Abstract: A method and apparatus for botnet analysis and visualization. Network traffic is filtered to compile a list of messages. The identified messages are tokenized, classified, and aggregated and changes in the frequency of tokenized messages are identified. A display of the tokenized messages is generated and displayed via a user interface. The user interface is configured to a allow a user to review data generated based on the filtered network traffic in order to detect potential botnet activity. User input may be used to adjust filtering and tokenization of the messages.

Abstract: A method and apparatus for botnet analysis and visualization. Network traffic is filtered to compile a list of messages. The identified messages are tokenized, classified, and aggregated and changes in the frequency of tokenized messages are identified. A display of the tokenized messages is generated and displayed via a user interface. The user interface is configured to a allow a user to review data generated based on the filtered network traffic in order to detect potential botnet activity. User input may be used to adjust filtering and tokenization of the messages.

Abstract: A method, a processing device, and a machine-readable medium are provided for improving speech processing. A transcript associated with the speech processing may be displayed to a user with a first visual indication of words having a confidence level within a first predetermined confidence range. An error correction facility may be provided for the user to correct errors in the displayed transcript. Error correction information, collected from use of the error correction facility, may be provided to a speech processing module to improve speech processing accuracy.