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Veritas Extends Reach of AI Compliance Tool


Veritas this week extended the reach of a compliance tool that makes use of machine learning algorithms to identify sensitive or inappropriate conversations to now include messages stored on the public cloud.

The Veritas Advanced Supervision module, available as an add-on to the Enterprise Vault.cloud archiving platform that the company delivers as a software-as-a-service (SaaS) application, now can be employed to analyze communications stored both on-premises and in public clouds.

David Scott, director of product management for digital compliance for Veritas, said that capability is important because more organizations are now opting to take advantage of low-cost cloud data to archive data. The challenge they face is that as the amount of data being collected continues to grow, it becomes impossible to manually inspect all the data to identify potential issues such as unauthorized conversations involving intellectual property or inappropriate activities such as gambling, he said. Machine learning algorithms now make it possible to analyze data at scale.

Obviously, organizations will want to narrowly classify the phrases that the Veritas Advanced Supervision module looks for to avoid the appearance of being too intrusive. The Enterprise Vault.cloud archiving platform makes it possible to automatically classify data in a way that enables a search for a specific topic, such as money laundering, to be narrowly defined.

In highly regulated industries there are now compliance mandates that require organizations to conduct such searches. The Veritas Advanced Supervision module simply makes it faster to conduct those required inspections at scale, noted Scott. In some cases, organizations are even going to far as to record voice calls that they later store in a text format for analysis, noted Scott.

Legally, all the data generated by employees belong to the organization that hired them. The fine line security professionals are trying to walk is the need to protect the organization without overly offending the sensibilities of employees, many of whom might opt to work somewhere else if they felt their organization was engaging in what could easily be viewed as “Big Brother” activity. Many of those same employees would also shift their conversations over to even less secure public platforms as a matter of principle, making it even more likely critical data might inadvertently be shared outside the organization when data loss prevention (DLP) systems are circumvented.

There is, of course, also a rising tide of data privacy legislation around the world, so organizations need to understand what communications they are allowed to capture. Most communications involve external participants such as customers, who might claim the archiving of a conversation is a violation of their privacy.

Regardless of regulation, however, it’s apparent data management and security are continuing to converge. As a longtime provider of data management tools, Veritas, is now extending its reach into the realm of data security. The challenge many organizations now face is determining not only how to manage their data but also who ultimately within their organization is accountable for securing it.



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