Systems and techniques for sharing security data are described herein. Security rules and/or attack data may be automatically shared, investigated, enabled, and/or used by entities. A security rule may be enabled on different entities comprising different computing systems to combat similar security threats and/or attacks. Security rules and/or attack data may be modified to redact sensitive information and/or configured through access controls for sharing.

Security sharing system

A computer system identifies malicious Uniform Resource Locator (URL) data items from a plurality of unscreened data items that have not been previously identified as associated with malicious URLs. The system can execute a number of pre-filters to identify a subset of URLs in the plurality of data items that are likely to be malicious. A scoring processor can score the subset of URLs based on a plurality of input vectors using a suitable machine learning model. Optionally, the system can execute one or more post-filters on the score data to identify data items of interest. Such data items can be fed back into the system to improve machine learning or can be used to provide a notification that a particular resource within a local network is infected with malicious software.

Malicious software detection in a computing system

Embodiments of the present disclosure relate to a data analysis system that may automatically analyze a suspected malware file, or group of files. Automatic analysis of the suspected malware file(s) may include one or more automatic analysis techniques. Automatic analysis of may include production and gathering of various items of information related to the suspected malware file(s) including, for example, calculated hashes, file properties, academic analysis information, file execution information, third-party analysis information, and/or the like. The analysis information may be automatically associated with the suspected malware file(s), and a user interface may be generated in which the various analysis information items are presented to a human analyst such that the analyst may quickly and efficiently evaluate the suspected malware file(s). For example, the analyst may quickly determine one or more characteristics of the suspected malware file(s), whether or not the file(s) is malware, and/or a threat level of the file(s).

Malware data item analysis

Systems and methods are disclosed for news events detection and visualization. In accordance with one implementation, a method is provided for news events detection and visualization. The method includes, for example, obtaining one or more user inputs, determining, based on the user inputs, an entity and a date range, obtaining one or more documents associated with the entity and with dates within the date range, the one or more documents being grouped into one or more clusters, and the clusters being grouped into one or more megaclusters, and presenting the one or more documents on one or more timelines, wherein the one or more documents are grouped into different megaclusters being presented in a visually distinct way. The method further allows for filtering of the one or more clusters based on a value associated with the one or more clusters.

System and method for news events detection and visualization

Systems and methods are provided for analyzing entity performance. In one implementation, a method is provided that includes receiving a request with one or more filter selections and accessing a data structure comprising a plurality of categories of information showing interactions associated with multiple entities. The method also comprises identifying a set of categories of the plurality of categories within the data structure based on the one or more filter selections. The method further comprises processing the information of the identified categories to analyze a performance of one or more entities of the multiple entities in accordance with the one or more filter selections and providing the processed information to display the performance of the one or more entities on a user interface.

Methods and systems for analyzing entity performance

In one aspect, a system includes a transaction handler to process transactions, a data warehouse to store data recording the transactions, a portal configured to communicate with a search engine and to provide a user interface to receive a request from a merchant, and at least one processor coupled with the data warehouse and the portal. In response to the request received from the merchant via the portal, the at least one processor identifies a set of first statistics based on search activities of the search engine, identifies a set of second statistics based on the transactions relevant to the search activities, and uses the portal to juxtapose the set of first statistics and the set of second statistics.

Michelle Eng Winters

Papers

Systems and methods to enhance search data with transaction based data