Abstract: A method for providing security to a network having a data stream with a plurality of portions of data, each having differing levels of sensitivity. The data stream is interrogated to determine the presence of predetermined characteristics associated with at least one of the portions of data within the data stream. At least one of the portions of data is then characterized, based upon the portion of data exhibiting a predetermined combination of characteristics, wherein the predetermined combination of characteristics is related to the sensitivity of the portion of data. The portions of the data stream are then distributed into a plurality of different channels, each of the channels associated with different level of sensitivity.

Abstract: Aspects of the present invention encompass methods and systems for detecting abnormal digital traffic by assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes include a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value includes a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic.

Abstract: Computer-processable communication authentication and validation methods and apparatuses are described according to various embodiments. In one embodiment, an authentication and validation method comprises encapsulating an untrusted payload with a header and an authenticator. The header can comprise a unique identifier and the authenticator can comprise at least a portion of a keyed-hash message authentication (HMAC) value based on the content of the header, the content of the payload, and a unique key maintained for each of one or more receiving devices.

Abstract: A method for providing security to a network having a data stream with a plurality of portions of data, each having differing levels of sensitivity. The data stream is interrogated to determine the presence of predetermined characteristics associated with at least one of the portions of data within the data stream. At least one of the portions of data is then characterized, based upon the portion of data exhibiting a predetermined combination of characteristics, wherein the predetermined combination of characteristics is related to the sensitivity of the portion of data. The portions of the data stream are then distributed into a plurality of different channels, each of the channels associated with different level of sensitivity.

Abstract: Embodiments encompassing methods and systems for detecting abnormal digital traffic are disclosed. The method comprises the steps of assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes comprise a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value comprises a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic. The system comprises sensors to detect network events, a program on a computer-readable medium, and a processing device to execute the program,.wherein a network behavior comprises at least one network event.