Top Five Challenges for CISOs to Address with Dark Data

Dark Data

Enterprises already struggle to manage and secure the data they are aware of having, so dark data—the data a company unintentionally produces—presents a unique set of challenges. Finding ways to access dark data, make use of it, keep it secure, and stop attackers from utilizing it against the company are crucial among these issues.

Data is often perceived as the new oil, making it a valuable asset for any business; therefore, it is astonishing how much of it gets wasted. According to The State of Dark Data by Splunk, a third of the 1,300 respondents believed that 75% of their data was dark. Numerous businesses are missing out on the potential commercial value that can be obtained from a vast amount of data that is mainly mishandled and untapped, according to other similar surveys that have been conducted.

Trying to deal with dark data presents both opportunities and challenges in equal measure. Firms are better prepared to utilize the possibilities of dark data when they are aware of these.

Anonymous data

People frequently believe that anonymizing data is the first step in data security. This means that while all the data points may be present, they will delete any account numbers, email addresses, names, and other identifying information from the person’s data to prevent direct identification.

An identifier is any collection of data points. An identifier is five data points connected to one individual, irrespective of the name used. A single identity is imprinted on the globe if someone is known to get out of bed, take a stroll, yawn, sneeze, kick a rock, and then go back to sleep.

Storage expenses

One of the main factors influencing the proliferation of dark data has been the decrease in storage costs. But data storage still represents a considerable cost to any large-scale firm.

All the truer with the pay-as-you-go paradigm of the public cloud, where monthly fees can gradually creep up surreptitiously before eventually ballooning out of control.

Also Read: Top Cloud Data Security Policy Challenges IT Leaders Should Look Out For

Businesses should take steps to eliminate duplicate, obsolete, and other redundant data through the use of deduplication technology, retention security policies, and technologies that provide them with insights into data usage trends in order to help keep storage expenditures down.

Visibility of data

Without comprehensive insight into the data, data governance, data compliance, and cost-effective storage would not be possible. Dark data will appear in a variety of formats in a business IT system, dispersed across a number of storage services on both cloud-based and on-premises infrastructure.

Companies will require systems that can combine data from all their many data sources to deliver consolidated insights through a single pane of glass in order to get around this complexity.

Data intersections

A person’s name could appear amid another group of data due to the vast amount of information available. The anonymized data can then be given a name when these data points connect and the two sets are cross-referenced. Statistics offers more complex approaches to de-anonymizing data, such as drawing a Venn diagram of many data sources to see which ones match.

Also Read: How a Modern Cybersecurity Strategy Can Reduce Complexity and Costs  

Regulatory compliance

Dark data could include personal information, making it potentially subject to relevant privacy regulations. To properly handle any personal data in their possession in accordance with data protection regulations, companies will need a mechanism to find and categorize it.

If so, enterprises should take action to safeguard it and amend their privacy program as necessary. Alternatively, if firms are not actually using it, then they may consider swiftly removing it.

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