Abstract: Machine-learning (ML) techniques and models are described for predicting the number and severity of network attacks within a specified timeframe, such as the next fifteen minutes. In some embodiments, the techniques including training a ML model based on features extracted from a training dataset and applying the trained ML model to estimate (a) the probability of an attack happening on an account within a specified timeframe; (b) how many attacks are predicted to occur in the specified timeframe (if any); and/or (c) the severity of the attacks predicted to occur. A system may deploy preventative measures based on the ML model output to counter or mitigate the effects of predicted and coordinated network attacks.

Abstract: Machine-learning techniques and models are described for alerting users to attacks on accounts in real-time or near real-time. In some embodiments, an attack detection model uses Natural Language Processing (NLP) and multi-level classification techniques to monitor login attempts and detect attacks. The model may use NLP to convert text associated with account activity to numerical vectors, where the vectors include scores and/or other numerical values computed based on the meaning of the converted text. The model may further include a set of classifiers trained to learn patterns in the numerical vectors that are predictive of a network attack. The model may assign labels to events based on the predicted likelihood that the event is an attack. The system may deploy real-time preventative or corrective measures based on the ML model output to counter or mitigate the effects of an attack.

Abstract: The present invention provides a dynamic organizational database as an underlying information system to support collaborative computing in a global enterprise. This information system is built based on the Organizational Modeling and Management model (OMM) and provides a system architecture and a graphical user interface for easy manipulation of organizational objects. Contrary to traditional approaches, the present invention separates the organization model from the process model, the application model and the data model. Thus, independent and flexible enterprise modeling and design is allowed to reflect more realistically a rapidly changing business environment.

Abstract: During the processing of a transaction or other distributed computation, a computation management system creates a number of agents to handle various aspects or portions of the computations to be performed. Each agent progresses through a predefined set of state transitions which define the status of the agent at any point in time. The computation management system defines for each agent a set of dependencies, each dependency corresponding to a state transition which will be blocked until a particular state transition occurs in another specified agent. By defining selected combinations of dependencies for each agent, a variety of different interdependencies and cooperating protocols can be implemented. The distributed processing management system can be used both for managing transaction processing and for synchronizing events in other types of distributed computations.

Abstract: A database index file is maintained by a computer system having primary random access memory and secondary memory. A record for each item added to the database is stored in a sequential file in secondary memory (disk storage) and an indexed pointer to the new record is stored in a small B-tree stored in primary random access memory. The full index file for the database is a second, large B-tree stored in secondary memory. Leaf-nodes of the full index file are stored in indexed order. Periodically, a portion of the memory resident small B-tree is merged with a corresponding portion of the large B-tree by selecting a range of index values and retrieving from secondary memory all indexed pointers in the selected range of index values. The indexed pointers in the first B-tree in the selected range of index values are merged into the retrieved records, the resulting merged set of indexed pointers are stored in secondary memory in indexed order in a contiguous area of secondary memory.