Abstract: Systems and methods for anonymizing personal information are provided. A set of data may be received that includes a first subset of data that corresponds to a unique identifier, a second subset of data that corresponds to a timestamp, and a third subset of data that corresponds to a personal identifiable information (PII) record. The PII record may include a plurality of fields, one or more of which may include values. The set of data may be pre-processed. A respective embedding may be generated, for each value of a respective field, of the plurality of fields, that includes a value. The pre-processed set of data may be anonymized to generate an anonymized set of data, in the form of a graph structure. The graph structure may be stored in a database, and a fraud risk model may be trained, based on the database.

Abstract: Aspects of the present disclosure are operable to protect against malicious objects, such as JavaScript code, which may be encountered, downloaded, or otherwise accessed from a content source by a computing system. In an example, antivirus software implementing aspects disclosed herein may be capable of detecting malicious objects in real-time. Aspects of the present disclosure aim to reduce the amount of time used to detect malicious code while maintaining detection accuracy, as detection delays and/or a high false positive rate may result in a negative user experience. Among other benefits, the systems and methods disclosed herein are operable to identify malicious objects encountered by a computing system while maintaining a high detection rate, a low false positive rate, and a high scanning speed.

Abstract: Aspects of the present disclosure are operable to protect against malicious objects, such as JavaScript code, which may be encountered, downloaded, or otherwise accessed from a content source by a computing system. In an example, antivirus software implementing aspects disclosed herein may be capable of detecting malicious objects in real-time. Aspects of the present disclosure aim to reduce the amount of time used to detect malicious code while maintaining detection accuracy, as detection delays and/or a high false positive rate may result in a negative user experience. Among other benefits, the systems and methods disclosed herein are operable to identify malicious objects encountered by a computing system while maintaining a high detection rate, a low false positive rate, and a high scanning speed.

Abstract: A system and method to explain model behavior, which can benefit not only those seeking to meet regulatory requirements when using machine learning models but also help guide users of the model to assess and increase robustness associated with model governance processes. The method described utilizes changes in behavior of a time series to identify the latent factors that drive explanation.

Abstract: Aspects of the present disclosure are operable to protect against malicious objects, such as JavaScript code, which may be encountered, downloaded, or otherwise accessed from a content source by a computing system. In an example, antivirus software implementing aspects disclosed herein may be capable of detecting malicious objects in real-time. Aspects of the present disclosure aim to reduce the amount of time used to detect malicious code while maintaining detection accuracy, as detection delays and/or a high false positive rate may result in a negative user experience. Among other benefits, the systems and methods disclosed herein are operable to identify malicious objects encountered by a computing system while maintaining a high detection rate, a low false positive rate, and a high scanning speed.

Abstract: Aspects of the present disclosure are operable to protect against malicious objects, such as JavaScript code, which may be encountered, downloaded, or otherwise accessed from a content source by a computing system. In an example, antivirus software implementing aspects disclosed herein may be capable of detecting malicious objects in real-time. Aspects of the present disclosure aim to reduce the amount of time used to detect malicious code while maintaining detection accuracy, as detection delays and/or a high false positive rate may result in a negative user experience. Among other benefits, the systems and methods disclosed herein are operable to identify malicious objects encountered by a computing system while maintaining a high detection rate, a low false positive rate, and a high scanning speed.

Abstract: A computer system comprising a processor and a memory storing instructions that, when executed by the processor, cause the computer system to perform a set of operations. The set of operations comprises collecting domain attribute data comprising one or more domain attribute features for a domain, collecting sampled domain profile data comprising one or more domain profile features for the domain and generating, using the domain attribute data and the sampled domain profile data, a domain reputation assignment utilizing a neural network.

Abstract: A system and method to explain model behavior, which can benefit not only those seeking to meet regulatory requirements when using machine learning models but also help guide users of the model to assess and increase robustness associated with model governance processes. The method described utilizes changes in behavior of a time series to identify the latent factors that drive explanation.

Abstract: Aspects of the present disclosure are operable to protect against malicious objects, such as JavaScript code, which may be encountered, downloaded, or otherwise accessed from a content source by a computing system. In an example, antivirus software implementing aspects disclosed herein may be capable of detecting malicious objects in real-time. Aspects of the present disclosure aim to reduce the amount of time used to detect malicious code while maintaining detection accuracy, as detection delays and/or a high false positive rate may result in a negative user experience. Among other benefits, the systems and methods disclosed herein are operable to identify malicious objects encountered by a computing system while maintaining a high detection rate, a low false positive rate, and a high scanning speed.