Abstract: Various embodiments of a method and system for detecting unauthorized signatures to or from a local network. Multiple sensors are connected at an internetworking device, which can be a router or a switch. The sensors operate in parallel and each receives a portion of traffic through the internetworking device, at a session-based level or at a lower (packet-based) level. Depending on the type of internetworking device (router or switch) the load balancing mechanism that distributes the packets can be internal or external to the internetworking device. Also depending on the level of packet distribution (session-based or packet-based), the sensors share a network analyzer (if session-based) or both a network analyzer and a session analyzer (if packet-based).

Abstract: In one aspect of the invention, a computer implemented method for rules-driven multi-phase network vulnerability assessment is disclosed. The method comprises pinging devices on a network to discover devices with a connection to the network. Port scans are performed on the discovered devices and banners are collected. Information from the collected banners are stored as entries in a first database. Analysis is performed on the entries by comparing the entries with a rule set to determine potential vulnerabilities. The results of the analysis are stored in a second database.

Abstract: A system and method are disclosed for real-time insertion of data into a multi-dimensional database. The system includes a multi-dimensional database and a user interface operable to access and provide views into the multi-dimensional database. A data insertion engine is coupled to and operable to access the multi-dimensional database. The data insertion engine is further operable to receive and process a real-time data feed and to insert data into the multi-dimensional database responsive to processing of the real-time data feed. In one embodiment, the real-time data feed can represent exploited network vulnerabilities, and the system can be used for network intrusion detection and vulnerability assessment. The method includes receiving a real-time data feed representing detection of an event and processing the event against the multi-dimensional database. Cells associated with the event are identified in the multi-dimensional database and appropriate vectors to the identified cells are created.