46 results about "Information privacy" patented technology

The invention provides a privacy protection multi-task allocation method for an unmanned aerial vehicle crowdsourcing perception system, which combines addition secret sharing and homomorphic encryption to realize bilateral privacy protection of a task side and an unmanned aerial vehicle position. The task requester and the working party split a task position and a UAV departure position into two secret shares [.] 1 and [.] 2 by adopting an additive secret sharing mechanism respectively, and send the two secret shares [.] 1 and [.] 2 to the two independent service parties S1 and S2 respectively; the service party calculates an encrypted square Euclidean distance between the UAV and the task based on the shared share, and generates two distance matrix shares D1 and D2. On the basis, the two service parties cooperatively execute privacy comparison and a minimum index protocol under the optimized Paillier, and multi-task encryption shortest path distribution is realized in combination with a Hungary algorithm. According to the method, addition secret sharing is fused, Paillier encryption and task matching optimization are optimized, the total flight path of the UAV is remarkably reduced while position information privacy of the whole task allocation process is guaranteed, and good safety and deployability are achieved.

The invention relates to a supply chain management method, in particular to a circulation box full life cycle management method and system based on a block chain and a program product. According to the method, logistics event information is collected and layered splitting is carried out, three parallel block chains including a logistics main chain, a carbon evaluation side chain and a prediction side chain are constructed, cross-chain atomic writing is realized in combination with two-stage submission and BLS aggregation signature, the residual life and path of a circulation box are predicted by using a digital twin model, and a carbon quota is dynamically allocated through deep reinforcement learning, so that the residual life and path of the circulation box are predicted. And finally, the position information privacy is protected by means of zero-knowledge proof. The circulation efficiency of the circulation box, the carbon emission reduction transparency and the system safety are remarkably improved.

The invention belongs to the technical field of block chain ERP (Enterprise Resource Planning), and discloses an enterprise ERP management system based on a block chain, which realizes credible sharing through an alliance chain architecture of a block chain base layer, ensures sensitive information privacy through a zero-knowledge proof technology, and can establish cooperative trust without endorsement of a third-party mechanism; the intelligent contract of the supply chain cooperation unit automatically executes cooperation rules such as purchase and acceptance, and trust disputes caused by manual intervention are avoided; the intelligent contract engine drives the unit processes of supply chain, production, finance and the like to be automated, so that end-to-end linkage of purchase-production-finance is realized, and manual operation links are reduced; the dynamic contract updating function enables the enterprise to quickly adapt to the business rule change, and the online period of a new business scene is shortened; the digital twinborn technology of the production management unit is fused with the AI model of the data analysis center, so that the decision accuracy of production scheduling and inventory management is improved, the resource configuration is optimized, and the problems of solidified process and slow response of the traditional ERP (Enterprise Resource Planning) are solved.

The invention discloses a federated learning privacy protection and attack defense method, which relates to the technical field of artificial intelligence and information privacy security crossing, and comprises the following steps: a client performs training based on local data and generates update, dynamically allocates privacy budget by evaluating the contribution degree of each network layer to model performance, and finally performs privacy protection and attack defense. The method comprises the following steps: reducing noise at a key layer to retain the utility of a model, enhancing disturbance at a non-key layer to improve privacy protection, uploading an update after noise addition to a server, predicting an update to be submitted by a client based on a historical training process by the server, calculating a deviation value between an actual update and a predicted update, and constructing a behavior evaluation value by combining multiple rounds of deviations. The method comprises the following steps: identifying and isolating abnormal clients by utilizing clustering analysis, dividing normal clients into fixed groups for intra-group aggregation, periodically executing global aggregation to update a model, starting an intra-group recovery mechanism when abnormality is detected, and performing local retraining and reconstruction aggregation output by the normal clients in the same group, thereby realizing safe and efficient federated learning.

The present application provides a vehicle-road cooperative voice interaction system, comprising: at least one set of first directional sound-transmitting and receiving devices arranged along the lanes for covering at least one lane, forming directional sound coverage of a section of the lane as a coverage area; the vehicle is equipped with a second directional sound-transmitting and receiving device; wherein the first directional sound-transmitting and receiving device and the second directional sound-transmitting and receiving device are arranged opposite to each other; if it is detected that the vehicle is about to enter the coverage area, the first and second directional sound-transmitting and receiving devices are turned on in advance to form directional sound communication between the first directional sound-transmitting and receiving device and the second directional sound-transmitting and receiving device, thereby completing the directional transmission and reception of sound information of vehicle-road cooperation; the present application breaks through the limitation that there is no direct audio information communication between roads and vehicles, and the relevant management departments cannot obtain the information in the vehicle in the first time, and the vehicle cannot obtain the latest road information in the first time, thereby realizing vehicle-road cooperative communication to the greatest extent; the present application also breaks through the barrier of sound isolation caused by the good sealing of the vehicle to ensure information privacy.

The invention discloses an energy sharing mutual aid benefit balanced distribution mechanism among multiple micro-energy networks, which belongs to the field of multi-micro-energy network system operation scheduling, and comprises the following steps: S1, dividing micro-energy network groups and combined pairing according to a matching index of a comprehensive curve form and a distance of micro-energy network source and load data, and constructing a micro-energy network benefit objective function; s2, introducing contribution, cost and risk factors into a traditional Shapley value method model, and constructing an improved Shapley value method model; and S3, performing distributed optimization solution on the micro-energy network cooperation alliance based on an ADMM algorithm, and realizing benefit balanced distribution by adopting a cooperation game strategy of an improved Shapley value method model. According to the method, the interaction efficiency is improved by dividing the group through source load matching, the information privacy is protected by using the ADMM algorithm, fair distribution is realized by improving the Shapley value method model, and the method is suitable for collaborative optimization operation of a multi-micro energy network system.

The invention belongs to the field of artificial intelligence security, and discloses a physical multi-scene figure information privacy protection method based on image disturbance shielding, which comprises a target figure image privacy protection module and a target figure anti-identification module. The target person image privacy protection module generates robust global disturbance according to a target person image release scene, and prevents an image from being identified by an artificial intelligence model after being maliciously acquired; and the target person anti-recognition module adds disturbance cheating to specific glasses selected by the target person, so that the target person cannot be correctly recognized by the artificial intelligence model. According to the method, efficient protection of the person information privacy is successfully realized, the method has relatively high attack resistance and practical application value, the technical level of personal privacy protection is remarkably improved, and an innovative solution and a practical direction are provided for the fields of information security and privacy protection.

The invention discloses an access control encryption and decryption method and system based on content detection, and belongs to the technical field of cryptography, and the method comprises the following steps: initializing a global parameter and a main private key by an access control strategy and a security parameter input by a central authority, and generating a trap door; and sending the main private key to a sender authority to generate an encryption key for the sender. And the sender encrypts the information by using the encryption key, and then sends a ciphertext to the purifier. And the purifier purifies the ciphertext, and broadcasts the purified ciphertext to all receivers. Except a sender and a receiver which conform to an access control strategy, corresponding information cannot be transmitted and received through the method. According to the scheme, through cooperation and cooperation of all participants, on the basis of ensuring sensitive information supervision efficiency, encrypted transmission and identity verification of user information are achieved, sensitive information and identity information privacy of users are fully protected, and therefore the technical problem that in the prior art, a stealing risk exists in sensitive information transmission and storage is solved.

The invention relates to the technical field of virtual power plants, in particular to a virtual power plant multi-class power resource collaborative clearing method considering uncertainty, and the method comprises the steps: constructing a hierarchical interaction architecture of a virtual power plant and a power grid for multi-class power resources provided by the virtual power plant for the operation of the power grid; constructing a virtual power plant operation model by taking an energy storage operation constraint, a micro gas turbine operation constraint, an electric energy transaction constraint, an electric power balance constraint and a multi-class electric power resource balance constraint as constraint conditions and taking minimization of the operation cost of the virtual power plant as a target; establishing a multi-virtual power plant multi-class power resource collaborative clearing optimization model; aiming at uncertainty of new energy output, introducing distribution robust opportunity constraints, and constructing a virtual power plant multi-class power resource distribution robust collaborative clearing optimization model; and considering information privacy of each main body and energy and information interaction among a plurality of virtual power plants, proposing a distributed solution algorithm fusing a bisection method and an alternating direction multiplier method, and solving the collaborative clearing optimization model.

The invention belongs to the technical field of coal mine safety authentication, and discloses a coal mine safety terminal mixed identification authentication system based on a private block chain, which uses the private block chain and a hierarchical consensus architecture, combines a PBFT and PoS mixed algorithm to distribute node differentiation weights, and gives a consensus verification negative right to a supervision node. The monitoring requirement is met while the decentralization characteristic is guaranteed, and dependence on a single central server is not needed any more; even if part of nodes break down or are attacked, the fog node self-organizing network can take over tasks quickly, authentication interruption of the whole system is avoided, and the high requirement for zero interruption of coal mine production is met. Meanwhile, a terminal full-life-cycle tracing chain is constructed by utilizing the characteristic that data on the chain cannot be tampered and a cross-chain hash synchronization technology, and a zero-knowledge proof and differential privacy algorithm is matched, so that authentication data is prevented from being tampered, sensitive information privacy can be protected, and responsibility tracing difficulty is reduced.

The invention provides a patient information privacy protection method for a sharing system of a three-dimensional physical examination system, belongs to the technical field of data processing, and is used for effectively balancing the requirements of privacy protection and data sharing. The method comprises the steps that the electronic equipment obtains physical examination information of a patient, the physical examination information comprises a first type of target physical examination information, a second type of target physical examination information and a third type of target physical examination information, and the privacy protection priority of the first type of target physical examination information is higher than that of the second type of target physical examination information; the electronic equipment executes first security processing on the first type of target physical examination information to obtain first type of target hidden information, and the electronic equipment executes second security processing on the second type of target physical examination information to obtain second type of target hidden information; and the electronic equipment stores the first type of target hidden information, the second type of target hidden information and the third type of target physical examination information into a three-dimensional physical examination system sharing system.

The application discloses a face image privacy protection method based on attention and a generative adversarial network, comprising the following steps: step one, constructing a self-attention perception generative network; step two, constructing a spatial attention guide discriminant network; step three, determining an attention-generative adversarial network optimization objective function; and step four, training the attention-generative adversarial network and outputting a final result. The application can improve the utility of the de-identified face image by retaining more abundant details of the de-identified face image, generate a high-fidelity de-identified face image, and ensure that the privacy attribute cannot be detected and the user's personal information privacy cannot be leaked.

This application provides a method for protecting patient information privacy in a three-dimensional physical examination system sharing system, belonging to the field of data processing technology, to effectively balance the needs of privacy protection and data sharing. The method includes: an electronic device acquiring a patient's physical examination information, which includes first-type target physical examination information, second-type target physical examination information, and third-type target physical examination information, with the privacy protection priority of the first-type target physical examination information being higher than that of the second-type target physical examination information; the electronic device performing a first security processing on the first-type target physical examination information to obtain first-type hidden target information, and the electronic device performing a second security processing on the second-type target physical examination information to obtain second-type hidden target information; and the electronic device storing the first-type hidden target information, the second-type hidden target information, and the third-type target physical examination information in the three-dimensional physical examination system sharing system.

The present disclosure relates to a system to proactively detect in real time one or more threats in crowded areas. The present disclosure presents a proactive system for real-time threat detection in crowded areas. Utilizing a network of imaging sensors and advanced machine learning algorithms, the system identifies suspicious individuals, objects, and behavioral patterns within a predefined area. The system detects potential threats such as individuals on watch lists, suspicious objects like unattended bags, and abnormal behaviors indicative of security risks, by continuously monitoring and analyzing images and video feeds. Upon detection, the system promptly notifies authorities, providing detailed information on threat location, suspected individuals, and behavioral analysis. Privacy-preserving measures, including encryption of facial recognition data, ensure compliance with privacy regulations. The present disclosure offers a scalable, efficient, and automated solution to enhance security measures, reduce response times, and safeguard public safety in dynamic urban environments.

This invention discloses a personalized location trajectory privacy protection method based on mutual information, belonging to the field of crowdsourced sensing technology. It includes: Step 1: Data preprocessing; Step 2: After generating the Markov matrix in Step 1, the matrix is ​​normalized, and a location privacy protection mechanism is established by setting a distortion threshold and regularization parameters; Step 3: Measuring the effectiveness of location privacy protection. This method generates a Markov transition matrix by merging user location trajectory data, analyzes implicit privacy information and adds distortion perturbations, and uses mutual information to measure the degree of privacy leakage, achieving a trade-off between privacy and usability. It solves the problem that existing technologies cannot effectively overcome the risk of location information privacy leakage.

The present disclosure relates to a system to proactively detect in real time one or more threats in crowded areas. The present disclosure presents a proactive system for real-time threat detection in crowded areas. Utilizing a network of imaging sensors and advanced machine learning algorithms, the system identifies suspicious individuals, objects, and behavioral patterns within a predefined area. The system detects potential threats such as individuals on watch lists, suspicious objects like unattended bags, and abnormal behaviors indicative of security risks, by continuously monitoring and analyzing images and video feeds. Upon detection, the system promptly notifies authorities, providing detailed information on threat location, suspected individuals, and behavioral analysis. Privacy-preserving measures, including encryption of facial recognition data, ensure compliance with privacy regulations. The present disclosure offers a scalable, efficient, and automated solution to enhance security measures, reduce response times, and safeguard public safety in dynamic urban environments.

The invention provides a multi-time-sequence integrated energy system control optimization method considering autonomy and collaboration. According to the method, through collaborative optimization of an IMES system operator and autonomous optimization of each MES superior coordinator, economic mutual aid is realized on the premise of ensuring the operation right and information privacy of each MES, the collaborative planning problem among multiple energy systems is effectively solved, and the efficient scheduling and dynamic adaptive capacity of the systems is improved. The power consumption cost minimization under different time scales is used as a target function, the consideration of factors such as the uncertainty of energy supply and demand response is realized, the economy and reliability of the system are improved, the peak load demand and the overall energy consumption are effectively reduced by the system autonomous adjustment and collaborative optimization mechanism, and the energy-saving and consumption-reducing effects are remarkable.

This invention discloses a method and apparatus for analyzing low-frequency oscillations in a converter-synchronous machine hybrid power supply system, belonging to the field of power system transmission and distribution technology. The method includes: establishing a linearized model of the entire hybrid power supply system under small disturbances; establishing a port impedance model of the converter and an impedance model of the power network, as well as an external port impedance model of the synchronous machine considering the embedded internal impedance of the converter and a damping torque model of the synchronous machine; constructing a damping torque stability criterion based on the external port impedance matrix of the synchronous machine; analyzing the influence of the converter's dynamic characteristics on the phase shift of the main and auxiliary diagonal elements of the external port impedance model of the synchronous machine, and deriving the key factors inducing low-frequency oscillations in the converter-synchronous machine hybrid power supply system. This invention achieves a unified analysis framework independent of specific converter control strategies, effectively protecting the information privacy of both the power grid dispatching department and the converter operator, and providing guidance for suppressing low-frequency oscillations in converter-synchronous machine hybrid power supply systems.

The invention provides a federal learning-based stock position privacy protection risk scene simulation system and method. The system comprises a terminal side position data processing module which is used for acquiring and processing local user position data; the risk scene parameter model module is used for providing a parameterized risk scene generation model; the federation training and synchronization module is used for calculating update information for optimizing the risk scene generation model based on the local user position data; the privacy protection and security aggregation module is used for performing privacy protection processing on the update information; the terminal side Monte Carlo simulation engine module is used for simulating a user position combination based on the updated risk scene parameter model and outputting a risk distribution result; the aggregation service module is used for receiving update information uploaded by a plurality of client terminal devices and performing aggregation operation to generate model parameters of the updated risk scene generation model; and the parameter version management module is used for storing, managing and distributing the updated model parameters of the risk scene generation model.

The invention discloses a digital copyright protection-oriented multi-party collaborative certificateless mimicry signature method, which integrates secure multi-party computation (MPC) and a threshold symmetric encryption mechanism, and avoids the key leakage risk and single-point fault problems caused by centralized storage by cooperatively generating and managing a key through a plurality of committee nodes. In the signature generation stage, a mimicry signature structure is utilized, and the copyright identifier is hidden and embedded through a random number redundant space, so that the signature and the copyright identifier are organically fused without influencing the verification correctness. In the copyright traceability stage, the copyright identifier can be reconstructed only by recovering the random number embedded in the signature through multi-party cooperation, and the secret key is not leaked or the signature security is not damaged in the recovery process, so that the safe and reliable traceability of the digital copyright is ensured. The method has signature verifiability, information privacy protection and copyright traceability, and can provide safe and credible technical support in digital work right confirmation, authorization tracking and responsibility tracing.

The invention provides an information desensitization recovery method, an end-cloud cooperation system, a device and electronic equipment, and relates to the technical field of data processing, data to be processed are input into a pre-trained encoder for information separation, desensitization features and sensitive features are obtained, the limitation of an existing static sensitive information list on application fields and data types is broken through, and the data processing efficiency is improved. The sensitive information can be dynamically identified and separated without depending on a predefined sensitive field, so that the information privacy in a data reasoning process is effectively improved; meanwhile, after the desensitization features are input into the preset data processing model to obtain the first reasoning result, the first reasoning result and the sensitive features are fused through the pre-trained decoder to obtain the target reasoning result, the problem that information is lost in the reasoning process due to the fact that the sensitive information is filtered is avoided, the sensitive information needed by reasoning is supplemented, and the reasoning accuracy is improved. Therefore, the accuracy of the model reasoning result is improved.

The present invention discloses a system and method for protecting the privacy of input information based on secure two-party computing, which relates to the field of privacy security. The system includes: a secure two-party computing protocol module, which provides secret sharing technology. The client includes an information input module, which uses secret sharing technology to convert the received input data into two shares of data in the form of additive secret sharing; and also includes a user corpus module, which receives one of the shares of data in the form of additive secret sharing. The private server includes an intelligent association algorithm module and a first prediction model. The intelligent association algorithm module receives the other share of data in the form of additive secret sharing, and obtains a first prediction result, i.e., a first ciphertext prediction result, by calculating the first prediction model; the third-party public cloud server receives the first ciphertext prediction result, reconstructs the first plaintext prediction result, and then sends it to the client.

The invention discloses a decentralized anonymous certificate management and privacy protection verification method, which is characterized in that a certificate issuing request and privacy parameters are sent to a target certificate issuing mechanism through a certificate subject, the certificate issuing request comprises a VRF public key and subject information of the certificate subject, and the privacy parameters comprise subject privacy information; after the target certificate issuing mechanism verifies the subject privacy information and the subject information, a target anonymous certificate is generated according to a preset certificate template, the VRF public key of the certificate subject and the privacy parameters; aggregating sub-signatures generated by a plurality of second certificate issuing mechanisms for the target anonymous certificate to obtain an aggregated signature, and generating a target threshold signature according to the aggregated signature; and storing the target anonymous certificate and the target threshold signature, and sending storage information to the certificate body. According to the invention, through decentralized key generation, the certificate issuing and management right is dispersed to a plurality of certificate issuing mechanisms by using a threshold signature method, so that the risk of single-point failure of the certificate issuing mechanisms is eliminated.

The invention belongs to the technical field of information, and relates to a DNS security policy data distribution method and system. The method comprises the following steps: generating a DNS security policy data set by a DNS security policy data server, wherein the DNS security policy data set comprises a threat information list, RPZ format response policy data and DNS threat Bloom filter vector data; a data distribution link is established between the DNS security policy data server and the analyzer executing the security policy; and the DNS security policy data server carries out data synchronization on the DNS security policy data set to the parser executing the security policy through the data distribution link. According to the method, data distribution synchronization is completed without depending on a DNS protocol, the method is suitable for various data types, the data on the DNS security policy data server can be automatically distributed to the resolver executing the security policy after being updated, the management efficiency is improved, and security threats can be quickly responded; the transmitted DNS threat Bloom vector can improve the data transmission efficiency, enhance the data synchronization information privacy protection and improve the threat disposal efficiency.

The invention discloses a management method and device based on an ip phone address book management platform, and relates to the technical field of information management. When a request for checking address book information is received, the authority level of a requester is identified, preliminary desensitization is executed, and whether secondary desensitization is needed or not is judged according to a desensitization disorder score. If yes, a field semantic path diagram is constructed, structural disturbance and semantic scattering are carried out, and secondary desensitization is achieved; and judging whether the secondary desensitization succeeds or not based on the desensitization intensity score, and if the secondary desensitization succeeds, returning the desensitized address book information to the requester for display, thereby realizing IP phone address book management. By means of the mode, the desensitization quality of the address book information can be evaluated, whether secondary desensitization needs to be carried out or not is judged, if yes, secondary desensitization is carried out, the potential privacy leakage risk of the address book information subjected to secondary desensitization is reduced, and the risk of privacy leakage of the address book information of enterprises or organizations is reduced.

The invention provides an electric power emergency operation and maintenance information pushing system based on AR and federated learning, and relates to the technical field of electric power operation and maintenance, and the system comprises an AR terminal, an edge end and a cloud server end. A sensor module of the AR terminal collects equipment operation state data and environment data, and a local lightweight processing module performs primary processing on the data and sends the processed data to an edge end; the equipment health fingerprint generation module of the edge end performs secondary processing on the primary equipment health fingerprint information, and sends the processed primary equipment health fingerprint information to the cloud server; an anomaly detection and decision-making module of the cloud server performs anomaly diagnosis on the health fingerprint information of the secondary equipment, generates operation and maintenance decision-making information in combination with a knowledge base and sends the operation and maintenance decision-making information to an edge end; the SLAM space positioning module carries out positioning and map construction based on the collected visual information; and the AR rendering engine superposes the operation and maintenance decision information to an AR view field domain of the operation and maintenance personnel to realize dynamic operation guidance and warning. According to the scheme, the data transmission pressure can be reduced, and the information privacy protection level is improved.

The application discloses a kind of edible agricultural products traceability and supply chain management system, the present application relates to agricultural product supply chain informatization and data credible management technical field, including: data acquisition and authentication module, for from the multiple terminal equipment deployed in agricultural product production end Multimodal source data acquisition, and the identity authentication of production subject, the multimodal source data includes environmental sensing data, operation event data and key node image data.The edible agricultural products traceability and supply chain management system, the adaptability of model to diversified production scene and unknown abnormality is improved, realizes from production to the whole process coherent depiction and visual analysis of sale, via independent double engine verification and consensus mechanism processing data, cross-chain storage is authenticated after through oracle network, while guaranteeing sensitive information privacy, ensure the consistency and public credibility of traceability information in complex cooperation network.

This invention discloses a layered adaptive network intrusion prevention system and method for resource-constrained edge computing scenarios, comprising: an edge rapid perception layer that collects multimodal data, quickly screens it, and generates structured natural language descriptions; an edge intelligent judgment layer that receives the structured natural language descriptions, performs semantic reasoning through a dynamically fine-tuned large-scale language model, and outputs threat judgment results; a fog-layer regional collaborative aggregation layer that acquires de-identified information generated from the threat judgment results, performs privacy-preserving aggregation and correlation analysis, and outputs regional threat reports and high-value samples; and a cloud-based cognition and evolution layer that generates synthetic threat data based on high-value samples, performs quality control screening, fine-tunes the screened data to obtain new adapters, and distributes them to the edge intelligent judgment layer. This invention achieves adaptive detection, privacy protection, and continuous evolution in resource-constrained environments, improving the defense capability against unknown attacks.

The application discloses a mobile phone information privacy protection method and system based on big data analysis, relates to the technical field of information security, and comprises the following steps: collecting the latest privacy protection requirements from an application market and / or a regulatory department, and extracting privacy protection clauses to generate a standardized privacy protection rule dataset; after obtaining an encryption analysis result, combining big data analysis to generate a dynamic privacy protection rule file; parsing the bytecode of a mobile phone application through an ASM framework for the dynamic privacy protection rule file, automatically modifying sensitive API calling points, and inserting privacy monitoring logic; repackaging the modified sensitive API calling points into an APK file, and verifying the privacy monitoring of the application program; and the application adopts encryption analysis and distributed training to ensure the safe sharing and processing of privacy data under the participation of multiple parties, effectively enhances the protection of mobile phone information privacy, and is suitable for complex and changeable application scenarios.

A user equipment of a wireless communication system according to an embodiment is provided. The user equipment is configured for generating an emergency context for the user equipment, such that the emergency context comprises first information and further information. Moreover, the user equipment is configured for transmitting the emergency context to another entity of the wireless communication system for making the emergency context in case of an emergency situation available at the other entity of the wireless communication system. The first information of the emergency context comprises at least one of: an information to distinguish an emergency SMS from a standard SMS, a location of the user equipment, a time when the location of the user equipment has been determined, an actual time of the user equipment, an actual date of the user equipment. The further information of the emergency context comprises at least one of: user-specific information comprising information on a user or a state of the user of the user equipment, device-specific information comprising information on the user equipment, environment-specific information comprising information on an environment in which the user equipment is located, privacy information comprising privacy settings that shall apply in case of an emergency, emergency transmission information comprising information for transmitting data in an emergency situation, an emergency message. The further information of the emergency context is different from the location of the user equipment, and is different from the time when the location of the user equipment has been determined, and is different from the actual time and the actual date of the user equipment.