Addressing Key Use Cases with the Titaniam Protect Suite
Titaniam for SaaS Providers
Cloud SaaS providers are entrusted with valuable enterprise and end user data.
Providers present both a security as well as a data privacy risk since they face insider, outsider and human error based threats, just like any other enterprise. Also, at a fundamental level, provider access to end user data, can be a source of privacy
concerns. However, providers often legitimately need some kind of access for
maintaining and providing the services themselves.
Titaniam enables automatic secure and private defaults for all sensitive data given to
the SaaS provider. Titaniam Protect translates this data into a secure and private
format prior to ingestion and storage. Depending on the SaaS backend, this can be
done via ARCUS (platform plug-in), PANTHER (standalone API) or RIPPLE (proxy).
Once ingested, the data can be sliced, diced, indexed, transacted, and manipulated
without being brought to clear text. Data protection keys can be generated by the
enterprise and managed inside a vault. Access to clear text data can be tightly
controlled by configuration and policy.
Machine Learning models require real production data. In order for models to be
built, trained and deployed, enterprises need to provide data scientists, ETL
developers and data engineers with access to data. Further, as data scientists are in
short supply, enterprises complement internal resources with consulting services
that perform data science work such as price optimization, demand forecasting, and
other types of analysis and scoring. The underlying data is currently provided to
internal and external parties in clear text, creating massive security and privacy
Titaniam enables enterprises to secure production data prior to sharing it with data
science teams. Production data can be de-identified and sensitive data secured using
redaction, masking, tokenization, encryption and entanglement, via Titaniam Protect
PANTHER (standalone API service), ARCUS (data platform plug-in) or RIPPLE (proxy
service). Once this is done, data scientists can use Titaniam Protect MICRA (language
library for Java, Python or C#) to model and manipulate this data without bringing it
to clear text. Titaniam Protect takes an inherently exposed ML process and
immediately makes it secure and private.
Titaniam for Data Science
Titaniam for SOC Privacy
The modern SOC integrates event data from scores of applications with threat feeds
and user behavior data to create events, alerts, and security intelligence. This data is
used to identify and respond to security incidents. SOC data often includes both
direct PII as well as indirect but extremely rich private information in the form of
user profiles and behaviors. Having this type of data freely available in clear text
creates both privacy as well as security risk. Addressing this risk is not easy since the
core operations of the SOC require this data to be available for investigations.
Titaniam enables incoming event data to be transformed into protected formats
before being stored. This can be done via Titaniam Protect PANTHER (standalone API
service), or ARCUS (data platform plug-in). Once the data is ingested, analysts can
continue to search and analyze this data without the use of clear text, thus
maintaining its security and privacy. If the investigations require specific data items
to be revealed in clear text, this can be easily enabled by either ARCUS or PANTHER
depending on the deployment. Titaniam Protect takes the existing complex
ecosystem of products inside the SOC and enables immediate security and privacy
The interception and analysis of network traffic data is a key part of the security
toolbox . Network packets, reveal a lot about users on the network. Source and
Destination IP and MAC addresses, hostnames, URL’s and other types of metadata
can be tied to specific users causing privacy issues internally and security issues if the
data gets out to external parties. NIST classifies IP Addresses, MAC addresses and
other device identification data as PII since it can be tied to specific individual users.
Titaniam converts all fields that can be linked to user identity and behavior into
protected fields. Depending on the backend system, Titaniam Protect PANTHER
(standalone API service), or ARCUS (data platform plug-in) can be utilized. Protected
data can still support all the analytics needed by the intrusion detection function,
while maintaining end user privacy and providing additional security. Clear text data
can be computed as needed based upon configuration or policy.
Titaniam for Network Analytics
Titaniam for Data Sharing
Enterprises are often faced with scenarios where valuable data from core systems needs to be shared with other internal teams or with external collaborators for the purposes of analytics or other supporting functions. Once the data is outside the core system, enterprises tend to lose control over both its circulation as well as its protection. This raises many tough questions with respect to security, privacy and data ethics.
Titaniam Protect can be used to protect datasets prior to sharing. By using Titaniam Protect PANTHER (standalone API service), or Titaniam Protect ARCUS (data platform plug-in), enterprises can convert designated fields into formats that are either completely redacted or converted to a protected form. The data can then be shared with third parties who can manipulate it without creating additional security or privacy risk. If the data needs to re-identified downstream, this can be done through Titaniam Protect PANTHER.
The day-to-day functioning of organizations require the use of countless spreadsheets that house inordinately large volumes and varieties of data much of which is either direct PII or otherwise sensitive. Whether is Finance data, HR data, or even COVID-19 based PHI from tests that many employers are now forced to gather and record regularly, sensitive data in spreadsheet is impossible to control and manage and creates large areas of exposure for organizations.
Titaniam provides a simple, low cost and highly effective solution using Titaniam Protect ARCUS on top of Elasticsearch, that accepts data from spreadsheets and makes it available for search and manipulation while keeping it protected even while it is in use. Using a variety of data protection techniques including traditional encryption, tokenization, masking, redaction, and data entanglement, Titaniam enables the enterprise to utilize valuable data for day-to-day work while reducing the risk that would otherwise be associated with using that data in clear text.
Titaniam for Secure Analytics
“So many data breaches and privacy issues happen because of inappropriate access to valid credentials. If the attacker has the creds to access an account, then it doesn’t matter if the data-at-rest is encrypted. By providing data-in-use protection, Titaniam is positioned to make a tremendous impact on data security and privacy as data lives and naturally flows through an enterprise.”
Chief Strategy Officer, Cobalt.io
"With the growing importance of data privacy, the fact that vast majority of data breaches braking place with valid credentials, and the need for companies to do a better job, Titaniam fills an important need to protect valuable data while it is being used"
Venture Capitalist, Cybersecurity thought leader