Abstract: In method of protecting signaling messages in a hop-by-hop network communication link between a source node and a destination node, a source node public digital signature verification key and a respective source node private digital signature key associated with said public digital signature verification key are provided to the source node. The source node public digital signature verification key associated with the source node private digital signature key is also provided to the destination node. The source node builds a message including a sequence of Information Elements, and calculates, for each Information Element, an Information Element hash value. The source node also calculates a sequence hash value of a concatenation of the calculated Information Element hash values, and generates a source node digital signature by digitally signing the calculated sequence hash value. An intermediate node receives and forwards the signaling message to the destination node.

Abstract: In method of protecting signaling messages in a hop-by-hop network communication link between a source node and a destination node, a source node public digital signature verification key and a respective source node private digital signature key associated with said public digital signature verification key are provided to the source node. The source node public digital signature verification key associated with the source node private digital signature key is also provided to the destination node. The source node builds a message including a sequence of Information Elements, and calculates, for each Information Element, an Information Element hash value. The source node also calculates a sequence hash value of a concatenation of the calculated Information Element hash values, and generates a source node digital signature by digitally signing the calculated sequence hash value. An intermediate node receives and forwards the signaling message to the destination node.

Abstract: A method of detecting anomalies in a communication system, includes: providing a first packet flow portion and a second packet flow portion; extracting samples of a numerical feature associated with a traffic status of the first and second packet flow portions; computing from said extracted samples a first statistical dispersion quantity and a second statistical dispersion quantity of the numerical feature associated with the first and second packet flow portions, respectively; computing from the dispersion quantities a variation quantity representing a dispersion change from the first packet flow portion to the second packet flow portion; comparing the variation quantity with a comparison value; and detecting an anomaly in the system in response to said comparison.

Abstract: An automatic biometric identification method based on face recognition and support vector machines, includes enrolling a user to generate a user's reference template; and identifying the user based on the user's reference template, wherein generating a user's reference template includes acquiring a number of user's face images, and training a one-class support vector machine based on the user's face images only.

Abstract: A user authentication method based on the use of identification biometric techniques, including the steps of generating a reference biometric template from a first biometric image of a user to be authenticated; splitting the reference biometric template into a first and a second reference biometric template portion that can be physically separated; signing and enciphering the first and the second reference biometric template portion; storing the signed and enciphered first and second reference biometric template portion into different memories.

Abstract: A method of detecting anomalies in a communication system, includes: providing a first packet flow portion and a second packet flow portion; extracting samples of a numerical feature associated with a traffic status of the first and second packet flow portions; computing from said extracted samples a first statistical dispersion quantity and a second statistical dispersion quantity of the numerical feature associated with the first and second packet flow portions, respectively; computing from the dispersion quantities a variation quantity representing a dispersion change from the first packet flow portion to the second packet flow portion; comparing the variation quantity with a comparison value; and detecting an anomaly in the system in response to said comparison.

Abstract: An automatic biometric identification method based on face recognition and support vector machines, includes enrolling a user to generate a user's reference template; and identifying the user based on the user's reference template, wherein generating a user's reference template includes acquiring a number of user's face images, and training a one-class support vector machine based on the user's face images only.

Abstract: A user authentication method based on the use of identification biometric techniques, including the steps of generating a reference biometric template from a first biometric image of a user to be authenticated; splitting the reference biometric template into a first and a second reference biometric template portion that can be physically separated; signing and enciphering the first and the second reference biometric template portion; storing the signed and enciphered first and second reference biometric template portion into different memories.

Abstract: Apparatus for monitoring operation of a processing system includes a set of modules for monitoring operation of a set of system primitives that allocate or release the system resources and are used by different processes running on the system. Preferably, the modules include at least one application knowledge module tracking the processes running on the system and monitoring the resources used thereby, a network knowledge module monitoring connections by the processes running on the system, a file-system analysis module monitoring the file-related operations performed within the system, and a device monitoring module monitoring operation of commonly used modules with the system. A preferred field of application is in host-based intrusion detection systems.