Protecting Data in the Cloud
Today’s cloud-driven, always-connected world enables organizations to be very agile but is also putting data integrity at risk
By: Raja Patel
Aug. 28, 2014 01:15 PM
The cloud plays an integral role in enabling the agility required to take advantage of new business models and to do so in a very convenient and cost-effective way. However, this also means that more personal information and business data will exist in the cloud and be passed back and forth. Maintaining data integrity is paramount.
Today's approach to security in the cloud may not be sufficient; it doesn't focus on putting controls close to data, which is now more fluid, and it doesn't discriminate one set of data from another. All data is not created equal and should not be treated in the same manner; a one-size fits all model doesn't work.
In this always-connected world, protection measures in the cloud need to focus on what really matters - the type of data, how it is used, and where it goes.
Tier 1, Regulated: Data subject to regulation, or data that carries with it proprietary, ethical, or privacy considerations such as personally identifiable information (PII). Unauthorized disclosure of regulated data may have serious adverse effects on an organization's reputation, resources, services, or individuals and requires the most stringent level of control.
Tier 2, Commercial: Industry-related, ecommerce or transactional and intellectual property data whose unauthorized disclosure may have moderately adverse effects on an organization's reputation, resources, services, or individuals. Commercial data requires a moderate level of security.
Tier 3, Collaborative: Collaborative and DevOps-type data that typically is publicly accessible, requires minimal security controls and poses little or no risk to the consuming organization's reputation, resources, or services.
Using this model, security teams can strategically partner with business users to understand requirements and determine the right approach for their organization. Small to mid-sized organizations, enterprises, and service providers can apply this model to begin classifying their data based on contextual attributes such as how the data will be accessed, stored, and transmitted. Once the data is classified, they can then apply appropriate data protection measures focused on protecting work streams and transactions that continue to evolve to enable business agility. Given that most of today's data breaches are a result of user-access issues, security considerations such as Identity and Access Management, Authorization, and Authentication are critical.
The Data Integrity Challenge
Business departments are increasingly encouraged to find efficient and innovative ways to generate new business. This requires identifying new applications and ways to support the business anywhere and anytime. Business users often make the decision to use the cloud before involving IT since they can get up and running in a fraction of the time and cost it would take to provision in house.
With this unprecedented change in operations and infrastructure comes an unprecedented need for ensuring data integrity - ultimately working through the life cycle of data that can, at any point, be within the confines of a company, out to a network of partners and suppliers, or floating in a cloud. The challenge in this fractured landscape is that the perimeter is amorphous, but legacy security solutions are not; designed for a time when there was a more well-defined perimeter. The result is that attackers now use various techniques to bypass traditional perimeter-based defenses and compromise data - be it through tampering, stealing, or leaking data. Point-in-time defenses are no longer sufficient.
To effectively protect data wherever it may be, defenses must go beyond simply blocking and detection to including capabilities such as data correlation, continuous data analysis, and retrospective action when data has been found to have been corrupted, tampered with, or exfiltrated.
A New Approach to Applying Controls
Let's take a closer look at the advantages of applying controls to protect data based on this model.
Pervasive translates into:
Today's cloud-driven, always-connected world is enabling organizations to be very agile but it is also putting data integrity at risk. IT teams need to quickly adapt to this new way of doing business despite having less control of the endpoints and the data. Traditional data protection models fail due to their inability to discriminate one set of data from another. By putting in place protection measures based on the type of data, how it is used, and where it goes, and backed by a security model that is open, integrated, continuous, and pervasive, organizations can take advantage of new business opportunities the cloud affords without sacrificing data integrity.
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