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sensitive data

Another Casualty of Prevalent PHI Breaches

Valley Hope Association’s mission is to help people overcome their dependence on alcohol and drugs. At their 16 addiction treatment centers, therapists and staff focus on helping people remove the triggers that drive their addictions in a safe and secure environment. But like so many non-profits, Valley Hope’s good intentions for protecting their patients weren’t enough to prevent hackers from exploiting their IT security weakness. Last week, 70,000 Valley Hope…

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This entry was posted in Healthcare, Sensitive Data and tagged PHI, sensitive data on February 14, 2019 by Bill Kuypers

Smaller Sensitive Data Footprints Lead to Trusted Reputations

Smaller Data Footprints Lead to Trusted Reputations The well-supported adage is that it takes years to get a loyal customer and only seconds to lose them. One of the biggest mistakes you can make is putting your customers’ personal information at risk. A recent survey conducted by Ping Identity reveals many consumers are making drastic changes to the ways they interact with companies and secure their own personal data following…

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This entry was posted in Sensitive Data and tagged data footprint, sensitive data on February 6, 2019 by Bill Kuypers

Data Protection Must be the Number One Enterprise Focus in 2019

Sensitive data protection continues to gain priority for many enterprises, especially from the C-suite perspective. The rise of privacy regulations such as the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) have increased the urgency to manage sensitive data — and to a greater extent, all data. Headlines in 2018 trumpeted major hacks and data breaches impacting millions of customers and smearing the names of several multinational…

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This entry was posted in Sensitive Data, sensitive data management and tagged sensitive data on February 1, 2019 by Abey Joseph

How To Identify Types of Sensitive Data

Sensitive data falls into two broad categories: regulated and unregulated data. Regulated data is always sensitive, though to varying degrees, and should always be classified. The vast majority of unregulated data (which includes all publicly known information) is not always sensitive. However, unregulated data can also include highly sensitive information (e.g., company confidential data, intellectual property or sensitive data unique to the organization), so you must apply your data classification process…

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This entry was posted in Sensitive Data Engine, sensitive data management, Sensitive Data Manager and tagged sensitive data on January 17, 2019 by Douglas Ribback

Sensitive Data Management Maturity – The DLP Missing Link

At the 2016 RSA Conference in San Francisco, CA, Todd Feinman, CEO and Gabriel Gumbs, VP of Product Strategy presented on Sensitive Data Management Maturity – The DLP Missing Link. As a company and with the help of industry professionals, we created a Sensitive Data Maturity Model to help organizations identify where their data is, who owns it, what should be done with it, and how much of it exists….

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This entry was posted in Classification, Conferences, Data privacy, Data Security, DLP, sensitive data management, Sensitive Data Manager and tagged Data Classification, Gabriel Gumbs, PCI, PHI, PII, sensitive data, sensitive data manager, Sensitive Data Maturity Model, Todd Feinman on March 24, 2016 by Douglas Ribback

Eight Things to Consider When Classifying Your Sensitive Data

Sensitive Data Classification Data classification is simple—it entails taking security measures by assigning a level of sensitivity to each piece of information, making it easier to locate and retrieve. Classifying data is essential in enabling enterprises to make sense of their vast amounts of data. Without sensitive data classification, an organization treats all data as if it were the same. You can’t know the level of sensitivity of any specific…

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This entry was posted in Classification, data breach, Data privacy, Data Security, PCI-DSS, Regulation, Sensitive Data Manager and tagged classification, Compliance, data breach, data breaches, data loss prevention, data privacy, HIPAA, PCI DSS, sensitive data, sensitive data manager on February 25, 2016 by Douglas Ribback

Introducing Sensitive Data Manager 9.0

In 2016, we announced Sensitive Data Manager 9.0, our Data Loss Prevention (DLP) solution. In addition to offering the highest accuracy of data discovery and data classification, this release adds powerful, custom data discovery capabilities that reduce the burden on IT Security by allowing organizations to locate their unique sensitive data. Sensitive Data Manager 9.0 increases automation of classification and DLP security controls, reaching deep into cloud environments to further data…

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This entry was posted in Classification, Data Security, DLP, Sensitive Data Engine, Sensitive Data Manager, Video and tagged data loss prevention, organizationally unique sensitive data, sensitive data, sensitive data manager, Todd Feinman on February 9, 2016 by Douglas Ribback

Forrester Report: Understand The State Of Data Security And Privacy: 2015 To 2016

Forrester recently released an insightful report Understand The State Of Data Security And Privacy: 2015 To 2016, based on hundreds of discussions with security experts. The in-depth research of the data security industry highlights which core data security technologies are in demand for 2016 and how our behaviors and motivations make data loss inevitable. It also covers why safeguarding the customer experience is essential for building trust, and why a…

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This entry was posted in Breaches, Classification, consumer privacy, data breach, Data privacy, Data Security, DLP, Regulation and tagged classification, data breach, data privacy, forrester, PII, privacy, sensitive data on February 4, 2016 by Douglas Ribback

How Are You Locating Your Organization’s Unique Sensitive Data?

Locating credit cards, personally identifiable information such as SSNs and drivers licenses is a staple of our AnyFind® technology. AnyFind narrows the likelihood of a positive match and eliminates false positives through a series of validations while looking for those discrete pieces of data the way a human would. For example, when looking for a Social Security number, if you simply look for a 9-digit number you get a lot…

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This entry was posted in Classification, data breach, Data Security, DLP, risk management, Sensitive Data Engine, sensitive data management, Sensitive Data Manager and tagged AnyFind, Data Classification, data loss prevention, discovery, infographic, organizationally unique sensitive data, sensitive data, sensitive data engine, sensitive data manager on January 26, 2016 by Gabriel Gumbs

Predicting Cybersecurity Trends in 2016

This has been a busy year for cybercriminals: There were more than 600 breaches in 2015 that involved identity and data theft. Our customers, colleagues and fellow security professionals have asked us what we think 2016 will look like, so here are our cybersecurity predictions for this year. These are insights and extrapolations for the serious practitioner who makes his or her living from keeping other folks safe online. Staying…

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This entry was posted in Breaches, Classification, data breach, Data privacy and tagged Compliance, data breaches, sensitive data on January 14, 2016 by Douglas Ribback
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  • The Lucrative Cost of Cybercrime of PII
  • Oklahoma Breach Exposes Decades Old Records
  • How to Determine the Sensitivity of Information
  • Data at Rest Data Loss Prevention for Healthcare
  • Another Casualty of Prevalent PHI Breaches

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