Dec 30
Data discovery management to meet governance, regulation and compliance.

Sensitive data has a considerable economic value to businesses and they must manage it appropriately. Protecting that data is of utmost concern because organizations risk substantial fines from regulators or damaging its brand reputation (Yahoo, Marriott, Equifax, etc.). As result, organizations are primarily driven to protect their network because of the sensitive data they store.

At the core of all successful data security management programs are an automated data discovery process which can accurately locate sensitive data so that it can be most effectively managed and protected. Generally most of that sensitive data are stored on workstations, file servers, database's and cloud repositories and the breadth of where data can be stored has grown significantly from just a few years ago. The exceedingly large number of individuals involved in the handling of sensitive data makes appropriate data management very challenging. It's obvious you can't protect these assets unless you know where this sensitive data resides.

In my 20+ years of operational data management and security, the most successful data management and governance programs have included a unified set of information security tools and a governance and compliance process. This process will include many components for its success however the most effective components in this process generally involve a good user awareness of the sensitive data used, the data classification or sensitivity of the data, a data governance process which includes policy, best practices, and standards, and IT systems used to augment data security protection strategies. With these key processes in place an organization can be most successful and meet internal IT policy, governance, regulation, and compliance needs.

IT Data Management

The most effective data management protection programs consist of the ability to report on the location of and types of sensitive data. There isn't a single best process or tool to protect any network however there are numerous technologies including DLP, Firewall, Encryption, Patch Management, IDS, Antivirus and most importantly a Data Discovery mechanism. The most effective approach to good data hygiene and the protection of sensitive data is to know what it is your protecting and to what extent to leverage those IT security processes. With the effective use of a data discovery tool you can complement and extend your data protection stance, the core of all these processes being a data discovery toolset such as the Spirion Sensitive Data Management. The following demonstrates how having a sensitive data discovery process can complement your existing data security posture.​

DLP – These technologies can protect sensitive data in motion, however are inundated with false positives and require considerable resources to manage. Complement and extend the DLP's capabilities by augmenting it with a at rest data discovery tool like Spirion so that the data can be more accurately discovered and leverage the persistent meta tags imbedded in that sensitive data to more accurately accomplish the data in motion protection process.

Firewall – This is the most common type of technology used. However knowing exactly which file server(s) contains the most sensitive (PCI, CCPA, GDPR, PII, etc) data allows the most effective use of FTE resources to more granularly define those firewalls and comply with regulators compensating control requirements. It's imperative to know what it is you're protecting to be successful at protecting access from those users or application that should not have it.

Encryption – Identifying what really needs protected through encryption will reduce the complications of managing various data repositories.

Patch Management – Which storage devices do we need to be more aggressive with patching when a zero day occurs?

Intrusion Detection (IDS) – What sensitive data was on the device when the intrusion occurred!?

Antivirus – What sensitive data was on the device when the malware infected your device with the Trojan six weeks ago?

Sensitive data management is not solely an internal IT security or policy driven process. Effective data management involves people, process, and technology. Good governance of this data is achieved when you can report on where and what types of sensitive data are being stored. Being able to do so will help with avoiding those costly mistakes and damage to a company's reputation.

Compliance and Regulation

This is a People, Process, and Technology driven challenge and the value of sensitive data discovery extends beyond the IT management of data. Data discovery tools are most useful in the compliance and regulation landscape. A data discovery tool will reveal what sensitive data was on a compromised, lost, or stolen device months ago should the situation arise which allows an organization to react more favorably to legal, compliance, or IT security process. Should a PCI audit occur you can work with a QSA to scope those devices under the PCI umbrella. If your organization must comply with GDPR, CCPA, or any number of US state laws and you receive a DSAR request you can act on that. The scope of value gained by having a process at the center of all sensitive data discovery is most valuable.

Data has grown exponentially in size and complexity and having an automated data discovery and reporting process is essential to be successful. New privacy regulations are being implemented around the globe at an increased pace and not all are prescribe identical requirements however all share a common requirement; know where and what sensitive data is being stored. Plan ahead and have a data discovery tool in place!

CCPA will take in effect January 1st of 2020, however you still need to know what and where that data was 1 year previous. GDPR has been in effect since May 25th, 2018 and you have already seen huge fines for noncompliance. The NY SHIELD Act is very similar in scope to CCPA, along with numerous other state data protection laws that have emerged in just the first 6 months of 2019 (See US State Data Protection Laws data sheet).

With so much more to consider in the data management governance, regulation and compliance landscape it can be overwhelming to decide where to start. More to come on that!

I welcome your feedback and look forward to your different perspectives?

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