Paypal, Inc.

Gaoyuan Wang

Li Cao

Ravi Retineni

Jie Huang

Yi Ren

Alejandro Picos

Hang Yu

Deepa Madhavan

Srinivasabharathi Selvaraj

Amir Hossein Youssefi

Zihao Zhao

Sneha Venkatachalam

Zhaoyang Wang

Huiting Li

Fuyuan Kang

Zelin Yan

Aspects of the present disclosure involve, a customizable system and infrastructure which can receive privacy data from varying data sources for privacy scanning, containment, and reporting. In one embodiment, data received is scanned for privacy data extraction using various data connectors and decryption techniques. In another embodiment, the data extracted is transferred to a privacy scanning container where the data is analyzed by various deep learning models for the correct classification of the data. In some instances, the data extracted may be unstructured data deriving form emails, case memos, surveys, social media posts, and the like. Once the data is classified, the data may be stored or contained according to the classification of the data. Still in another embodiment, the classified data may be retrieved by an analytics container for use in reporting.

System and method for generating privacy data containment and reporting

Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Software process modification platform for compliance

Techniques are discussed for preparing and executing scanning plans for particular types of information, including personally identifiable information. A user indicates one or more datastores to be scanned for the particular type of information. A scanner determines scan objectives for the scanning plan and classifiers for use in scans conducted according to the scanning plan. The scanner estimates scan performance metrics and scan quality metrics. The scanner presents estimated results for the scanning plan based on the selected classifiers, scan objectives, estimate scan performance metrics, and estimated scan quality metrics. The user can modify the set of scan objectives or select between alternative sets of scan objectives. The scanning plan may be performed iteratively and the results of previous scan may be used to adjust classifiers or scan objectives to be used in subsequent scans.

Scanning for information according to scan objectives

Methods and systems are presented for performing data scanning in a heterogenous data storage environment. A data scanning process on multiple different data storages may be performed based on a data scanning request, which specifies certain data of interest to be detected during the scanning. First, sampled data records are scanned from each of the data storages. Based on analyzing the data in the sampled data records and the metadata associated with each data storage, a fingerprint may be generated for each of the data storages that indicates a likelihood that the data storage includes the data of interest. A second scan may be performed on the data storage only if the fingerprint exceeds a threshold. The data of interest may be detected in the data storages during the second scan of the selected data storages.

Customized data scanning in a heterogeneous data storage environment

Growing community of inventors

San Jose, CA, United States of America

Gaoyuan Wang