Zoho Corporation Private Limited

Shailesh Kumar Davey

Ramprakash Ramamoorthy

Sujatha S Iyer

Satya Madhuri Penumarthi

Sita Lakshmi Sangameswaran

Balachandar S

Gouttham Nambirajan

A system and method for masking personally identifiable information (PII) using neural style transfer is disclosed. The present disclosure helps tackle the problem of PII being harvested from documents for illegitimate purposes. The present disclosure also curtails unscrupulous means of employing an optical character recognition (OCR) engine in exploiting or harvesting PII from digitized documents. Techniques described in this paper include customized PII masking.

Method and system for masking personally identifiable information (PII) using neural style transfer

Described are methods and system that digitally watermark documents using an encoding scheme that embeds unique identifiers into the files by perturbing the relative heights of words to create patterns that are imperceptible to the human eye but decodable to recover the identifiers. The unique identifiers can be precoded before they are embedded in the documents.

Methods and systems for watermarking documents

An effective strategy provides an intuitive starting point for an enterprise network agent to resolve issues before the issues increase the probability of an outage. Being able to predict whether and when a current anomalous state will transform into an outage is valuable to an enterprise network agent tasked with network administration, including monitoring the network; configuring the network; recommending software or hardware licenses, updates, or additions; obtaining software or hardware licenses or devices; generating reports and alerts; and launching countermeasures in association with the enterprise network.

Outage prediction in full-stack performance monitoring space

Obtaining one or more metrics associated with a network location. Determining, based on the one or more metrics and one or more prefatory check conditions, a prefatory status of the network location, the prefatory status indicating a benign status, malicious status, or a suspicious status. If the prefatory status of the network location indicates the benign status or the malicious status, providing a notification of the prefatory status in response to the prefatory status being determined. If the prefatory status of the network location indicates a suspicious status, obtaining a document object model of the network location. Obtaining a screenshot of an entire page of content at the network location. Generating a null hypothesis based on the document object model, the null hypothesis including a potential brand list, the potential brand list including one or more potential brands. Obtaining a set of reference images for each of the one or more potential brands of the potential brand list. Extracting one or more globally invariant visual features from the screenshot of the entire page of the content. Generating, based on a machine learning model using the one or more globally invariant visual features, an alternate hypothesis, the alternate hypothesis indicating a list of potentially malicious content brands. Determining, based on the null hypothesis and the alternate hypothesis and the machine learning model, a classification result. Performing one or more responsive actions in response to determining the classification result.

Machine learning-based sensitive resource collection agent detection

A method and system for time series forecasting are described. Forecasting a time series, though uncertain, has a potential to improve decision-making. It gives a picture of what can probably be expected. A live time series typically has trend and seasonality as its innate characteristic features, randomness being obvious in real-time. Described embodiments address complexity in configuring zero-configuration workflow forecasting methods at production scale. Described embodiments address complexity in configurating domain independent forecasting methods at production scale.

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Potheri, India

Shailesh Kumar Davey