Abstract: A system for identifying one or more sub-fields within a field of a given field type, the field comprising a plurality of field bits, and each of the sub-fields comprising a distinct sub-group of the field bits having one or more fixed consecutive bit positions within each instance of a plurality of instances of the field, the system including a processing resource configured to: obtain one or more input time-series, each input time-series of the one or more input time-series including a plurality of input instances of the field; generate one or more new time-series, each new time-series of the generated new time-series being associated with at least one input time-series of the one or more input time-series and including a plurality of new instances of the field; generate a bit-field based on selected instances of the new instances in each new time-series of the generated new time-series; and analyze the bit-field to identify the fixed consecutive bit positions of at least one of the sub-fields within the fi

Abstract: A system for detecting Controller Area Network (CAN) messages anomalies, the system comprising a processing resource configured to: obtain a training set including training CAN messages associated with respective one or more vehicles; and train an anomaly detection model, using the training set, the anomaly detection model comprising one or more CAN message type anomaly detection models for one or more respective CAN message types that appear in the training set, each of the CAN message type anomaly detection models characterizing a functional dependency, if any, between one or more parts of values of payloads and interarrival times of CAN messages of the respective CAN message type, the interarrival times being determined using a timestamps associated with the CAN messages of the respective CAN message type; wherein the anomaly detection model is usable for classifying an unclassified CAN message of a given CAN message type as anomalous or non-anomalous.

Abstract: Website phishing detection is enabled using a siamese neural network. One twin receives a query image associated with a website page. The other twin receives a subset of a set of reference website images together with positive (phishing) examples that were used to train the networks, the subset of reference website images having been determined by applying an identifier associated with a brand of interest. The operation of applying the identifier significantly reduces the relevant search space for the inferencing task. If the inferencing determines a sufficient likelihood that the website page is a phishing page, control signaling is generated to control a system to take a given mitigation action n.

Abstract: Provided herein are populations of anti-CD20 antibody proteins with specified ranges of post-translational modifications. Also provided are methods of using and methods of making such populations of anti-CD20 antibody proteins.

Abstract: Provided herein are populations of anti-CD20 antibody proteins with specified ranges of post-translational modifications. Also provided are methods of using and methods of making such populations of anti-CD20 antibody proteins.

Abstract: Website phishing detection is enabled using a Message Passing Neural Network (MPNN) that scores requested HTML with a likelihood of being a phishing website. The technique leverages the assumption that the HTML in a phishing website often presents anomalous structure or features when compared with an analogous benign website. Once a phishing site is detected, a given mitigation action is then taken.

Abstract: Provided herein are populations of anti-CD20 antibody proteins with specified ranges of post-translational modifications. Also provided are methods of using and methods of making such populations of anti-CD20 antibody proteins.

Abstract: A system for generating a set of rules for detecting Controller Area Network (CAN) messages anomalies, the system comprising a processing resource configured to: obtain a training set including a plurality of CAN messages, each CAN message having properties; train a model, using the training set, the model characterizing statistical relationships between one or more first types of CAN messages of respective first CAN message type and one or more second types of CAN messages each of respective second CAN message type, wherein the statistical relationships are based on one or more of the properties of the CAN messages of the training set; wherein the model is usable for identifying anomalies within a sequence of input CAN messages.

Abstract: Provided herein are populations of anti-CD20 antibody proteins with specified ranges of post-translational modifications. Also provided are methods of using and methods of making such populations of anti-CD20 antibody proteins.

Abstract: A method executes upon receiving data (email, IP address) associated with an account registration. In response, an encoding is applied to the data to generate a node vector. The node vector indexes a database of such node vectors that the system maintains (from prior registrations). The database potentially includes one or more node vector(s) that may have a given similarity to the encoded node vector. To determine whether there are such vectors present, a set of k-nearest neighbors to the encoded node vector are then obtained from the database. This set of k-nearest neighbors together with the encoded node vector comprise a virtual graph that is then fed as a graph input to a Graph Neural Network previously trained on a set of training data. The GNN generates a probability that the virtual graph represents a NAF. If the probability exceeds a configurable threshold, the system outputs an indication that the registration is potentially fraudulent, and a mitigation action is taken.

Abstract: Provided herein are populations of anti-CD20 antibody proteins with specified ranges of post-translational modifications. Also provided are methods of using and methods of making such populations of anti-CD20 antibody proteins.

Abstract: Provided herein are populations of anti-CD20 antibody proteins with specified ranges of post-translational modifications. Also provided are methods of using and methods of making such populations of anti-CD20 antibody proteins.

Abstract: A method, apparatus and computer program product for real-time new account fraud detection and prevention. The technique leverages machine learning. In this approach, first and second computational branches of a machine learning model are trained jointly on a corpus of emails. Following training, an arbitrary email is received. The arbitrary email is then applied through the computational branches of the machine learning model. The first branch has an attention layer, and the second branch has a convolutional layer. The outputs of the branches are aggregated into an output that is then applied through another self-attention layer to generate a score. Based on the score, the arbitrary email is characterized. If the email is characterized as fraudulent, a mitigation action is taken.

Abstract: A system for generating a set of rules for detecting Controller Area Network (CAN) messages anomalies, the system comprising a processing resource configured to: obtain a training set including a plurality of CAN messages, each CAN message having properties; train a model, using the training set, the model characterizing statistical relationships between one or more first types of CAN messages of respective first CAN message type and one or more second types of CAN messages each of respective second CAN message type, wherein the statistical relationships are based on one or more of the properties of the CAN messages of the training set; wherein the model is usable for identifying anomalies within a sequence of input CAN messages.

Abstract: A system for identifying one or more sub-fields within a field of a given field type, the field comprising a plurality of field bits, and each of the sub-fields comprising a distinct sub-group of the field bits having one or more fixed consecutive bit positions within each instance of a plurality of instances of the field, the system including a processing resource configured to: obtain one or more input time-series, each input time-series of the one or more input time-series including a plurality of input instances of the field; generate one or more 10 new time-series, each new time-series of the generated new time-series being associated with at least one input time-series of the one or more input time-series and including a plurality of new instances of the field; generate a bit-field based on selected instances of the new instances in each new time-series of the generated new time-series; and analyze the bit-field to identify the fixed consecutive bit positions of at least one of the sub-fields within the

Abstract: Systems and computerized and computer-implemented methods operate to detect malicious applications (APPs). A method, which is performed on a suitably designed computerized system, comprises: obtaining text associated with an application; inputting a representation of the text into a classifier; and, the classifier processing the representation of the text. The classifier processes the representation of the text by processes including: applying weights to words of the text for which the classifier has provided weights by a words attention process, such that the weighted words of each sentence form a sentence vector; analyzing the sentence vectors by a sentence attention process to obtain a single summary vector for the sentence vectors; and, from the single summary vector, determining a score that the application is malicious.

Abstract: One aspect of the present invention provides a use of polymer 2-(methacryloyloxy)ethyl-2-(trimethylammonio)ethyl phosphate-stearylmethacrylate copolymer suspension as a compound which is beneficial to inflamed, irritated and sensitive skin. According to an alternative further aspect of the present invention there is provided a method of preparing a fabric which is non-irritating to the skin, said method comprising: scouring a fabric; rinsing the scoured fabric; coating the fabric with a polymer suspension having dual hydrophilic and hydrophobic characteristics; and finally setting the coated fabric to the required dimensions using a heat drying process so that an original handfeel of the fabric is not affected by the coating.

Abstract: An insect repellent fabric. The fabric comprises a fabric base and an active insect repellent ingredient. The active ingredient is contained within microcapsules and the fabric base is impregnated with the microcapsules. The preferred active ingredient is a Citronella extract or DEET.

Abstract: An insect repellent fabric. The fabric comprises a fabric base and an active insect repellent ingredient. The active ingredient is contained within microcapsules and the fabric base is impregnated with the microcapsules. The preferred active ingredient is a Citronella extract or DEET.

Abstract: A measuring apparatus and method for measuring dynamic parameters in a driven bicycle wheel are described. Parameters which are measured are; driven torque, angular velocity, angular acceleration, lateral angular acceleration, and applied power of the driven wheel. The measuring apparatus is affixed to the rear driven cog(s) of a bicycle wheel. One or more strain sensing elements affixed to the rear driven cog(s) detect the applied driven torque. Three or more acceleration sensing integrated circuits are used to determine angular velocity, angular acceleration, and lateral angular acceleration of the driven rear cog. These circuits reside on the primary electronics board and are affixed to the rear driven cog; hence they rotate along with the driven rear cog. Power applied to the driven wheel is derived from the torque and angular velocity measurements of the invention. These performance variables will aid a competitive cyclist to evaluate and observe progress in his or her physical training.