Trusted environment detection method and device, storage medium and electronic equipment

Abstract

The invention discloses a trusted environment detection method and device, a storage medium and electronic equipment, and relates to the technical field of network security, the method comprises the following steps: in response to a sensitive operation initiated by a mobile terminal through a first SIM card, sending a control instruction, the control instruction being used for instructing the mobile terminal to detect identity information of a second SIM card through the first SIM card, the second SIM card is another SIM card located in a detection range of the first SIM card, receiving identity information of the second SIM card, determining a relative position of the first SIM card and the second SIM card according to the identity information of the second SIM card, and detecting whether the first SIM card is in a trusted environment according to the relative position. According to the technical scheme, whether the physical environment where the user is located when executing the sensitive operation is safe and credible or not can be detected, the technical blank in the aspect of user physical environment safety perception in the prior art is filled up, and the safety protection capacity is improved.

Description

Technical Field

[0001] This application relates to the field of network security technology, and in particular to a trusted environment detection method, apparatus, storage medium and electronic device. Background Technology

[0002] The Subscriber Identity Module (SIM) is a secure hardware device that conforms to national cryptographic standards and possesses secure storage, computing, and independent communication capabilities. It can support national-level basic applications such as SIM digital identity, and also integrate various convenient card applications such as public transportation cards, school and enterprise access cards, and access control cards, providing a one-card solution for users' lives and work in the 5G era. Currently, many network services have been deeply integrated with the Super SIM card, relying on its security capabilities to complete user authentication and other operations. When processing business involving sensitive information, a high level of security authentication can be achieved based on the Super SIM card.

[0003] To protect user privacy and property security, Super SIM cards offer various security measures, including hardware encryption, multi-factor authentication, and security monitoring and early warning. These solutions effectively prevent risks such as Super SIM card hacking, theft, or authentication bypass. However, their protection relies heavily on the Super SIM card itself. In real-world scenarios, even if user authentication is successful, their actions may not be voluntary, such as performing sensitive operations under duress. Existing technologies lack effective perception and assessment of the user's physical environment and operational behavior, failing to detect whether the user is in a monitored or coerced environment, thus hindering comprehensive protection of user privacy and property security. Summary of the Invention

[0004] In view of this, this application provides a trusted environment detection method, apparatus, storage medium, and electronic device to detect whether the physical environment in which a user is located when performing sensitive operations is safe and trusted.

[0005] Firstly, this application provides a trusted environment detection method, including: In response to a sensitive operation initiated by the mobile terminal through the first SIM card, a control command is sent; the control command is used to instruct the mobile terminal to detect the identity information of the second SIM card through the first SIM card; the second SIM card is another SIM card located within the detection range of the first SIM card; Receive the identity information of the second SIM card; Based on the identity information of the second SIM card, determine the relative positions of the first SIM card and the second SIM card; Based on the relative position, it is determined whether the first SIM card is in a trusted environment.

[0006] In some embodiments of this disclosure, the sending of control commands includes: Generate the first random value; Write the first random value into the control command; Send the control command to the mobile terminal; In response to a control response sent by the mobile terminal, the second random value and ciphertext in the control response are parsed. The registration information is retrieved locally; the registration information is the registration information reserved by the first SIM card in the server. Based on the first random value and the registration information, a key generation function is selected from the key algorithm pool corresponding to the first SIM card; Based on the second random value and the registration information, a symmetric key algorithm is selected from the key algorithm pool corresponding to the first SIM card; Using the key generation function, a key is generated based on the first random value, the second random value, and the registration information; The ciphertext is decrypted using the key and the symmetric key algorithm to obtain the identity information of the second SIM card.

[0007] In some embodiments of this disclosure, determining the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card includes: Based on the identity information of the second SIM card, reverse positioning is performed on the second SIM card to obtain its current location; A coordinate system is constructed with the current position of the first SIM card as the origin, and the current position of the second SIM card is converted into coordinates in the coordinate system to obtain the relative position.

[0008] In some embodiments of this disclosure, the method further includes: Based on the identity information of the second SIM card, the communication relationship between the first SIM card and the second SIM card is determined; Based on the relative position and the communication relationship, it is determined whether the first SIM card is in a trusted environment.

[0009] In some embodiments of this disclosure, detecting whether the first SIM card is in a trusted environment based on the relative position and the communication relationship includes: The risk value and uncertainty are calculated based on the relative position; the risk value represents the safety level of the current environment; the uncertainty represents the confidence level of the relative position. A relationship coefficient is calculated based on the communication relationship; the relationship coefficient is used to represent the communication tightness between the first SIM card and the second SIM card; The environmental credibility is calculated based on the risk value, the uncertainty, and the relationship coefficient. Based on the degree of trustworthiness of the environment, it is determined whether the first SIM card is in a trustworthy environment.

[0010] In some embodiments of this disclosure, calculating the risk value and uncertainty based on the relative position includes: Construct a temporal position sequence based on the relative positions within a continuous time period; The time-series position sequence is input into a pre-trained deep learning model to detect the risk value and the uncertainty, so as to obtain the risk value and the uncertainty.

[0011] In some embodiments of this disclosure, the deep learning model includes a backbone structure, a first branch structure, and a second branch structure; the backbone structure is used to extract features from the temporal position sequence and input the features into the first branch structure and the second branch structure respectively; the first branch structure is used to detect and output the risk value; and the second branch structure is used to detect and output the uncertainty.

[0012] In some embodiments of this disclosure, calculating the relationship coefficient based on the communication relationship includes: The quantitative values ​​of the communication relationship are determined; the quantitative values ​​include SMS communication frequency, telephone communication frequency, and data traffic generated during communication per unit time. Determine the preset baseline value; A relationship coefficient is calculated based on the quantized value and the benchmark value; the relationship coefficient is the weighted sum of the ratios of the quantized value and the benchmark value.

[0013] In some embodiments of this disclosure, detecting whether the first SIM card is in a trusted environment based on the degree of environmental trust includes: Determine the confidence threshold based on the operation type of the sensitive operation; If the trust level of the environment is less than the trust level threshold, the first SIM card is determined to be in an untrusted environment, and the sensitive operation is prevented from being performed. If the trust level of the environment is greater than or equal to the trust level threshold, the first SIM card is determined to be in a trust environment, and the sensitive operation is allowed to be performed.

[0014] Secondly, this application provides a trusted environment detection method, including: After a sensitive operation is initiated through the first SIM card, in response to a control command sent by the server, the identity information of the second SIM card is detected through the first SIM card; the second SIM card is another SIM card located within the detection range of the first SIM card. The server sends the identity information of the second SIM card so that it can determine the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card, and detect whether the first SIM card is in a trusted environment based on the relative position.

[0015] In some embodiments of this disclosure, sending the identity information of the second SIM card includes: Analyze the first random value in the control command; Generate a second random value; The registration information is read from the local machine; the registration information is the registration information reserved by the first SIM card in the server. Based on the first random value and the registration information, a key generation function is selected from the key algorithm pool pre-set in the first SIM card; Based on the second random value and the registration information, a symmetric key algorithm is selected from the key algorithm pool pre-set in the first SIM card; Using the key generation function, a key is generated based on the first random value, the second random value, and the registration information; Using the key and the symmetric key algorithm, the identity information of the second SIM card is encrypted to obtain ciphertext; The second random value and the ciphertext are written into the control response, and the control response is sent to the server.

[0016] Thirdly, this application provides a reliable environment detection device, comprising: The first sending module is used to send a control command in response to a sensitive operation initiated by the mobile terminal through the first SIM card; the control command is used to instruct the mobile terminal to detect the identity information of the second SIM card through the first SIM card; the second SIM card is another SIM card located within the detection range of the first SIM card; The first receiving module is used to receive the identity information of the second SIM card; The first detection module is used to determine the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card; and to detect whether the first SIM card is in a trusted environment based on the relative position.

[0017] Fourthly, this application provides a reliable environment detection device, comprising: The second detection module is used to detect the identity information of the second SIM card through the first SIM card in response to the control command sent by the server after a sensitive operation is initiated through the first SIM card; the second SIM card is another SIM card located within the detection range of the first SIM card. The second sending module is used to send the identity information of the second SIM card, so that the server can determine the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card, and detect whether the first SIM card is in a trusted environment based on the relative position.

[0018] Fifthly, this application provides an electronic device including at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect or the second aspect.

[0019] In a sixth aspect, this application provides a computer-readable storage medium storing computer instructions for causing the computer to perform the method described in the first or second aspect.

[0020] In a seventh aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first or second aspect.

[0021] Based on the above technical solutions, this application provides a trusted environment detection method, apparatus, storage medium, and electronic device, relating to the field of network security technology. The method includes: responding to a sensitive operation initiated by a mobile terminal through a first SIM card, sending a control command, the control command instructing the mobile terminal to detect the identity information of a second SIM card through the first SIM card, the second SIM card being another SIM card located within the detection range of the first SIM card; receiving the identity information of the second SIM card; determining the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card; and detecting whether the first SIM card is in a trusted environment based on the relative position.

[0022] In the technical solution of this application, when the server detects a sensitive operation initiated by the user on the mobile terminal through the first SIM card, it controls the mobile terminal to detect the identity information of other second SIM cards in the vicinity through the first SIM card via control instructions. This allows the server to locate the relative position of the second SIM card with respect to the first SIM card based on the identity information of the second SIM card, thereby determining whether the first SIM card (the current user) is in a trusted environment. This fills the technical gap in the existing technology regarding the security perception of the user's physical environment and improves security protection capabilities.

[0023] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0024] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0025] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 A flowchart illustrating a trusted environment detection method for servers provided in this embodiment of the disclosure; Figure 2 A flowchart illustrating a trusted environment detection method for mobile terminals provided in an embodiment of this disclosure; Figure 3 This is a schematic diagram of the structure of a deep learning model provided in an embodiment of the present disclosure; Figure 4 A schematic diagram of backbone structure training provided in an embodiment of this disclosure; Figure 5 Schematic diagram of the trusted environment detection device provided in the embodiments of this disclosure Figure 1 ; Figure 6 Schematic diagram of the trusted environment detection device provided in the embodiments of this disclosure Figure 2 ; Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0027] The embodiments of this application will now be described in more detail with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0028] Embodiments of this disclosure are described in detail below, with examples of embodiments illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting this disclosure.

[0029] This disclosure is not exhaustive, but merely illustrative of some embodiments, and is not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0030] In each of the disclosed embodiments, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of the embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0031] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure. In this disclosure, unless otherwise stated, elements expressed in the singular form, such as "a," "an," "the," "the," "the," "the," "the," "the," "this," etc., can mean "one and only one," or "one or more," "at least one," etc. For example, when using articles such as "a," "an," "the," etc. in translation, the noun following the article can be understood as either a singular or a plural expression.

[0032] In some embodiments, the terms “in response to…”, “in response to determining…”, “in the case of…”, “when…”, “if…”, “if…”, etc., can be used interchangeably.

[0033] In some embodiments, the terms “greater than,” “greater than or equal to,” “not less than,” “more than,” “more than or equal to,” “not less than,” “higher than,” “higher than or equal to,” “not lower than,” and “above” can be used interchangeably, as can the terms “less than,” “less than or equal to,” “not greater than,” “less than,” “less than or equal to,” “not more than,” “lower than,” “lower than or equal to,” “not higher than,” and “below”.

[0034] The prefixes such as "first" and "second" in the embodiments of this disclosure are only for distinguishing different descriptive objects and do not constitute restrictions on the position, order, priority, number or content of the descriptive objects. For the description of the descriptive objects, please refer to the description in the claims or the context of the embodiments. The use of prefixes should not constitute unnecessary restrictions.

[0035] In the embodiments disclosed herein, "multiple" refers to two or more.

[0036] In the embodiments disclosed herein, terms such as “import”, “input”, and “read in” can be used interchangeably.

[0037] In some embodiments, devices, etc., can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as “device”, “equipment”, “circuit”, “network element”, “node”, “function”, “unit”, “section”, “system”, “network”, “chip”, “chip system”, “entity”, and “subject” can be used interchangeably.

[0038] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriberstation, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, and client can be used interchangeably.

[0039] The Subscriber Identity Module (SIM) is a secure hardware device that conforms to national cryptographic standards and possesses secure storage, computing, and independent communication capabilities. It is operable and manageable. The card can not only support national-level basic applications such as SIM digital identity, but also integrate various convenient card applications such as public transportation cards, school and enterprise all-in-one cards, and access control cards, providing a one-card solution for users' lives and work in the 5G era, enabling them to use a single mobile phone for all their needs. Currently, many network services have been deeply integrated with the Super SIM card, relying on its security capabilities to complete user authentication and other operations. When processing business involving sensitive information, a high level of security authentication can be achieved based on the Super SIM card.

[0040] To protect user privacy and asset security, the Super SIM card provides security protection in the following three ways: Hardware encryption technology: The Super SIM card has a built-in national cryptographic security chip that encrypts user data stored in the Super SIM card at the hardware level, ensuring that information cannot be illegally read or tampered with at the physical level.

[0041] Multi-factor authentication mechanism; using biometric technologies (such as fingerprints, faces, etc.), SIM card shields, dynamic passwords and other methods to authenticate user identity, strengthen the identity authentication process, and ensure that only authorized users can perform sensitive operations.

[0042] Security monitoring and early warning: Based on users' communication behavior and operating habits, big data analysis is used to monitor abnormal user behavior in real time and trigger early warnings in a timely manner. For example, if abnormal operations such as logging in from a different location with the Super SIM card or frequently trying the wrong password are detected, the account will be temporarily frozen or access will be restricted.

[0043] The aforementioned security measures focus on the security of the Super SIM card itself, employing various methods to prevent its cracking, bypassing, or theft. However, these methods cannot address situations involving the verification of user intent, such as user-initiated switching or coerced operations. Existing methods have certain monitoring blind spots, failing to detect user status or whether sensitive operations were triggered under duress.

[0044] To address the aforementioned problems, embodiments of this application provide a reliable environment detection method, such as... Figure 1 The diagram shown is a flowchart of a trusted environment detection method provided in this application embodiment, applied to a server, and includes the following steps: S101: In response to a sensitive operation initiated by the mobile terminal through the first SIM card, a control command is sent, which instructs the mobile terminal to detect the identity information of the second SIM card through the first SIM card.

[0045] The second SIM card is any other SIM card within the detection range of the first SIM card, and there can be multiple second SIM cards. In some scenarios, the first and second SIM cards can be super SIM cards.

[0046] Sensitive operations are those involving user privacy and asset security, including mobile payments and sensitive data transmission. It is understood that such sensitive operations may occur voluntarily or under duress. To effectively identify and block involuntary risky operations, the server can respond to sensitive operations by initiating a subsequent trusted environment detection process. This process dynamically assesses the trustworthiness of the user's environment and determines whether to allow the sensitive operation based on that trustworthiness, thereby ensuring user privacy and asset security.

[0047] S102: Receive the identity information of the second SIM card.

[0048] S103: Determine the relative positions of the first SIM card and the second SIM card based on the identity information of the second SIM card.

[0049] S104: Detect whether the first SIM card is in a trusted environment based on the relative position.

[0050] like Figure 2 The diagram shown is a flowchart of a trusted environment detection method provided in an embodiment of this application. The method is applied to a mobile terminal, which includes a first SIM card and comprises the following steps: S201: After a sensitive operation is initiated through the first SIM card, in response to the control command sent by the server, the identity information of the second SIM card is detected through the first SIM card.

[0051] The second SIM card is any other SIM card that is within the detection range of the first SIM card.

[0052] S202: Send the identity information of the second SIM card so that the server can determine the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card, and detect whether the first SIM card is in a trusted environment based on the relative position.

[0053] In this embodiment, when the server detects a sensitive operation initiated by a user on a mobile terminal using the first SIM card, it can control the mobile terminal to obtain the identity information of the second SIM cards of other users in the vicinity through the first SIM card. Based on this identity information, the server can determine the relative position of the second SIM card with respect to the first SIM card, thereby determining whether the first SIM card (the current user) is in a trusted environment (secure environment). This fills the technological gap in existing technologies regarding user physical environment security awareness, improves security protection capabilities, and safeguards the privacy and security of user identity and location information. This method is a low-power, high-precision identity and environment assessment scheme that enables a dynamic, environment-aware security protection mechanism. When the system determines that the user is in an untrusted environment, it can proactively prevent sensitive operations even if identity authentication is successful.

[0054] In some embodiments, the server can monitor in real time the operations performed by the user through the first SIM card in the mobile terminal. When a sensitive operation is detected, the server can perform a subsequent trusted environment detection process to detect whether the first SIM card (the current user) is in a trusted environment and decide whether to allow the sensitive operation to be performed accordingly.

[0055] In some embodiments, in order to ensure the security of communication between the server and the mobile terminal, when the server detects a sensitive operation performed by the user through the first SIM card in the mobile terminal, in response to the sensitive operation, it generates a first random value SaltA, writes the first random value SaltA into the control command, and sends the control command to the mobile terminal.

[0056] The mobile terminal receives a control command, responds to the control command by parsing the first random value SaltA in the control command, detects the identity information Info of the surrounding second SIM cards through the first SIM card, generates a second random value SaltB, and reads the registration information Reg from the local machine.

[0057] The registration information is the registration information reserved by the first SIM card in the server. For example, the registration information consists of a specified number of characters from the user's ID card and a specified number of characters from the International Mobile Subscriber Identity (IMSI).

[0058] The mobile terminal selects a key generation function f from the key algorithm pool pre-set in the first SIM card based on the first random value SaltA and the registration information Reg, and selects a symmetric key algorithm RC from the key algorithm pool pre-set in the first SIM card based on the second random value SaltB and the registration information Reg.

[0059] For example, a mobile terminal can perform a hash operation on a specified number of bits taken from both a first random value SaltA and the registration information Reg, using the remainder as an index to select the key generation function f corresponding to that index from the key algorithm pool. Similarly, a mobile terminal can perform a hash operation on a specified number of bits taken from both a second random value SaltB and the registration information Reg to select the symmetric key algorithm RC.

[0060] The mobile terminal uses a key generation function f to generate a key Key that meets the requirements of the symmetric key algorithm RC, based on a first random value SaltA, a second random value SaltB, and registration information Reg, i.e., Key = f (SaltA, SaltB, Reg). Then, the key Key and the symmetric key algorithm RC are used to encrypt the identity information Info of the second SIM card, resulting in ciphertext Info_Secret, i.e., Info_Secret = RC(Key, Info). Finally, the second random value SaltB and the ciphertext Info_Secret are written into the control response, which is then sent to the server.

[0061] After receiving the control response from the mobile terminal, the server parses the second random value SaltB and the ciphertext Info_Secret in the control response, and queries the registration information Reg of the first SIM card in the mobile terminal that was reserved on the server from the local machine.

[0062] The server selects a key generation function f from the key algorithm pool corresponding to the first SIM card based on the first random value SaltA and the registration information Reg, and selects a symmetric key algorithm RC from the key algorithm pool corresponding to the first SIM card based on the second random value SaltB and the registration information Reg.

[0063] The server can locally deploy multiple key algorithm pools used by SIM cards. The key algorithm pool used by the first SIM card can be determined based on the registration information Reg that the first SIM card has reserved on the server. The selection of the key generation function f and the symmetric key algorithm RC can be referred to the selection operation of the mobile terminal described above, and will not be repeated here.

[0064] The server uses a key generation function f to generate a key Key that meets the requirements of the symmetric key algorithm RC, based on a first random value SaltA, a second random value SaltB, and registration information Reg. That is, Key = f(SaltA, SaltB, Reg). Then, the ciphertext Info_Secret is decrypted using the key Key and the symmetric key algorithm RC to obtain the identity information Info of the second SIM card, i.e., Info = RC(Key, Info_Secret).

[0065] In this embodiment, the key generation function and symmetric key algorithm are determined by real-time random values ​​and registration information, and a one-time pad session key is dynamically generated, which can effectively improve the security of communication.

[0066] In some embodiments, after the server obtains the identity information of the second SIM card, it can use the mobile network infrastructure (such as base station positioning) to perform reverse positioning of the second SIM card based on the identity information of the second SIM card, obtain the current position of the second SIM card, and then construct a coordinate system with the current position of the first SIM card as the origin, and convert the current position of the second SIM card into coordinates in the coordinate system to obtain the relative position of the second SIM card with respect to the first SIM card, that is, the relative position of other users with respect to the current user.

[0067] In this embodiment, the server constructs a coordinate system with the first SIM card (mobile terminal, current user) as the origin, and performs reverse positioning on the second SIM card based on the identity information of the second SIM card of other users to obtain the coordinates of the second SIM card in the coordinate system. These coordinates are the relative position of the second SIM card with respect to the first SIM card, which can reflect the distance and direction between other users and the current user.

[0068] There is a significant difference between normal social spatial distance and spatial distance in coercive scenarios. When a user is being coerced, the distance between the coercor and the user exhibits certain patterns, such as a spatial distribution pattern indicating a controlling intent, like surrounding or closely holding the user, to prevent the user from escaping. Therefore, the distance and location between the current user and other users are characteristics that can be used to identify whether the current environment is trustworthy.

[0069] In some embodiments, the server can determine the communication relationship between the first SIM card and the second SIM card based on the identity information of the second SIM card, and detect whether the first SIM card is currently in a trusted environment based on the relative position and communication relationship.

[0070] The communication relationship is used to characterize the historical interaction behavior between the first SIM card (current user) and the second SIM card (other users) through the mobile communication network.

[0071] In some embodiments, the server can calculate the risk value and uncertainty based on the relative position of the second SIM card with respect to the first SIM card, calculate the relationship coefficient based on the communication relationship, calculate the environmental trustworthiness based on the risk value, uncertainty and relationship coefficient, and determine whether the first SIM card is currently in a trustworthy environment based on the environmental trustworthiness.

[0072] The risk value represents the security level of the current environment; a higher risk value indicates a greater likelihood of an untrusted environment. Uncertainty represents the confidence level of the relative location; higher uncertainty indicates a less reliable relative location. The relationship coefficient represents the communication tightness between the first SIM card (the current user) and the second SIM card (other users) in historical interactions. A lower relationship coefficient, a higher risk value, and higher uncertainty indicate a lower level of environmental trust and a greater likelihood that the current environment is untrusted.

[0073] In some embodiments, the server can locate the relative position of the second SIM card with respect to the first SIM card within a continuous time period, construct a time-series position sequence based on the relative position within the continuous time period, input the time-series position sequence into a pre-trained deep learning model, and perform risk value and uncertainty detection to obtain the risk value and uncertainty.

[0074] For example, the relative position of the second SIM card (other users) relative to the first SIM card (current user) is determined over t consecutive time points. At each time point, the distance between the second and first SIM cards is calculated based on their relative positions. The k closest relative positions are selected. If there are fewer than k relative positions, zeros are added. The k relative positions are then organized into a k-dimensional vector according to their directional distribution. Arranged chronologically, the k-dimensional vectors from the t time points form a temporal position sequence, M = {m1, m2, ..., mt}.

[0075] Understandably, on the one hand, changes in the time-series location sequence reflect the relative positional changes among users in the current environment, which can be used to assess the security level of the user's current environment, i.e., the risk value. On the other hand, there is a certain error in the reverse positioning of the second SIM card through positioning technology (such as base station positioning), and the time-series location sequence can also reflect this measurement error, which can be used to assess the reliability of the positioning results, i.e., the uncertainty.

[0076] In summary, this application can construct a unified deep learning model for coordinate detection based on deep learning, and use a temporal position sequence to synchronously output risk values ​​and their uncertainties.

[0077] like Figure 3 The diagram shown is a structural schematic of a deep learning model provided in an embodiment of this application. The deep learning model includes a shared backbone structure and two independent branches, namely the first branch structure (Branch1) and the second branch structure (Branch2).

[0078] The backbone structure can use structures such as Long Short-Term Memory (LSTM) networks and Gated Recurrent Units (GRUs) to extract common features from the input temporal position sequence M. These features are unbiased by the task and can be used by both the subsequent task of detecting risk values ​​and the task of detecting uncertainty, effectively reducing the computational load of feature extraction.

[0079] The first branch structure includes a first encoder (Encoder1) and a first output head (Head1). The first encoder can use structures such as LSTM and GRU to continue extracting deeper features and perform the task of detecting risk values. The first output head can use structures such as a fully connected layer (FC) and a sigmoid function to output risk values.

[0080] The second branch structure includes a second encoder (Encoder2) and a second output head (Head2). The second encoder can use structures such as LSTM and GRU to continue extracting deeper features and perform the task of detecting uncertainty. The second output head can use structures such as FC and Sigmoid to output uncertainty.

[0081] In some embodiments, the training of a deep learning model includes two stages: the first stage is self-supervised training of the backbone structure, and the second stage is supervised training of the branch structure.

[0082] In the first stage, the backbone structure is trained individually using a self-supervised approach, such as... Figure 4 The diagram shown is a schematic of the backbone structure training provided in the embodiment of this application. Based on the sequence-to-sequence (Seq2Seq) architecture, the backbone structure is regarded as a third encoder (Encoder3) and connected to a decoder (Decoder). The structure of the decoder is the opposite of that of the third encoder (backbone structure), thus constructing a reconstruction network. The training objective of this reconstruction network is that the output sequence is the same as the input sequence, that is, the decoder can accurately reconstruct the input sequence based on the features extracted by the third encoder.

[0083] During training, sample sequence 1 is input into the third encoder (i.e., the backbone structure) for feature extraction. The extracted features are then input into the decoder for sequence reconstruction, generating sample sequence 2. The generation loss values ​​(such as mean squared error (MSE) and mean absolute error (MAE)) between sample sequence 1 and sample sequence 2 are calculated to update the parameters of the third encoder (i.e., the backbone structure) and the decoder.

[0084] After training is complete, the decoder can be discarded, and the third encoder (i.e., the backbone structure) that has learned effective feature representations can be retained.

[0085] In the second stage, while keeping the parameters of the backbone structure unchanged, supervised training is performed simultaneously on the first and second branch structures. Sample sequences are constructed and labeled with the true risk value 1 and uncertainty 1. These labeled sample sequences are then input into the deep learning model to train the first and second branch structures simultaneously. The parameters of the first and second branch structures are optimized based on the joint loss between the predicted risk value 2 and uncertainty 2 and the true risk value 1 and uncertainty 1.

[0086] The sample sequences include positive and negative sample sequences. Positive sample sequences are location sequences generated during normal user activities in various locations, while negative sample sequences are location sequences generated under simulated coercive scenarios. To eliminate the impact of sample class imbalance on model training, the more numerous positive sample sequences can be downsampled, and the fewer numerous negative sample sequences can be resampled to balance the samples.

[0087] In some embodiments, the risk value 1 is a label that can be assigned based on human experience, and the uncertainty 1 can be quantified and calculated using the following formula: ; in, For uncertainty 1, N represents the number of familiar users around the current user, and M represents the number of unfamiliar users around the current user. Let be the distance between the current user and the i-th familiar user. Let j be the distance between the current user and the j-th unfamiliar user. This is a normal reference distance between the current user and familiar users. This is a normal reference distance between the current user and an unfamiliar user. and As weight, > This reflects the greater weight given to the impact of uncertainty on the distance between current users and familiar users.

[0088] During training, sample sequences labeled with risk value 1 and uncertainty value 1 are input into the pre-trained backbone structure for feature extraction. The extracted features are then input into the first branch structure to perform the task of detecting risk values ​​and output risk value 2. Based on risk value 1 and risk value 2, loss value 1 (such as cross-entropy loss) is calculated. Simultaneously, the extracted features are also input into the second branch structure to perform the task of detecting uncertainty and output uncertainty 2. Based on uncertainty 1 and uncertainty 2, loss value 2 (such as relative entropy loss) is calculated. Then, risk value 1 and risk value 2 are weighted and summed to obtain risk value 3, which is used to update the parameters of the first and second branch structures. The parameters of the backbone structure remain unchanged in this stage and are not updated.

[0089] In some embodiments, the server can quantify the communication relationship between the first SIM card (current user) and the second SIM card (other users) from multiple dimensions. The quantified values ​​of the communication relationship include SMS communication frequency, telephone communication frequency, and data traffic generated per unit time. To comprehensively evaluate the closeness of the relationship, the relationship coefficient can be calculated using the following formula: ; in, The coefficient represents the relationship. This represents the quantized value of the i-th communication relationship. This is the baseline value for the i-th communication relationship, that is, the reasonable value for this communication relationship in normal social relationships. Let i be the weight of the i-th communication relationship. This represents the total number of communication relationships. In other words, the relationship coefficient is the weighted sum of the ratios of the quantified values ​​to the baseline values.

[0090] In some embodiments, the credibility of the environment can be calculated based on the following formula, according to the risk value, uncertainty, and relationship coefficient: ; in, For environmental credibility, This is the risk value. Due to uncertainty, Let be the relationship coefficient. In this formula, the degree of environmental credibility is positively correlated with the relationship coefficient and negatively correlated with the risk value and uncertainty.

[0091] In some embodiments, the server can compare the calculated environmental trust level with a preset trust level threshold and make a final decision on whether to allow the execution of sensitive operations. That is, if the environmental trust level is less than the preset trust level threshold, the server can determine that the first SIM card (current user) is in an untrusted environment and prevent the execution of sensitive operations by the current user. If the environmental trust level is greater than or equal to the preset trust level threshold, the server can determine that the first SIM card (current user) is in a trusted environment and allow the execution of sensitive operations by the current user.

[0092] In some embodiments, the server can set different trust thresholds for different types of sensitive operations. The sensitivity of a sensitive operation is positively correlated with the corresponding trust threshold, thereby achieving different levels of protection. For example, mobile payment operations involving financial transactions have a higher level of protection, and their trust thresholds are also set accordingly, requiring execution only in a highly trusted environment.

[0093] In response, the server can detect the type of sensitive operation, determine the corresponding trust threshold based on the operation type, and compare the calculated environmental trust level with the trust threshold. If the environmental trust level is less than the trust threshold, it is determined that the first SIM card (current user) is in an untrusted environment, and the sensitive operation of the current user is blocked.

[0094] The above embodiments provide a trusted environment detection method based on SIM cards. During the user authentication process, the identity information of the SIM cards of other users in the vicinity is obtained through the current user's mobile terminal and SIM card. The server performs reverse positioning based on the identity information to obtain the location of the other users' SIM cards. By analyzing the relative positional relationship, dynamic movement patterns, and historical communication behavior between SIM cards, the method comprehensively calculates whether the current user's environment is a trusted environment (secure environment). By providing a protection mechanism for users, the method enhances the detection of situations where others operate or coerce users to operate, thereby protecting the privacy and security of user identity and location information.

[0095] When users are coerced, the coercer may force them to perform operations such as transferring or making payments, resulting in significant financial losses for the user. This application detects whether a user is being coerced, promptly identifies abnormal operations, and takes appropriate measures, such as suspending transactions and freezing accounts, to effectively protect the user's personal privacy and asset security, and prevent theft of funds.

[0096] At the same time, detecting whether a user is under duress can serve as an additional security mechanism, adding a layer of security for the SIM card, thereby reducing the business risks of the SIM card and improving its security and reliability.

[0097] Users often worry about personal information leaks and financial security when using SIM cards for various operations. This application provides a function to detect whether a user is being coerced, allowing users to experience more comprehensive security protection, thereby enhancing their trust and sense of security in communication and financial services, and improving user satisfaction and loyalty.

[0098] According to embodiments of this disclosure, this disclosure also provides a trusted environment detection device, such as... Figure 5 The diagram shown is a structural schematic of a trusted environment detection device provided in a disclosed embodiment. The device includes: The first transmitting module 501 is used to send a control command in response to a sensitive operation initiated by the mobile terminal through the first SIM card. The control command instructs the mobile terminal to detect the identity information of the second SIM card through the first SIM card. The second SIM card is any other SIM card located within the detection range of the first SIM card.

[0099] The first receiving module 502 is used to receive the identity information of the second SIM card.

[0100] The first detection module 503 is used to determine the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card; and to detect whether the first SIM card is in a trusted environment based on the relative position.

[0101] In some embodiments, the first sending module 501 is used to generate a first random value, write the first random value into a control instruction, and send the control instruction to the mobile terminal.

[0102] The first receiving module 502 is used to respond to the control response sent by the mobile terminal, parse the second random value and ciphertext in the control response, query the registration information from the local machine, select a key generation function from the key algorithm pool corresponding to the first SIM card based on the first random value and the registration information, select a symmetric key algorithm from the key algorithm pool corresponding to the first SIM card based on the second random value and the registration information, use the key generation function to generate a key according to the first random value, the second random value and the registration information, and use the key and the symmetric key algorithm to decrypt the ciphertext to obtain the identity information of the second SIM card.

[0103] The registration information refers to the registration information reserved by the first SIM card in the server.

[0104] In some embodiments, the first detection module 503 is used to perform reverse positioning on the second SIM card based on the identity information of the second SIM card to obtain the current position of the second SIM card; construct a coordinate system with the current position of the first SIM card as the origin, and convert the current position of the second SIM card into coordinates in the coordinate system to obtain the relative position.

[0105] In some embodiments, the first detection module 503 is used to calculate risk value and uncertainty based on relative position, calculate relationship coefficient based on communication relationship, calculate environmental trustworthiness based on risk value, uncertainty and relationship coefficient, and detect whether the first SIM card is in a trustworthy environment based on environmental trustworthiness.

[0106] The risk value represents the security level of the current environment. Uncertainty represents the confidence level of the relative position. The relationship coefficient represents the communication strength between the first and second SIM cards.

[0107] In some embodiments, the first detection module 503 is used to construct a temporal position sequence based on the relative position within a continuous time period, input the temporal position sequence into a pre-trained deep learning model, and detect risk values ​​and uncertainties to obtain risk values ​​and uncertainties.

[0108] In some embodiments, the first detection module 503 is used to determine the quantized value of the communication relationship, determine the preset reference value, and calculate the relationship coefficient based on the quantized value and the reference value.

[0109] The quantified values ​​include SMS communication frequency, telephone communication frequency, and data traffic generated per unit time. The relationship coefficient is the weighted sum of the ratios of the quantified values ​​to the baseline values.

[0110] In some embodiments, the first detection module 503 is configured to determine a trust level threshold based on the operation type of the sensitive operation; if the environmental trust level is less than the trust level threshold, determine that the first SIM card is in an untrusted environment and prevent the execution of the sensitive operation; if the environmental trust level is greater than or equal to the trust level threshold, determine that the first SIM card is in a trusted environment and allow the execution of the sensitive operation.

[0111] According to embodiments of this disclosure, this disclosure also provides a trusted environment detection device, such as... Figure 6 The diagram shown is a structural schematic of a trusted environment detection device provided in a disclosed embodiment. The device includes: The second detection module 601 is used to detect the identity information of the second SIM card via the first SIM card in response to a control command sent by the server after a sensitive operation is initiated through the first SIM card. The second SIM card is any other SIM card within the detection range of the first SIM card.

[0112] The second sending module 602 is used to send the identity information of the second SIM card so that the server can determine the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card, and detect whether the first SIM card is in a trusted environment based on the relative position.

[0113] In some embodiments, the second detection module 601 is configured to parse the first random value in the control command, generate a second random value, read registration information from the local machine, select a key generation function from the key algorithm pool preset in the first SIM card based on the first random value and the registration information, select a symmetric key algorithm from the key algorithm pool preset in the first SIM card based on the second random value and the registration information, use the key generation function to generate a key according to the first random value, the second random value and the registration information, use the key and the symmetric key algorithm to encrypt the identity information of the second SIM card to obtain ciphertext, write the second random value and the ciphertext into the control response, and send the control response to the server.

[0114] The registration information refers to the registration information reserved by the first SIM card in the server.

[0115] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0116] Figure 7 A schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0117] like Figure 7 As shown, the electronic device 700 includes a computing unit 701, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 702 or a computer program loaded from storage unit 708 into RAM (Random Access Memory) 703. The RAM 703 can also store various programs and data required for the operation of the electronic device 700. The computing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An I / O (Input / Output) interface 705 is also connected to the bus 704.

[0118] Multiple components in electronic device 700 are connected to I / O interface 705, including: input unit 706, such as keyboard, mouse, etc.; output unit 707, such as various types of displays, speakers, etc.; storage unit 708, such as disk, optical disk, etc.; and communication unit 709, such as network card, modem, wireless transceiver, etc. Communication unit 709 allows electronic device 700 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0119] The computing unit 701 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above, such as the trusted environment detection method. For example, in some embodiments, the trusted environment detection method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 700 via ROM 702 and / or communication unit 709. When the computer program is loaded into RAM 703 and executed by the computing unit 701, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the aforementioned trusted environment detection method by any other suitable means (e.g., by means of firmware).

[0120] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), System-on-Chips (SOCs), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0121] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0122] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Erasable Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0123] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0124] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0125] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0126] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0127] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0128] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A reliable environment detection method, characterized in that, Applied to servers, including: In response to a sensitive operation initiated by the mobile terminal through the first SIM card, a control command is sent; the control command is used to instruct the mobile terminal to detect the identity information of the second SIM card through the first SIM card; the second SIM card is another SIM card located within the detection range of the first SIM card; Receive the identity information of the second SIM card; Based on the identity information of the second SIM card, determine the relative positions of the first SIM card and the second SIM card; Based on the relative position, it is determined whether the first SIM card is in a trusted environment.

2. The method according to claim 1, characterized in that, The sending control command includes: Generate the first random value; Write the first random value into the control command; Send the control command to the mobile terminal; In response to a control response sent by the mobile terminal, the second random value and ciphertext in the control response are parsed. The registration information is retrieved locally; the registration information is the registration information reserved by the first SIM card in the server. Based on the first random value and the registration information, a key generation function is selected from the key algorithm pool corresponding to the first SIM card; Based on the second random value and the registration information, a symmetric key algorithm is selected from the key algorithm pool corresponding to the first SIM card; Using the key generation function, a key is generated based on the first random value, the second random value, and the registration information; The ciphertext is decrypted using the key and the symmetric key algorithm to obtain the identity information of the second SIM card.

3. The method according to claim 1 or 2, characterized in that, Determining the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card includes: Based on the identity information of the second SIM card, reverse positioning is performed on the second SIM card to obtain its current location; A coordinate system is constructed with the current position of the first SIM card as the origin, and the current position of the second SIM card is converted into coordinates in the coordinate system to obtain the relative position.

4. The method according to claim 1 or 2, characterized in that, The method further includes: Based on the identity information of the second SIM card, the communication relationship between the first SIM card and the second SIM card is determined; Based on the relative position and the communication relationship, it is determined whether the first SIM card is in a trusted environment.

5. The method according to claim 4, characterized in that, The step of detecting whether the first SIM card is in a trusted environment based on the relative position and the communication relationship includes: The risk value and uncertainty are calculated based on the relative position; the risk value represents the safety level of the current environment; the uncertainty represents the confidence level of the relative position. A relationship coefficient is calculated based on the communication relationship; the relationship coefficient is used to represent the communication tightness between the first SIM card and the second SIM card; The environmental credibility is calculated based on the risk value, the uncertainty, and the relationship coefficient. Based on the degree of trustworthiness of the environment, it is determined whether the first SIM card is in a trustworthy environment.

6. The method according to claim 5, characterized in that, The calculation of risk value and uncertainty based on the relative position includes: Construct a temporal position sequence based on the relative positions within a continuous time period; The time-series position sequence is input into a pre-trained deep learning model to detect the risk value and the uncertainty, so as to obtain the risk value and the uncertainty.

7. The method according to claim 6, characterized in that, The deep learning model includes a backbone structure, a first branch structure, and a second branch structure; the backbone structure is used to extract features from the temporal position sequence and input the features into the first branch structure and the second branch structure, respectively. The first branch structure is used to detect and output the risk value; The second branch structure is used to detect and output the uncertainty.

8. The method according to claim 5, characterized in that, The calculation of the relationship coefficient based on the communication relationship includes: The quantitative values ​​of the communication relationship are determined; the quantitative values ​​include SMS communication frequency, telephone communication frequency, and data traffic generated during communication per unit time. Determine the preset baseline value; A relationship coefficient is calculated based on the quantized value and the benchmark value; the relationship coefficient is the weighted sum of the ratios of the quantized value and the benchmark value.

9. The method according to claim 5, characterized in that, The step of detecting whether the first SIM card is in a trusted environment based on the degree of environmental trust includes: Determine the confidence threshold based on the operation type of the sensitive operation; If the trust level of the environment is less than the trust level threshold, the first SIM card is determined to be in an untrusted environment, and the sensitive operation is prevented from being performed. If the trust level of the environment is greater than or equal to the trust level threshold, the first SIM card is determined to be in a trust environment, and the sensitive operation is allowed to be performed.

10. A reliable environment detection method, characterized in that, Applied to mobile terminals, including: After a sensitive operation is initiated through the first SIM card, in response to a control command sent by the server, the identity information of the second SIM card is detected through the first SIM card; the second SIM card is another SIM card located within the detection range of the first SIM card. The server sends the identity information of the second SIM card so that it can determine the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card, and detect whether the first SIM card is in a trusted environment based on the relative position.

11. The method according to claim 10, characterized in that, The step of sending the identity information of the second SIM card includes: Analyze the first random value in the control command; Generate a second random value; The registration information is read from the local machine; the registration information is the registration information reserved by the first SIM card in the server. Based on the first random value and the registration information, a key generation function is selected from the key algorithm pool pre-set in the first SIM card; Based on the second random value and the registration information, a symmetric key algorithm is selected from the key algorithm pool pre-set in the first SIM card; Using the key generation function, a key is generated based on the first random value, the second random value, and the registration information; Using the key and the symmetric key algorithm, the identity information of the second SIM card is encrypted to obtain ciphertext; The second random value and the ciphertext are written into the control response, and the control response is sent to the server.

12. A reliable environment detection device, characterized in that, include: The first transmitting module is used to send control commands in response to sensitive operations initiated by the mobile terminal through the first SIM card; The control command is used to instruct the mobile terminal to detect the identity information of the second SIM card through the first SIM card; The second SIM card is another SIM card located within the detection range of the first SIM card; The first receiving module is used to receive the identity information of the second SIM card; The first detection module is used to determine the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card; and to detect whether the first SIM card is in a trusted environment based on the relative position.

13. A reliable environment detection device, characterized in that, include: The second detection module is used to detect the identity information of the second SIM card through the first SIM card in response to the control command sent by the server after a sensitive operation is initiated through the first SIM card. The second SIM card is another SIM card located within the detection range of the first SIM card; The second sending module is used to send the identity information of the second SIM card, so that the server can determine the relative position of the first SIM card and the second SIM card based on the identity information of the second SIM card, and detect whether the first SIM card is in a trusted environment based on the relative position.

14. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9 or 10-11.

15. A computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-9 or 10-11.

16. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-9 or 10-11.

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