Citrix Systems, Inc.

Other

Aikaterini Kalou

Georgios Papaloukopoulos

Nicholas James Stavrakos

Georgios Tsolis

Athanasios Kordelas

Asterios Stergioudis

Manbinder Pal Singh

Saifulla Shaik

Pakshal Kumar H Dhelaria

Ambarish Kumar

Kostas Katrinis

Stuart Kennedy

Abirami Sukumaran

Described embodiments provide systems and methods for generating a network space to perform mitigation actions on a plurality of users. At least one server may determine a plurality of users of one or more levels of riskiness in a network environment, and network locations of the users. Using a plurality of clustering features, the at least one server may generate a network space comprising a cluster of network locations corresponding to a subset of the users of at least a defined level of riskiness. The at least one server may perform a mitigation action on the subset of users corresponding to the generated network space.

System and method for deriving network address spaces affected by security threats to apply mitigations

Described embodiments provide systems and methods for enhancing user engagement with micro applications. A computing device can include one or more processors and memory. The computing device can receive an indication of an action to be completed with use of a micro application. The computing device can be in communication with a client device and one or more computing systems of record to execute the micro application. The computing device can values for one or more attributes of the micro application. The computing device can generate, based on the identified values, a score for the micro application. The computing device can provide the score to the client device for display within a user interface. The user interface can be configured to initiate the action with use of the micro application.

Systems and methods to implement microapps in digital workspaces

Described embodiments provide systems and methods for inferring a network type and network conditions. The system includes a packet capturing engine configured to capture a plurality of network packets from a plurality of TCP network connections. The system includes a packet analyzer configured to analyze the plurality of network packets to generate a plurality of metrics. The system includes a network classifier configured to infer network types of the plurality of TCP connections based on the plurality of metrics and at least one classification model. The system also includes a conditions ranking engine configured to estimate a level of network congestion for each TCP connection based on the plurality of metrics and the network types.

Inferring radio type from clustering algorithms

The present disclosure is directed to a scalable, extensible, fault-tolerant system for stateful joining of two or more streams that are not fully synchronized, event ordering is not guaranteed, and certain events arrive a bit late. The system can ensure to combine the events or link the data in near real-time with low latency to mitigate impacts on downstream applications, such as ML models for determining suspicious behavior. Apart from combining events, the system can ensure to propagate the needed entities to other product streams or help in entity resolution. If any of the needed data is yet to arrive, a user can configure a few parameters to achieve desired eventual and attribute consistency. The architecture is designed to be agnostic of stream processing framework and can work well with both streaming and batch paths.

Systems and methods for data linkage and entity resolution of continuous and un-synchronized data streams

Described embodiments provide systems and methods for anomaly detection and root cause analysis. A root cause analyzer receives a plurality of data samples input to an anomaly detection engine, and a corresponding plurality of anomaly labels output from the anomaly detection engine. The root cause analyzer trains a classification model using the plurality of data samples and the corresponding plurality of anomaly labels. The root cause analyzer determines, using the trained classification model and the plurality of data samples, relative contributions of anomalous features in a data sample of the plurality of data samples, to a prediction that the data sample is anomalous. The root cause analyzer provides the relative contributions of anomalous features to a device, to determine an action in response to the prediction that the data sample is anomalous.

Root cause analysis in multivariate unsupervised anomaly detection

Described embodiments provide systems, methods, computer readable media for determining risk metrics. A device may provide a risk model for a network environment. The risk model may include an input level and an output level. The input level may process first datasets each corresponding to a feature and a time window. The first datasets may include factors on access requests. The output level may generate a first aggregate risk metric of a first access request according to the datasets processed by the input level. The device may identify a second dataset corresponding to a second access request over the features and time windows. The device may determine a second aggregate risk metric by applying the second dataset to the risk model. The device may generate a response to the second access request according to an access control policy and the second aggregate risk metric.

Determining risk metrics for access requests in network environments using multivariate modeling

In accordance with one example method, a computing system may determine that first user profile data of a first user of a relevance scoring service is similar to second user profile data of a second user of the relevance scoring service, where the relevance scoring service is configured to assign first relevance scores to first information chunks to be presented to the first user based at least part on at least a first portion of first stored behavior data of the first user, and where the first stored behavior data is indicative of the first user's interactions with second information chunks previously presented to the first user. In response to determining that the first user profile data is similar to the second user profile data, the relevance scoring service may be configured to assign second relevance scores to third information chunks to be presented to the second user based at least in part on at least a second portion of the first stored behavior data.

Bootstrapped relevance scoring system

In some embodiments, a computing system may receive at least first data indicative of a first event of a first system of record accessed using first access credentials associated with a user, determine, based at least in part on first stored contextual data associated with the user, to create at least a first notification of the first event based at least in part on the first data, and send the first notification to a client device operated by the user.

Growing community of inventors

Patras, Greece

Aikaterini Kalou