Concentric Software, Inc.

Sumeet Khirwal

Madhusudana Shashanka

Shankar Subramaniam

Leomart Reyes Crisostomo

Bonnie Arogyam Varghese

Methods and systems for determining anomalous user access to data objects. The method includes determining baseline access data comprising a plurality of access elements. The method includes generating target access data for the user, where the target access data indicates a count of data objects accessed by the user within each of the plurality of semantic categories during a target time interval. The method includes computing an anomalous factor for the user based, at least in part, on the baseline access data and the target access data. The anomalous factor for the user indicates a degree of the anomalous behavior of the user during the target time interval. The method includes determining whether the user is an anomalous user based, at least in part, on the computed anomalous factor for the user.

Methods and systems for determining anomalous user access to data objects

Methods and systems for optimizing grouping for enhanced access control and risk mitigation. The method includes obtaining user data including data associated with a plurality of users and a plurality of groups, and access data including data associated with a plurality of data objects and corresponding access information. The method includes determining a first mapping information between each of the plurality of groups with corresponding users of the plurality of users based on the user data, and determining a second mapping information between each of the plurality of data objects with corresponding users of the plurality of users based on the access data. The method includes generating a cluster dataset representing a plurality of clusters based at least on processing of a relational structure between the first mapping information and the second mapping information. The plurality of clusters represent newly generated groups of the plurality of users.

Methods and systems for optimizing grouping for enhanced access control and risk mitigation in an enterprise

Methods and systems for identifying anomalous users exhibiting overreaching access permissions to data objects. The method includes determining access permission data for each of a plurality of users. Each of the plurality of data objects corresponds to one of a plurality of categories. The method includes determining first score data for each user of the plurality of users based on the access permission data associated with each of the plurality of users. The method includes computinga threshold value of the first score data defining a boundary value of the first score datafor identification of the anomalous users. The method includes identifying a subset of users, among the plurality of users, as the anomalous users exhibiting overreaching access permission. The first score data for each of the subset of usersis equal to or below the computed threshold value.

Methods and systems for identifying anomalous users exhibiting overreaching access permissions to data objects

Methods and systems for clustering documents according to semantic similarity are disclosed. The method includes generating an embedding for each of a plurality of documents to form a plurality of embeddings. Each embedding is indicative of a semantic representation for the corresponding document. The method includes segregating the plurality of embeddings into a plurality of shards. The method includes clustering one or more embeddings within each shard of the plurality of shards into the one or more first clusters. The one or more first clusters for each shard collectively constitute a plurality of first clusters. The method includes generating a plurality of second clusters across the plurality of shards, based, at least in part, on semantic similarity between the plurality of embeddings and the plurality of first clusters.

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Jamshedpur, India

Sumeet Khirwal