Eldardiry
Hoda Eldardiry, San Carlos, CA US
Patent application number | Description | Published |
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20160042287 | Computer-Implemented System And Method For Detecting Anomalies Using Sample-Based Rule Identification - A computer-implemented system and method for detecting anomalies using sample-based rule identification is provided. Data for data is maintained analytics in a database. A set of anomaly rules is defined. A rare pattern in the data is statistically identified. The identified rare pattern is labeled as at least one of anomaly and non-anomaly based on verification by a domain expert. The set of anomaly rules is adjusted based on the labeled anomaly. Other anomalies in the data are detected and classified by applying the adjusted set of anomaly rules to the data. | 02-11-2016 |
Hoda M.a. Eldardiry, San Carlos, CA US
Patent application number | Description | Published |
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20150235152 | SYSTEM AND METHOD FOR MODELING BEHAVIOR CHANGE AND CONSISTENCY TO DETECT MALICIOUS INSIDERS - One embodiment of the present invention provides a system for identifying anomalies. During operation, the system obtains work practice data associated with a plurality of users. The work practice data includes a plurality of user events. The system further categorizes the work practice data into a plurality of domains based on types of the user events, models user behaviors within a respective domain based on work practice data associated with the respective domain, and identifies at least one anomalous user based on modeled user behaviors from the multiple domains. | 08-20-2015 |
Hoda M. A. Eldardiry, San Carlos, CA US
Patent application number | Description | Published |
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20140244528 | METHOD AND APPARATUS FOR COMBINING MULTI-DIMENSIONAL FRAUD MEASUREMENTS FOR ANOMALY DETECTION - A fraud-detection system facilitates detecting fraudulent entities by computing weighted fraud-detecting scores for the individual entities. During operation, the system can obtain fraud warnings for a plurality of entities, and for a plurality of fraud types. The system computes, for a respective entity, a fraud-detection score which indicates a normalized cost of fraudulent transactions from the respective entity. The system then determines, from the plurality of entities, one or more anomalous entities whose fraud-detection score indicates anomalous behavior. The system can determine an entity that is likely to be fraudulent by comparing the entity's fraud-detection score to fraud-detection scores for other entities. | 08-28-2014 |
20140325643 | DETECTING ANOMALIES IN WORK PRACTICE DATA BY COMBINING MULTIPLE DOMAINS OF INFORMATION - One embodiment of the present invention provides a system for multi-domain clustering. During operation, the system collects domain data for at least two domains associated with users, wherein a domain is a source of data describing observable activities of a user. Next, the system estimates a probability distribution for a domain associated with the user. The system also estimates a probability distribution for a second domain associated with the user. Then, the system analyzes the domain data with a multi-domain probability model that includes variables for two or more domains to determine a probability distribution of each domain associated with the probability model and to assign users to clusters associated with user roles. | 10-30-2014 |