The present invention relates to a DDoS attack detection and mitigation method for an industrial SDN network, and belongs to the field of network security. According to the method, by means of the cooperation between an east-west interface of an SDN controller in an industrial backhaul network and a system manager of an industrial access network, in conjunction with the features of the industrial backhaul network and an industrial access network data packet, a flow entry matching field of an OpenFlow switch is extended, and a flow table 0 is set to be a “flow table dedicated to DDoS attack mitigation” for defending against an attacking data flow in a timely manner. By using the SDN controller of an industrial backhaul network and a DDoS attack detection and mitigation system, an attacking data flow is identified and a DDoS attack source is found, and the policy of mitigating a DDoS attack is implemented by means of scheduling a system manager of the industrial access network. According to the present invention, the normal traffic of an industrial backhaul network and an industrial access network is ensured, and a threat posed by a DDoS attack to the security of an industrial network is overcome.

Authentication processes to counter subscriber identity module swapping fraud attacks is disclosed. A method can comprise receiving location data representative of a tower device of a group of tower devices; receiving duration data representing a time period during which the mobile device has been traversing through a transmission region monitored by the tower device; as a function of the identification data, the location data, and the duration data, formulating a challenge query for the mobile device to answer; and sending the challenge query to the tower device.

Masking a route by determining a first location of a first user, receiving destination data for the first user, generating a plurality of map segments according to the first location and the destination data, presenting a first map segment to a second user, determining a second location of the first user, and presenting a second map segment to the second user according to the second location.

The invention relates to a device/method a tracking and management method for responding to a cyber-attack directed to at least one attacked vehicle of a fleet including a plurality of vehicles, each vehicle comprising an intrusion detection and prevention system (IDPS) configured to track data wirelessly received by said vehicle for identifying the cyber-attack, the method comprising the following steps: identifying the cyber-attack in said at least one attacked vehicle, the identification corresponding to the discovery, by the intrusion detection and prevention system (IDPS) of the at least one attacked vehicle, of at least one piece of malicious data among the wirelessly received data and the definition of a report update that characterizes said at least one piece of malicious data; broadcasting the report update to at least one non-attacked vehicle of the fleet from the at least one attacked vehicle according to a short range communication protocol.

A computer-implemented method of testing whether or not a blockchain transaction is a double spend attempt, the method being performed by a first party and comprising: generating a first blockchain transaction, wherein the first blockchain transaction comprises an input for unlocking an output of a blockchain transaction previously transmitted to one or more nodes of a blockchain network for inclusion in the blockchain; generating a signature based on the first blockchain transaction and one or more time indicators, each time indicator indicating when the first blockchain transaction was generated and/or transmitted to a second party; and transmitting to the second party, the first blockchain transaction, the signature and the one or more time indicators, wherein at least the first blockchain transaction is transmitted to the second party via an off-chain communication channel.

A privacy protection authentication method based on a wireless body area network may be applied to a smart home care system. The method provides an authentication method for two-way authentication and key verification between a device and a cloud server, can ensure identities of the device and the cloud server to be valid and prevent network information security from being affected by external invasion attacks. A physical unclonable function and an elliptic curve cryptography algorithm are introduced to encrypt key data in the authentication process, so that the whole authentication process is in a safe environment, and the security of the authentication process is further improved through adding and removing functions of a third-party identity. The privacy protection authentication protocol method can resist replay attacks and smart card impersonation attacks, the whole authentication process is safe and efficient, and has a high application value in smart home care scenes.

Provided are a method for safely and reliably designing augmented reality (AR) applications on at least one server and at least one augmented reality device connected to each other and a network structure consisting of at least one server and at least one augmented reality device connected to each other. The method proposes a platform for developing and running augmented reality applications. Accordingly, at least two users can use the method to develop an AR application, to modify an AR application or run a ready application. The method prevents information leakage by calling some elements from TEE with asymmetric cryptography and safely operates a reliable system. In this way, the method provides a secure environment since third party access to asymmetric passwords is prevented.

An information processing device, comprising a processor, wherein the processor is configured to: acquire security event information for a vehicle from another information processing device installed in the vehicle; and in cases in which wireless communication with a security center cannot be performed, notify a destination inside the vehicle of at least one of a response instruction, which is predetermined according to the security event information, or the security event information.

A data attack detection system that includes a record host and an orchestration host. The record host stores account information for card holders. The orchestration host includes a switch interface configured to receive transaction information for a card from a network. The orchestration host further includes a velocity trap engine that stores received transaction information for the card in a cardholder file. The velocity trap engine creates entries in a velocity transaction timestamp record for the card when the number of transactions for the card in the cardholder record within a first predetermined time interval exceeds a first activity level threshold. The velocity trap engine discontinues a transaction flow between the orchestration host and the record host for the card when the number of transactions for the card in the velocity transaction timestamp record within a second predetermined time interval exceeds a second activity level threshold.

A data attack detection system that includes a record host and an orchestration host. The record host stores account information for card holders. The orchestration host includes a switch interface configured to receive transaction information for a card from a network. The orchestration host further includes a velocity trap engine that stores received transaction information for the card in a cardholder file. The velocity trap engine creates entries in a velocity transaction timestamp record for the card when the number of transactions for the card in the cardholder record within a first predetermined time interval exceeds a first activity level threshold. The velocity trap engine discontinues a transaction flow between the orchestration host and the record host for the card when the number of transactions for the card in the velocity transaction timestamp record within a second predetermined time interval exceeds a second activity level threshold.