Abstract:
A security device provisioning hub, including: a memory; and a processor configured to: receive a first secret token from a device manufacturer, wherein the first secret token is associated with a first service; receive a second secret token from a customer device having a security chip; verify that the first secret token and the second secret token are the same; and provide to the customer device access credentials to the first service.
Abstract:
A data processing system and a method are provided for recognizing a scanned biometric characteristic in the data processing system. The data processing system includes a biometric sensor, a rich execution environment (REE), and a secure element (SE). In one embodiment, during an enrollment operation, a random challenge is applied to scanned data to produce a biometric template that is stored. During subsequent validation operations, the SE determines if user data includes evidence of the random challenge before providing access to a secure application. Evidence of the random challenge indicates the user data was provided by the biometric sensor. In another embodiment, the sensor data is split between the REE and the SE and partially processed in the SE. The described embodiments prevent a replay attack from being conducted in communications between the REE and the SE.
Abstract:
Articles and methods for transaction irregularity detection are disclosed. In one example, the article discloses: a memory including a record of a last-reported security-device transaction with the security-device, and including a last-reported transaction counter value associated with the last-reported security-device transaction; a previous device identifier; a record of the previous security-device transaction with the security-device, and including the previous device identifier associated with the previous security-device transaction; a record of a current security-device transaction with the security-device, and including a currently-reported transaction counter value associated with the current security-device transaction; and a back-end device tagging the previous device with fraud if the current transaction counter value differs from the last-reported transaction counter value by other than an increment. In one example, the method discloses: a transaction irregularity detection process based on the article.
Abstract:
A data processing system and a method are provided for recognizing a scanned biometric characteristic in the data processing system. The data processing system includes a biometric sensor, a rich execution environment (REE), and a secure element (SE). In one embodiment, during an enrollment operation, a random challenge is applied to scanned data to produce a biometric template that is stored. During subsequent validation operations, the SE determines if user data includes evidence of the random challenge before providing access to a secure application. Evidence of the random challenge indicates the user data was provided by the biometric sensor. In another embodiment, the sensor data is split between the REE and the SE and partially processed in the SE. The described embodiments prevent a replay attack from being conducted in communications between the REE and the SE.
Abstract:
A data processing system and a method are provided for recognizing a scanned biometric characteristic in the data processing system. The data processing system includes a biometric sensor, a rich execution environment (REE), and a secure element (SE). In one embodiment, during an enrollment operation, a random challenge is applied to scanned data to produce a biometric template that is stored. During subsequent validation operations, the SE determines if user data includes evidence of the random challenge before providing access to a secure application. Evidence of the random challenge indicates the user data was provided by the biometric sensor. In another embodiment, the sensor data is split between the REE and the SE and partially processed in the SE. The described embodiments prevent a replay attack from being conducted in communications between the REE and the SE.
Abstract:
A data processing system and a method are provided for recognizing a scanned biometric characteristic in the data processing system. The data processing system includes a biometric sensor, a rich execution environment (REE), and a secure element (SE). In one embodiment, during an enrollment operation, a random challenge is applied to scanned data to produce a biometric template that is stored. During subsequent validation operations, the SE determines if user data includes evidence of the random challenge before providing access to a secure application. Evidence of the random challenge indicates the user data was provided by the biometric sensor. In another embodiment, the sensor data is split between the REE and the SE and partially processed in the SE. The described embodiments prevent a replay attack from being conducted in communications between the REE and the SE.
Abstract:
The exemplary embodiments of the invention realize an efficient prevention of massive infiltration of cloned RFID transponders into existing and new RFID systems. Furthermore, reader devices used for authentication of RFID transponders do not need to be on-line and do not need to be equipped with a Security Authentication Module (SAM). This simplifies authentication procedures and reduces costs. According to an exemplary embodiment of the invention a transponder-specific originality signature is stored by a transponder manufacturer on the transponder. The transponder-specific originality signature may, for example, be stored in the non-volatile memory (EEPROM) of the transponder during the fabrication of the transponder. This transponder-specific originality signature can be checked at any time in a convenient way, which provides an indication of originality of said transponder.
Abstract:
Articles and methods for transaction irregularity detection are disclosed. In one example, the article discloses: a memory including a record of a last-reported security-device transaction with the security-device, and including a last-reported transaction counter value associated with the last-reported security-device transaction; a previous device identifier; a record of the previous security-device transaction with the security-device, and including the previous device identifier associated with the previous security-device transaction; a record of a current security-device transaction with the security-device, and including a currently-reported transaction counter value associated with the current security-device transaction; and a back-end device tagging the previous device with fraud if the current transaction counter value differs from the last-reported transaction counter value by other than an increment. In one example, the method discloses: a transaction irregularity detection process based on the article.
Abstract:
The exemplary embodiments of the invention realize an efficient prevention of massive infiltration of cloned RFID transponders into existing and new RFID systems. Furthermore, reader devices used for authentication of RFID transponders do not need to be on-line and do not need to be equipped with a Security Authentication Module (SAM). This simplifies authentication procedures and reduces costs. According to an exemplary embodiment of the invention a transponder-specific originality signature is stored by a transponder manufacturer on the transponder. The transponder-specific originality signature may, for example, be stored in the non-volatile memory (EEPROM) of the transponder during the fabrication of the transponder. This transponder-specific originality signature can be checked at any time in a convenient way, which provides an indication of originality of said transponder.