Deutschetelekom Ag

Verint Systems, Inc.

B.g. Negev Technologies and Applications Ltd.

Yoochoose Gmbh

Lior Rokach

Rami Puzis

Yuval Elovici

Asaf Shabtai

Zahy Bnaya

Guy Shtar

Ziv Katzir

Liran Orevi

Genady Malinsky

Ron Bitton

Roni Stern

Tal Beja

Ariel Felner

Liron Samama

Barak Chizi

Bracha Shapira

Dudu Mimran

Meir Kalech

David Mimran

Amnon Meisels

Robert Moskovitch

Andreas Grothe

Rahul Swaminathan

Elihau Khalaschi

Michael Friedmann

David Ben-Shimon

Eitan Menahem

Gai Shani

Nischal Piratla

Oleg Brodt

Ariel Bar

Moshe Unger

Andreas Rederer

Genady Malinksy

Ma'ayan Gafny

Amir Harel

Tomer Shimshon

Stefan Zeidler

Described embodiments include a system that includes a monitoring agent, configured to automatically monitor usage of a computing device by a user, and a processor. The processor is configured to compute, based on the monitoring, a score indicative of a cyber-security awareness of the user, and to generate an output indicative of the score.

System and method for assessing cybersecurity awareness

When using Web intelligence ('Webint') to collect information regarding a target social network user, one of the most valuable pieces of information is the target user's List-Of-Friends (LOF). In some cases, however, the LOF of the target user is not accessible in his profile. Herein are described methods and systems for identifying the LOF of a target user. An analysis system crawls the profiles of social network users, other than the target user, and reconstructs the LOF of the target user from the crawled profiles.

System and method for identifying contacts of a target user in a social network

A method for generating synthetic data records which include datasets that capture state-based transitions, according to which a state transition family is randomly selecting, according to the distribution of samples between the different clusters of users and the context variables are randomly sampled according to their distribution within the chosen cluster. The relevant Markov Chains models are selected according to the sampled context and the initial state of the sequence is randomly selected according to the distribution of states. A random walk process is initialized on the graph models and the random walk is performed process on each context separately, assuming context independency. The cause condition of the current transition is sampled for each state transition, based on the distributions on the selected edge.

Synthetic data generation method

A method for detecting and diagnosing sensor faults in an autonomous system that includes sensors and hardware components, according to which sensors are related to hardware components and correlations between data readings are recognized online and correlation between sensors is determined. Predefined suspicious patterns are identified by online and continuously tracking the data readings from each sensor and detecting correlation breaks over time. The readings from sensors that match at least one of the patterns are marked as uncertain. For each online reading of the sensors, whenever sensors that used to be correlated show a different behavior, reporting that the reading indicates a fault. Upon identifying fault detection, diagnosing which of the internal components or sensors caused the fault, based on a function that returns the state of the sensor which is associated with the fault detection.

Sensor fault detection and diagnosis for autonomous systems

A recommender system for recommending items to a user based on geo-Tagged information related to him, in which items associated with a GeoTag are stored in a database. Feedback regarding the various items is obtained from the user and the provided rating of items is propagated to closely located items based on their associated GeoTags. A user-to-user similarity matrix is calculated and a predicted score is assigned for each user and item, using a recommendation server. All the items in the catalog of items are sorted according to their predicted scores as calculated for the user, and all items that have been already rated by the user are filtered out. Then, items from the catalog of items are presented to the user, according to their scores.

Method and system for recommending Geo-tagged items

A method for improving stacking schema for classification tasks, according to which predictive models are built, based on stacked-generalization meta-classifiers. Classifications are combined to build a new scheme from at least two layers and multiclass classification problems are converted into binary classification problems. One-against-all class binarization and regression learners are used for each class model and ensemble classifiers are improved using stacking. Accuracy differences, accuracy ratio, and runtime classification in multiclass datasets are also improved and the class of a value is then predicted.

Stacking schema for classification tasks

A hybrid recommender system, in which the initial stereotype is manually defined by an expert and an affinity vector of stereotypes relating to each specific user who registers onto the system, is created to define a specific profile for each user. Recommendations for a specific user are generated according to the initial stereotype and the affinity vector of stereotypes. A binary feedback, from user regarding specific items picked by him is received (e.g., while of the item), which can be either positive or negative. Then the affinity vector of stereotypes is updated.

Interactive hybrid recommender system

Growing community of inventors

Omer, Israel

Lior Rokach