Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Many security professionals feel like broken records at this point when we say, “the threat landscape is constantly evolving”, and especially when we talk about how security operations centers (SOCs) are always trying to do more with less. But over the last couple of years, what we think of as standard security issues have evolved into several new, daunting challenges.

A Cloud data migration project can be a complicated procedure that requires much planning, coordination, and management to ensure successful outcomes. There are many risks to consider including data quality control, over-exposure, data loss and the costs involved, particularly when it comes to large volumes of specialized data. When an organization is considering a SharePoint migration to Microsoft 365 (M365), they must prepare their data to mitigate these risks to ensure a successful outcome.

The results are in, and Protegrity has officially been named the “Data Security Solution of the Year” by the 2021 Data Breakthrough Awards. Data Breakthrough is an independent market intelligence organization that recognizes the top companies, technologies, and products in the global data technology market today.

As the name implies, dynamic data masking actually masks data. Just as protective masks have obscured people’s smiles (and frowns) during the pandemic, this data-protection method covers sensitive data. People who shouldn’t see the data won’t see it.

Tokenization hides data. Sometimes data must be hidden in order to satisfy compliance requirements and customers’ expectations for data privacy. A form of data protection, tokenization conceals sensitive data elements so should an organization’s data be breached, the visible tokenized data—essentially a replacement for the valuable data—means nothing.A hacker will only see characters that are meaningless.

Spelling, let alone pronouncing, “anonymization” and “pseudonymization” is just the beginning. Vocabulary, however, will be the least of the challenges for organizations that ignore the business value created through the use of these data protection methods. Anonymization and pseudonymization are two ways to de-identify sensitive data, and each has a distinct purpose in the tightrope balance between fully using and fully protecting data and data privacy.

If you work in a financial organization that operates in the US, you’ll have heard the phrases Nacha and ACH. Together, these entities affect many of the transactions you’re responsible for — and dictate how, why, and when your business accesses sensitive data. But, what exactly are they? And, what’s the difference between the two? Read on to find out.

Only those hiding from the news, prospects, and customers can miss the data security and privacy challenges that are occurring. More businesses are relying on data analytics (garnered from data collection) for more and improved service and product offerings. More individuals want data privacy and security. More nations want their citizens protected from corporate tactics that rely on mining and scraping personal data. More customers want tailored experiences that only come through data analytics.

Enterprises require multiple tools for cyber defense, so network and information security staff often end up managing a patchwork of solutions, a blend of legacy and new technologies. If they find and deploy solutions that solve several business and security problems at once, they can reduce costs, logistics, and headaches while helping the business grow and innovate.