Data Classification & Protection powered by AI/ML

The power of artificial intelligence and machine learning at the service of information classification

Avoid data leakage by labelling data and automating the protection

Organizations need to classify their data to understand its value and determine its sensitivity level, prevent data breaches and critical incidents by adequately protecting said data, and comply with relevant industry-specific regulations (PCI, GDPR, etc.).

Most companies deploy theoretical approaches instead of realistic ones that consider the organization’s intricacies. At the same time, most organizations either rely on simplistic labels or utilize too many labels that ultimately confuse the users. Furthermore, outdated data classification systems disregard compliance with regulations and imply excessive dependence on the user to classify the data.

Sealpath’s approach to data classification

The power of artificial intelligence and machine learning at the service of information classification

  • It relies on a high level of classification accuracy through model pre-training for years with:
    • Industry data (financial, automotive, defense, aerospace, healthcare, etc.).
    • Various document types (invoices, CVs, intellectual property, etc.).
    • Regulation data (PCI, HIPAA, GDPR, CMMC, etc.).
  • It utilizes efficient algorithms to improve data classification accuracy: Support Vector Machines (SVM), Neural Networks, Logistic Regressions, Linear Regressions, Decision Trees, and Natural Language Processing (NLP).

Data classification accuracy improvement with industry data and user feedback

The classification of a file can vary significantly from one sector to another. Continuous training of AI models with industry data is vital. This training allows the ML system to decide the type of classification of a document after an inference over the set of parameters in a document or email. The trained model, jointly with powerful software specialized in data classification, helps minimize human errors, costs, and time in labeling corporate information.

These models fed with sectoral and regulatory data are continuously fed back and improved with user classification verdicts. This helps to correct the possible precision inefficiencies in a specific organization in different iterations.

  • The user receives suggestions about the classification level;
  • The suggestions enable users to avoid making mistakes in the classification process;
  • The users’ verdicts help continuously improve the process, and the improvement in accuracy accelerated at the rate of 8% per hour per user;
  • The user does not need prior training to classify documents.

The underlying anonymous data handling mechanism that allows this increase is unique, is not available in other products on the market, and was designed for the AI/ML-powered software from the beginning.

A flexible approach with 4 different data classification dimensions

The Machine Learning and Artificial Intelligence system on which it is based can give users suggestions regarding the following dimensions:

  • Data sensitivity: Classification based on the level of damage it can cause to the organization if it falls into the wrong hands. (e.g., Highly Confidential, Internal, Public, etc.);
  • Associated regulation: Classification based on content related to industry-specific regulations (e.g., PCI, GDPR, etc.);
  • Types of data: Classification based on financial data, PII, PHI, Intelectual Property, etc.;
  • Scope of dissemination:g., Internal Dissemination, External-Suppliers, etc.

 

sealpath data classification integration

A 360 approach that automates the protection of classified information

SealPath’s protection, combined with the robust AI and Machine Learning-powered classification system, streamlines an organization’s efforts to mitigate sensitive information errors quickly and cost-effectively, as follows:

  • The admin associates classification and compliance tags with SealPath-specific protection policies;
  • When a classified file with a certain level of sensitivity is detected, it will be automatically protected without user intervention;
  • Automatic protection is applied when editing a file via Microsoft Office or detecting tagged data on file servers, cloud storage systems, etc.;
  • Detailed reports about end-user activity in classification and protection are also available for the administrator.

The solution also allows visual labeling customization (font change, multiple colors, etc), configurable metadata, enforcement/warning to save files, print, send emails, etc.

Key differences with rudimentary data classification systems

  • AI/ML data classification suggestions;
  • Straightforward to use and deploy;
  • Accuracy continuously improved with industry data and user feedback;
  • Flexible approach with different data classification dimensions;
  • Data protection is 100% integrated, enabling automatic protection of tagged data.

The core benefits

  • It allows applying the most appropriate protection to prevent data breaches;
  • It enables business owners to understand their data footprint and control it wherever it travels;
  • It ensures compliance via an easy-to-use data classification system;
  • It allows users to classify their data with unprecedented confidence and accuracy;
  • It provides automated protection based on classification and compliance tags.

Integration with other data classification Solutions

SealPath is able to access the metadata of the files and interpret the classification level. This is so, both in the documents that users access and in the documents that are stored in file servers, or document managers. This integration allows you to join SealPath protection policies with classification tags.

Once classification tags and SealPath’s protection policies are linked, files classified with these tags will be automatically protected. SealPath integrates also with data classification solutions such as GetVisibility, Boldon James, Titus, Microsoft MIP, Tukan IT, Janus, Kriptos, etc.

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