Abstract: Methods and systems can reduce the spread of computer files or data on a network by obtaining and tracking times of arrival for chunks of data transmitted on the network. The times of arrival for a node can be transformed into time-series and periodograms computed from the time-series. Successive periodograms can be compared to determine changes in the strongest peaks of the periodograms. If a new peak is identified, a search for the occurrence of the peak in previous periodograms can be conducted. If no peak having a matching frequency is found, a search for the peak in the periodograms for neighboring nodes can be performed. If matching peaks are found, the associated data stream can be classified. Predictions of the timing and length of associated data packets can be used to randomly interrupt transmission of associated data packets resulting in reducing the spread of the classified data stream.

Abstract: Methods and systems can reduce the spread of computer files or data on a network by obtaining and tracking times of arrival for chunks of data transmitted on the network. The times of arrival for a node can be transformed into time-series and periodograms computed from the time-series. Successive periodograms can be compared to determine changes in the strongest peaks of the periodograms. If a new peak is identified, a search for the occurrence of the peak in previous periodograms can be conducted. If no peak having a matching frequency is found, a search for the peak in the periodograms for neighboring nodes can be performed. If matching peaks are found, the associated data stream can be classified. Predictions of the timing and length of associated data packets can be used to randomly interrupt transmission of associated data packets resulting in reducing the spread of the classified data stream.

Abstract: A system processes communication signals in a network [100, 200]. The system may obtain time of arrival information for chunks of data in the network and construct a signal [410, 420] to represent the time of arrival information. The signal may consist of data that is non-uniformly spaced. The system may process the signal using a Lomb technique to obtain periodicity information [600, 800] about the signal.

Abstract: A system processes communication signals in a network [100, 200]. The system may obtain time of arrival information for chunks of data in the network and construct a signal [410, 420] represent the time of arrival information. The signal may consist of data that is non-uniformly spaced. The system may process the signal using a Lomb technique to obtain periodicity information [600, 800] about the signal.

Abstract: A method analyzing communication in a network [100, 200] may include obtaining time of arrival information for chunks of data in the network. A number of signals [410-460] may be constructed to represent the time of arrival information at respective nodes in the network. A pair of the number of signals may be processed to obtain similarity information [610-660, 710-760] about data flow between a corresponding pair of nodes. Data flow between the pair of nodes may be analyzed using the cross spectral density or coherence information.