Enterprise Content Analysis and Metadata Tagging
Meet the next-generation enterprise metadata tagging tool, with built-in OCR and machine learning
Search And Protect All Enterprise Content
Centralize The MLS Data Transfer Process
Scan Network Locations For Spilled Data
Integrate With Content Management Systems
How to protect company sensitive information, while also making it discoverable?
It’s important to protect a company’s most sensitive secrets. Every organization has information that it considers proprietary or confidential. Many organizations also manage sensitive customer data, such as credit card numbers, social security numbers, account numbers, and health information. And despite the best efforts of technology and policy, sensitive data is occasionally exposed — and the ramifications are sometimes severe. Competitors may gain access to a company’s most valuable secrets. Customers may lose confidence in a firm’s ability to protect their data. And the damage done to a company’s reputation may be expensive and permanent. Sensitive documents can be vulnerable in even highly classified environments.
It’s equally important that organizations be able to access valuable information in a timely fashion. This is an exceptionally tricky problem, as most files are not properly tagged with useful metadata. Most organizations rely on full-text search, which frequently results in overwhelming search results. Also, many files (such as pictures, videos, and scanned PDF documents) are not searchable — nor are documents containing pattern-based information. And without proper metadata tagging, sophisticated technologies like digital rights management (DRM), attribute-based access control (ABAC), and content targeting become completely ineffective. These limitations result in losing potentially valuable data down deep content gravity wells.
There are a number of moving parts that make the problem of controlling data dissemination especially difficult, including:
SIFT™: Helping Keep Sensitive Data Secure
SIFT™, from Aerstone Labs, is automated metadata tagging software, designed to identify keywords in files of any kind, based on a centrally-maintained list. SIFT™ also ships with an advanced machine learning algorithm that supports identifying specific shapes in pictures and video files. SIFT™ is designed to protect an organization from accidentally exposing sensitive data, while making all information properly discoverable. SIFT™ can be used as a stand-alone portal, or integrated seamlessly with existing content management systems. Once configured to search for the kind of data an organization considers sensitive, based on keywords or regular expression (RegEx) patterns, SIFT™ processes and tags files with useful and specific metadata. SIFT™ natively supports both searchable documents (e.g., MS Office) and non-searchable assets (e.g., pictures, video, and scanned PDFs).
Key Product Features
Supported File Types
- Support for a wide range of common file types, including most Microsoft Office and Adobe documents.
- A built-in OCR engine, to support scanning for text in pictures and scanned PDF documents.
- A modular design, which easily allows extending support to additional asset types.
- Several ways to scan documents, including browser-based manual and bulk scanning.
- Restful API for inline deployment with document management systems and high assurance guards.
- A customizable set of scanning rules, which supports scanning documents against a centralized list of keywords.
- Full support for both static and pattern-based keywords, like SSNs or credit card numbers, based on industry-standard regular expressions.
- Tag file metadata with discovered keywords, to support enterprise search and security solutions like digital rights management, data loss prevention, or attribute-based access control .
Auditing and Reporting
- Scan network locations for spilled data against enclave keyword rulesets, with recursive file ingest.
- Highly customizable auditing and historical reporting, with drill-down capability.