Healthy.io Ltd

Red Bend Ltd.

Harman International Industries, Inc.

Shachar Mendelowitz

Roee Salomon

Yonatan Adiri

Ido Omer

Alexander Kreines

Nir Morgulis

Ori Goldberg

Aashish Kumar

George Jose

Dror Cohen

Sambuddha Saha

Nurit Peres

David Reikher

Srinivas Kruthiveti Subrahmanyeswara Sai

A method, system, and computer program product for anomaly detection using embedding space representation of system states. An anomaly detection model is trained using an anomaly detection algorithm and a plurality of reference vectors obtained using an embedding space representation process configured for mapping to a single point vector in an embedding space each of a plurality of system state snapshots comprised in a training dataset and each capturing during a defined time window a plurality of features of each process operating in the system. Responsive to receiving a testing dataset comprising one or more system state snapshots, one or more vectors in the embedding space are obtained using the embedding space representation process for mapping each system state snapshot in the testing dataset, and the anomaly detection model is used to determine whether a vector of the one or more vectors being indicative of a cyber-attack on the system.

Anomaly detection using embedding space representation of system states

Disclosed herein are systems and methods for detecting potential malicious attacks in vehicles operational environment using staged Machine Learning (ML), comprising creating a plurality of features vectors each comprising a plurality of features extracted from vehicle operational data generated by a plurality of devices deployed in one or more vehicles which is indicative of operation of the one or more vehicles, detecting, in real-time, a plurality of anomaly feature vectors using one or more unsupervised ML models applied to the plurality of feature vectors, identifying, in real-time, one or more potential cyberattack events using one or more supervised ML models applied to the plurality of anomaly feature vectors, and generating an alert indicative of the one or more potential cyberattack events.

Using staged machine learning to enhance vehicles cybersecurity

Kits, diagnostic systems and methods are provided, which measure the distribution of colors of skin features by comparison to calibrated colors which are co-imaged with the skin feature. The colors on the calibration template (calibrator) are selected to represent the expected range of feature colors under various illumination and capturing conditions. The calibrator may also comprise features with different forms and size for calibrating geometric parameters of the skin features in the captured images. Measurements may be enhanced by monitoring over time changes in the distribution of colors, by measuring two and three dimensional geometrical parameters of the skin feature and by associating the data with medical diagnostic parameters. Thus, simple means for skin diagnosis and monitoring are provided which simplify and improve current dermatologic diagnostic procedures.

Measuring and monitoring skin feature colors, form and size

Examples are disclosed for methods and mechanisms to address Base Transceiver Stations (BTSes) attempting to hijack Mobile Stations (MSes) in wireless communication networks. In some example methods, a record having values for a set of features associated with an MS and a BTS of a wireless communication net may be processed. A score for the record may be calculated, for example based on a machine-learning model pertaining to the set of features, and a determination may be made as to whether the record demonstrates an anomalous condition based upon the score. The set of features may include at least one feature based on a measured power of the BTS.

Detection of wireless communication hijacking

Systems and methods for verifying wireless connections are provided. In one example, a method includes, at a computing system, responsive to initiating a wireless connection between a client device and a host device, generating a communication fingerprint of the client device based on at least one response characteristic of the client device, the at least one response characteristic based on a communication between the client device and the host device, the communication passing through each of a software layer of the client device and a hardware element of the client device. In this way, overall system security of a wireless connection between the host device and the client device may be increased.

Systems and methods for bluetooth authentication using communication fingerprinting

Techniques for detecting anomalies or cyber attacks on a vehicle. A computer-implemented method for anomaly or attack detection includes determining, using a first model, a first predicted value of a first variable message associated with a vehicle, determining, using a second model, a second predicted value of the first variable message associated with the vehicle, determining, based on a difference between an actual value of the first variable message and the first predicted value of the first variable message and on a difference between the actual value of the first variable message and the second predicted value of the first variable message, a vector, and determining, using a third model, an output value based on the vector, the output value corresponding to at least one of a likelihood that an anomaly or an attack is occurring or a type of the anomaly or the attack.

Detecting vehicle malfunctions and cyber attacks using machine learning

Techniques are disclosed for detecting adversarial attacks. A machine learning (ML) system processes the input into and output of a ML model using an adversarial detection module that does not include a direct external interface. The adversarial detection module includes a detection model that generates a score indicative of whether the input is adversarial using, e.g., a neural fingerprinting technique or a comparison of features extracted by a surrogate ML model to an expected feature distribution for the output of the ML model. In turn, the adversarial score is compared to a predefined threshold for raising an adversarial flag. Appropriate remedial measures, such as notifying a user, may be taken when the adversarial score satisfies the threshold and raises the adversarial flag.

Defending machine learning systems from adversarial attacks

Mechanisms and methods are provided for establishing vectors indicating the presence, in a first vehicle and second vehicle, of a super-set of vehicle features present across a fleet of vehicles. The first vehicle may be a reference vehicle. A distance function of the vectors may be calculated in order to establish a similarity score indicating the degree of similarity between the designs of the two vehicles. If the second vehicle is sufficiently similar to the reference vehicle, a software update may be recommended and applied.

Methods for prioritizing updates for vehicle fleets

Systems and methods for testing visible chemical reactions of a reagent are provided. In one implementation, the method may include receiving from an image sensor associated with a mobile communications device an image of a reagent with a plurality of colored test reagent pads in proximity to a colorized surface having a plurality of colored reference elements of differing shades. The method further includes using the differing shades of the plurality of colored reference elements to determine local illumination conditions. Thereafter, the method includes using the determined local illumination conditions and an analysis of a depiction of the plurality of colored test reagent pads in the image to determine an extent of a chemical reaction on the reagent. Then the method includes causing the mobile communications device to provide to the user an indication that the testing of the reagent is complete.

Systems and methods for urinalysis using a personal communications device

Systems and methods for analyzing visible chemical reactions are provided. In one implementation, the method may include receiving from an image sensor associated with a mobile communications device an image of a reagent pad in proximity to a colorized surface having at least one pair of colored reference elements. The method includes identifying in the image the reagent pad, a first colored reference element, and a second colored reference element. Thereafter, the method includes using the first colored reference element and the second colored reference element to determine an extent of a chemical reaction on the reagent pad irrespective of local illumination conditions. Then the method includes causing the mobile communications device to provide data based on the extent of the chemical reaction.

Utilizing personal communications devices for medical testing

A method for analyzing a dipstick using a smartphone is provided herein. The method includes: capturing an image containing: a dipstick having colored test reagents, and a color board having a grid of grey patches and a plurality of reference color patches; deriving, based on the grid, local illumination parameters associated with the colored test reagents and the plurality of reference color patches; determining whether illumination parameters are sufficient for interpreting the colored test reagent; in a case the illumination parameters are insufficient, notifying a user that an interpretation of the colored test reagents is not possible, otherwise, applying one or more image enhancement operation to the captured image, based on an analysis of the grid of grey patches, to yield enhanced reference color patches; and interpreting the one or more colored test reagents, by projecting the colored test reagents onto a vector of the enhanced reference color patches.

Growing community of inventors

Tel Aviv, Israel

Shachar Mendelowitz