Symantec Corporation

Ca, Inc.

Nortonlifelock Inc.

Mahmood Sharif

Kevin Alejandro Roundy

Sandeep B Bhatkar

Christopher Gates

Daniel Kats

Acar Tamersoy

Saurabh Shintre

Matteo Dell'Amico

Dong Chung

The disclosed computer-implemented method for training malware classifiers may include (1) perturbing, at a computing device, a binary file in a manner that maintains functionality of the binary file, (2) classifying the perturbed binary file with a first machine learning classifier to produce a classification result, (3) producing a transformed file by repeating the perturbing and classifying steps until the transformed file becomes misclassified, and (4) performing a security action comprising training a second machine learning classifier with the transformed file and an associated correct classification result. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for training malware classifiers

The present disclosure relates to using correlations between support interaction data and telemetry data to discover emerging incidents for remediation. One example method generally includes receiving a corpus of support interaction data and a corpus of telemetry data. Topics indicative of underlying problems experienced by users of an application are extracted from the corpus of support interaction data. A topic having a rate of appearance in the support interaction data above a threshold value is identified. A set of telemetry data relevant to the topic is extracted from the corpus of telemetry data, and a subset of the relevant set of telemetry data having a frequency in the relevant set of telemetry data above a second threshold value is identified. The topic and the subset of telemetry data are correlated to an incident to be remediated, and one or more actions are taken to remedy the incident.

Discovery of computer system incidents to be remediated based on correlation between support interaction data and computer system telemetry data

The disclosed computer-implemented method for using electronic text information to automatically determine untrustworthy voice calls, at least a portion of the method being performed by a computing device comprising at least one processor, may include (1) during a voice call, receiving, by the computing device, text information representing contents of the voice call, (2) analyzing, by the computing device, the text information representing the contents of the voice call, (3) determining, by the computing device, that the voice call is untrustworthy based on the analysis of the text information, and (4) during the voice call, advising a recipient of the voice call of the determination that the voice call is untrustworthy. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for real-time scam protection on phones

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Pittsburgh, PA, United States of America

Mahmood Sharif