt the data using keys shared between the NFs / WTRUs and the NWDAF. The data may be sent to the VFLM / IDM.

[0112] The encryption / decryption may be performed in the VFL / IDM.

[0113] At 5, the VFLM / IDM may perform the data authorization check. For the data from the WTRU, authentication may be performed to make sure the data is from the claimed WTRU. The feature associated with the WTRU identifier in training data may be mapped (e.g., by the I DM system) to the anonymized identifier that will be used for the training or local model aggregation.

[0114] At 6, the feature corresponding to the anonymized WTRU identifier and the decrypted data may be sent back to the NWDAF.

[0115] At 7, the NWDAF may train the local model using the data and feature received from the VFLM / IDM.

[0116] At 8, the trained local model may be sent to the VFL server NWDAF or VFL AF (e.g., depending on which entity is performing the global model aggregation).

[0117] Although features and elements described above are described in particular combinations, each feature or element may be used alone without the other features and elements of the preferred embodiments, or in various combinations with or without other features and elements.

[0118] Although the implementations described herein may consider 3GPP specific protocols, it is understood that the implementations described herein are not restricted to this scenario and may be applicable to other wireless systems. For example, although the solutions described herein consider LTE, LTE-A, New Radio (NR) or 5G specific protocols, it is understood that the solutions described herein are not restricted to this scenario and are applicable to other wireless systems as well. For example, while thesystem has been described with reference to a 3GPP, 5G, and / or NR network layer, the envisioned embodiments extend beyond implementations using a particular network layer technology. Likewise, the potential implementations extend to all types of service layer architectures, systems, and embodiments. The techniques described herein may be applied independently and / or used in combination with other resource configuration techniques.

[0119] The processes described herein may be implemented in a computer program, software, and / or firmware incorporated in a computer-readable medium for execution by a computer and / or processor. Examples of computer-readable media include, but are not limited to, electronic signals (transmitted over wired and / or wireless connections) and / or computer-readable storage media. Examples of computer- readable storage media include, but are not limited to, a read only memory (ROM), a random access memory (RAM), a register, cache memory, semiconductor memory devices, magnetic media such as, but not limited to, internal hard disks and removable disks, magneto-optical media, and / or optical media such as compact disc (CD)-ROM disks, and / or digital versatile disks (DVDs). A processor in association with software may be used to implement a radio frequency transceiver for use in a WTRU, terminal, base station, RNC, and / or any host computer.

[0120] It is understood that the entities performing the processes described herein may be logical entities that may be implemented in the form of software (e.g., computer-executable instructions) stored in a memory of, and executing on a processor of, a mobile device, network node or computer system. That is, the processes may be implemented in the form of software (e.g., computer-executable instructions) stored in a memory of a mobile device and / or network node, such as the node or computer system, which computer executable instructions, when executed by a processor of the node, perform the processes discussed. It is also understood that any transmitting and receiving processes illustrated in figures may be performed by communication circuitry of the node under control of the processor of the node and the computer-executable instructions (e.g., software) that it executes.

[0121] The various techniques described herein may be implemented in connection with hardware or software or, where appropriate, with a combination of both. Thus, the implementations and apparatus of the subject matter described herein, or certain aspects or portions thereof, may take the form of program code (e.g., instructions) embodied in tangible media including any other machine-readable storage medium wherein, when the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the subject matter described herein. In the case where program code is stored on media, it may be the case that the program code in question is stored on one or more media that collectively perform the actions in question, which is to say that the one or more media taken together contain code to perform the actions, but that - in the case where there is more than onesingle medium - there is no requirement that any particular part of the code be stored on any particular medium. In the case of program code execution on programmable devices, the computing device generally includes a processor, a storage medium readable by the processor (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. One or more programs that may implement or utilize the processes described in connection with the subject matter described herein, e.g., through the use of an API, reusable controls, or the like. Such programs are preferably implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language, and combined with hardware implementations.

[0122] Although example embodiments may refer to utilizing aspects of the subject matter described herein in the context of one or more stand-alone computing systems, the subject matter described herein is not so limited, but rather may be implemented in connection with any computing environment, such as a network or distributed computing environment. Still further, aspects of the subject matter described herein may be implemented in or across a plurality of processing chips or devices, and storage may similarly be affected across a plurality of devices. Such devices might include personal computers, network servers, handheld devices, supercomputers, or computers integrated into other systems such as automobiles and airplanes.

[0123] In describing preferred embodiments of the subject matter of the present disclosure, as illustrated in the Figures, specific terminology is employed for the sake of clarity. The claimed subject matter, however, is not intended to be limited to the specific terminology so selected, and it is to be understood that each specific element includes all technical equivalents that operate in a similar manner to accomplish a similar purpose.

Claims

CLAIMSWhat is Claimed:1 . A network entity, wherein the network entity comprises: a processor configured to: select a first vertical federated learning (VFL) device, wherein the first VFL device is associated with a first local identifier; determine a second local identifier associated with the first VFL device at a second VFL device, and a third local identifier associated with the first VFL device at a third VFL device; generate a global anonymized identifier that is associated with the first local identifier, the second local identifier, and the third local identifier; assign the global anonymized identifier to the first VFL device to provide privacy protection for at least the first local identifier; and send the global anonymized identifier to the second VFL device and the third VFL device, wherein the global anonymized identifier is used in a VFL procedure.

2. The network entity of claim 1 , wherein the first VFL device comprises a wireless transmit / receive unit (WTRU) or a network function.

3. The network entity of claim 1 or 2, wherein the VFL procedure comprises VFL training of an artificial intelligence model.

4. The network entity of any of claims 1 to 3, wherein the processor is further configured to: send a VFL security key to the first, second, and third VFL devices; receive information associated with artificial intelligence (Al) training, wherein the information is encoded based on the VFL security key; perform an authentication check on the information based on the VFL security key; on a condition that the information is authenticated, determine a trained Al model based on the information; and send results associated with the trained Al model to a second network entity.

5. The network entity of claim 4, wherein the processor being configured to perform the authentication check on the information based on the VFL security key comprises the processor being configured todetermine whether a digital signature in the information is associated with the VFL security key.

6. The network entity of any of claims 1 to 5, wherein the processor is further configured to: receive local training data from the first VFL device; determine a feature based on the local training data and the global anonymized identifier; and use the feature and the local training data to train an artificial intelligence model.

7. The network entity of any of claims 1 to 6, wherein the processor is further configured to generate feedback associated with a global model based on an aggregation of a first model locally trained at the first VFL device, a second model locally trained at the second VFL device, and a third model locally trained at the third VFL device.

8. The network entity of any of claims 1 to 7, wherein the second local identifier and the third local identifier are associated with different protocol layers.

9. The network entity of any of claims 1 to 8, wherein the processor is further configured to subscribe to training data from the first, second, and third VFL devices.

10. A method, performed by a network entity, wherein the method comprises: selecting a first vertical federated learning (VFL) device, wherein the first VFL device is associated with a first local identifier; determining a second local identifier associated with the first VFL device at a second VFL device, and a third local identifier associated with the first VFL device at a third VFL device; generating a global anonymized identifier that is associated with the first local identifier, the second local identifier, and the third local identifier; assigning the global anonymized identifier to the first VFL device to provide privacy protection for at least the first local identifier; and sending the global anonymized identifier to the second VFL device and the third VFL device, wherein the global anonymized identifier is used in a VFL procedure.11 . The method of claim 10, wherein the first VFL device comprises a wireless transmit / receive unit (WTRU) or a network function.

12. The method of claim 10 or 11 , wherein the VFL procedure comprises VFL training of an artificial intelligence model.

13. The method of any of claims 10 to 12, wherein the method further comprises: sending a VFL security key to the first, second, and third VFL devices; receiving information associated with artificial intelligence (Al) training, wherein the information is encoded based on the VFL security key; performing an authentication check on the information based on the VFL security key; on a condition that the information is authenticated, determining a trained Al model based on the information; and sending results associated with the trained Al model to a second network entity.

14. The method of claim 13, wherein performing the authentication check on the information based on the VFL security key comprises determining whether a digital signature in the information is associated with the VFL security key.

15. The method of any of claims 10 to 14, wherein the method further comprises: receiving local training data from the first VFL device; determining a feature based on the local training data and the global anonymized identifier; and using the feature and the local training data to train an artificial intelligence model.

16. The method of any of claims 10 to 15, wherein the method further comprises generating feedback associated with a global model based on an aggregation of a first model locally trained at the first VFL device, a second model locally trained at the second VFL device, and a third model locally trained at the third VFL device.

17. The method of any of claims 10 to 16, wherein the second local identifier and the third local identifier are associated with different protocol layers.

18. The method of any of claims 10 to 17, wherein the method further comprises subscribing to training data from the first, second, and third VFL devices.

Images