Abstract: A method for hierarchical clustering comprises multi-level partitioning of data points into non-overlapping LDFs and formation of sets of such LDFs, wherein original data points may reside in different LDFs. The sets of LDFs are then hierarchically processed into sets of super-LDFs, which are further processed up the hierarchy. In some embodiments, the further processing ends with the construction of a single super-LDF at the root of the hierarchy. The partitioning of the data points and the hierarchical processing of the sets of LDFs and super-LDFs uses respective local affinity matrices.

Abstract: A method for detecting a SQL injection attack comprises a training phase and a detection phase. In the training phase, a plurality of SQL queries is transformed into a respective plurality of SQL token domain queries which are processed using a n-gram analysis to provide a threshold and an averaging vector. In the detection phase, each newly arrived SQL query is transformed into a new SQL token domain query, and the n-gram analysis is applied together with the averaging vector and the threshold to each new SQL token domain query to determine if the new SQL query is normal or abnormal. The detection may be online or offline.

Abstract: A head mounted display (HMD) is worn on a user's head for displaying an image. A HMD is a personal see-through device designed to view still or video images or data that nonetheless permits the user to view his surroundings.