Disclosed are various embodiments for searching encrypted data stores. A first computing device can send a message authentication code (MAC) to a second computing device the MAC representing a tuple of a name of a data table, an identifier of a column of the data table, and a valid value for the column. Then, an encrypted bitmap can be received from the second computing device and decrypted to generate a decrypted bitmap. Bitwise operations can be performed on the decrypted bitmap to identify a plurality of encrypted rows of the data table containing a cell that comprises the valid value. Then, at least the plurality of at least partially encrypted rows of the data table can be requested from the second computing device and decrypted to generate a respective plurality of decrypted rows.

A memory for storing a directed acyclic graph (DAG) for access by an application being executed by one or more processors of a computing device is described. The DAG includes a plurality of nodes, wherein each node represents a data point within the DAG. The DAG further includes a plurality of directional edges. Each directional edge connects a pair of the nodes and represents a covering-covered relationship between two nodes (a covering node and a covered node). Each node comprises a subgraph consisting of the respective node and all other nodes reachable via a covering path that comprises a sequence of covering and covered nodes. Nodes present in the subgraph that do not cover any other nodes are leaves of the subgraph. Each node comprises a set of node parameters including at least an identifier and an address range. Each node and the legal address specify a cover path.

Efficient inner product search is important for many data ranking services, such as recommendation and Information Retrieval. Efficient retrieval via inner product dramatically influences the performance of such data searching and retrieval systems. To resolve deficiencies of prior approaches, embodiments of a new index graph construction approach, referred to generally as Norm Adjusted Proximity Graph (NAPG), for approximate Maximum Inner Product Search (MIPS) are presented. With adjusting factors estimated on sampled data, NAPG embodiments select more meaningful data points to connect with when constructing a graph-based index for inner product search. Extensive experiments verify that the improved graph-based index pushes the state-of-the-art of inner product search forward greatly, in the trade-off between search efficiency and effectiveness.

Configuring a data management system by receiving user interaction data associated with search results associated with a first system configuration, identifying a usage pattern in the user interaction data using a first machine learning model, and altering the first system configuration according to the usage pattern.

One embodiment provides for a method including performing, by a processing thread, a process that analyzes transactional operations by maintaining the transactional operations in transaction local side logs, and waiting until a successful transaction commit to append the transaction local side logs to a log stream. The processing thread processes the transactional operations on a key used to determine whether existing data is found for the key. The transactional operations are sped up through parallelism based on partitioning tables across nodes handling the transactional operations. A first process is performed by a first processor that processes updates for values of a key based on updating a first start time table index using unique keys and a start time field of a row for a first appearance of each unique key from the transactional operations.

An alarm processing method includes: receiving an alarm query request for a service, and acquiring a plurality of alarm records of the service; performing keyword extraction processing on the alarm record according to an attack word library of the service to obtain an attack keyword; determining a similarity between every two of the plurality of alarm records according to the attack keywords in the alarm records; and clustering the plurality of alarm records according to the similarity to obtain a plurality of alarm record clusters.

A system and method uses a vectorization model to determine similar elements within a web page to the known web page. The vectorization model takes a known web element and generates a first set of vectors, representative of the various properties of the web element. A vectorization model generates a second set of vectors for each element in a new web page. The first set of vectors is compared to each second set of vectors for each element in the new web page to select the most similar web element.

Configuring a data management system by receiving user interaction data associated with search results associated with a first system configuration, identifying a usage pattern in the user interaction data using a first machine learning model, and altering the first system configuration according to the usage pattern.

In one example, a method for assessing data records is disclosed. The method maps a plurality of keys to a respective plurality of the pools of records. The mapping operation may include mapping a first key to a first pool of records of a first array and mapping a second key to a second pool of records of a second array. The method applies logic rules to values of the pools of records that are in the same index or position of the first and the second array to generate a risk assessment score for a record corresponding to that index or position.

Methods, systems, and computer programs for distributed processing of a matrix data structure is disclosed. In one aspect, the method can include obtaining a first matrix data structure (DS), segmenting the obtained matrix DS into a set of M different matrix DS portions, segmenting each of the different M matrix DS portions into respective sets of K matrix DS sub-portions, for each of the respective sets of K matrix DS sub-portions: generating an obfuscation matrix having the same dimensions as each of the K matrix DS sub-portions, and generating, by one or more computers, an obfuscated representation of each respective set of K matrix DS sub-portions that includes (i) the K matrix DS sub-portions and (ii) the obfuscation matrix, and transmitting data representing each (of the N) obfuscated representation of the (K) matrix DS sub-portions of the respective sets of M matrix DS portions to a different computer for processing.