Sold by: Mphasis
Deployed on AWS
PII Anonymizer identifies Personally Identifiable Information (Name, SSN, Email, Phone numbers) in tabular data and masks them.
Overview
This solution identifies and anonymizes Personally Identifiable Information like Name, SSN, Email, Phone numbers from tabular data. The Solution is designed to work on structured data source.
Highlights
- ML based NER methodology to mask Personally Identifiable Information (Name, SSN, Email, Phone numbers).
- Safeguard PII data and ensure compliance to data privacy regulations.
- Need customized Machine Learning and Deep Learning solutions? Get in touch!
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $16.00 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $8.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $16.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $16.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $16.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $16.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $16.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $16.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $16.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $16.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
Legal
Vendor terms and conditions
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Content disclaimer
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Bug Fixes and Performance Improvement
Additional details
Inputs
- Summary
Input:
Following are the mandatory inputs for PII masking on structured data:
- The algorithm detects and masks PII (Name, SSN, Email, Phone numbers ).
- The input can be provided as a csv file (.csv) with 'utf-8' encoding.
- A column named 'column_list' must be there in csv file . It must contain names of the columns that require PII masking (refer sample input :https://tinyurl.com/y8p7q5g9 ).
- 'column_list' can have upto 5 column names only.
- Only First 1000 rows will be processed.
- Supported content types: 'text/csv'.
Output:
Instructions for score interpretation:
- Output is in the form of a ‘.csv’ file.
- In the Output file, Column names given in 'column_list' will be masked whereas other columns from Input csv file will be as it is.
- Supported content types: 'text/csv'.
Invoking endpoint:
If you are using real time inferencing, please create the endpoint first and then use the following command to invoke it:: aws sagemaker-runtime invoke-endpoint --endpoint-name "endpoint-name" --body fileb://sample.csv --content-type text/csv --accept text/csv out.csv
Resources:
Disclaimer: The personal details like names, email, phone_number, SSN, dates of birth, account number, addresses in the sample transcript provided are fictitious, and any resemblance to actual persons or their details is purely coincidental and unintentional.
- Input MIME type
- text/csv
See Input Summary
See Input Summary
Resources
Vendor resources
Support
Vendor support
For any assistance reach out to us at:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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