Dark Data: A Glaring Concern for Security Leaders

Dark Data: A Glaring Concern for Security Leaders

Sensitive and confidential data is spreading throughout the environment at unimaginable rates due to the rapid expansion of private, public, multi and hybrid-cloud models. Organizational risk increases as the footprint of this type of data expand.

Multicloud frameworks have become mainstream during the past few years. Large volumes of data are increasingly being created, stored, and managed by organizations across various cloud platforms. Despite the size of this development, there is one stark and unsettling reality: Many businesses have limited or no visibility of the data stored on these clouds. The cause? Dark data. 

Identifying and analyzing all the data is incredibly challenging when enterprises build multi-cloud frameworks and distribute data across numerous containers and components. Dark data poses considerable security and compliance issues, which is not surprising. Data systems, the data that is stored in cloud components, and how this data is safeguarded cannot be easily identified.

Hence, businesses must move past the simple inventory solutions that only offer limited insights into cloud data. Adopting a more sophisticated strategy that delivers complete visibility into the company’s asset footprint and makes it possible for certain risk-reduction measures to be taken is essential.

Multicloud Environments Are Here to Stay

Multicloud systems considerably raise data storage and security concerns—this is the root of the dark data issue. Organizations typically use native tools to manage cloud inventory. Although useful, these technologies can’t detect dark data because their main objective is to provide native asset discovery. These content security policy tools do not offer multi-cloud visibility, either. As a result, when a company forklifts data from data, they risk the data turning dark.

This issue arises when businesses transfer data to their preferred cloud service providers without modifying the underlying data systems. Because there is no need to worry about changing the underlying schemas, infrastructure, or other components, the process is quick and easy, but security and data compliance issues ultimately increase.  

Dark data may end up dispersed over several cloud service provider accounts, geographical regions, and legal jurisdictions as the volume of data increases and the footprint of multi-cloud systems expand. Compliance with privacy, security, and data compliance rules, regulations, and standards become much more challenging when a business lacks insight into its data footprint. 

Also Read: What Security Leaders Need to Know About Zero-Day Attacks

Breaking Down Data Silos and Eliminating Out Dark Data

The ability to detect dark data and address it more efficiently is central to data security, governance, and privacy best practices. A company can enhance its data storage and access management frameworks by laying the proper foundation.

Here are six essential measures for eliminating data silos and eradicating dark data. 
  • Identifying all native and shadow data assets that are spread out among the main cloud service providers is crucial. Companies must extract them into an asset inventory after they are discovered.
  • Risks must be detected, and any exposures must be fixed. Organizations must also identify compliance and security posture risks related to dark data assets.
  • Following the categorization and labeling process, businesses can search for and map out the distribution of sensitive data pieces across both unstructured and structured data systems. 
  • A company can now create a relationship map between the identified personal data and its owners. With this visibility, businesses can fully understand their security threats and regulate access at a granular level.
  • With personal data mapping in place, companies can promptly and accurately fulfil Data Subject Requests (DSRs), consent management, and breach notifications.
  • At this point, companies can set up automated procedures and workflows to adhere to data privacy laws and restrictions. 

By putting these best practices into action, dark data issues can be handled holistically and seamlessly. Companies can embrace a more enlightened approach to privacy, security, and governance by shedding light on dark data.

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