Abstract: Systems and methods are provided for addressing issues caused by interruptions that may occur while operating under the Metro Ethernet Forum (MEF) 35.1 standard. A method, according to one implementation, includes obtaining PM data during a current Measurement Interval of an ongoing PM session in accordance with MEF 35.1. The PM data can be locally stored as a current dataset and reported at the end of the current Measurement Interval for storage in a history database. Following an interruption event that interrupts at least the current Measurement Interval, the method detects a recommencement event that clears the interruption event and allows a PM session to resume. The method further includes determining a number of Measurement Intervals affected by the interruption event based on an end time of a last-reported Measurement Interval and then inserting the number of affected Measurement Intervals into the history database after the last-reported Measurement Interval.

Abstract: Systems and methods are provided for addressing issues caused by interruptions that may occur while operating under the Metro Ethernet Forum (MEF) 35.1 standard. A method, according to one implementation, includes obtaining PM data during a current Measurement Interval of an ongoing PM session in accordance with MEF 35.1. The PM data can be locally stored as a current dataset and reported at the end of the current Measurement Interval for storage in a history database. Following an interruption event that interrupts at least the current Measurement Interval, the method detects a recommencement event that clears the interruption event and allows a PM session to resume. The method further includes determining a number of Measurement Intervals affected by the interruption event based on an end time of a last-reported Measurement Interval and then inserting the number of affected Measurement Intervals into the history database after the last-reported Measurement Interval.

Abstract: A system and a method for detecting fraudulent transactions at a transaction site by analyzing pattern of events associated with one or more transactions are provided. The present invention provides for forming a collection of most probable fraudulent patterns and true patterns associated with one or more transactions, selecting a pattern classification technique, generating a data input from an ongoing transaction that is interpretable by the selected pattern classification technique, and effectively and efficiently categorising ongoing transaction into fraudulent and genuine transactions using selected pattern classification technique. The present invention may be utilized in a variety of applications where discrete time-ordered visual events are associated with a transaction, for example: vehicles detected in relation to a transit point, badge or card swipes from an automated door lock etc., which indicate trespassing, theft and unauthorized access to restricted areas etc.

Abstract: A system and a method for detecting fraudulent transactions at a transaction site by analyzing pattern of events associated with one or more transactions are provided. The present invention provides for forming a collection of most probable fraudulent patterns and true patterns associated with one or more transactions, selecting a pattern classification technique, generating a data input from an ongoing transaction that is interpretable by the selected pattern classification technique, and effectively and efficiently categorising ongoing transaction into fraudulent and genuine transactions using selected pattern classification technique. The present invention may be utilized in a variety of applications where discrete time-ordered visual events are associated with a transaction, for example: vehicles detected in relation to a transit point, badge or card swipes from an automated door lock etc., which indicate trespassing, theft and unauthorized access to restricted areas etc.