5 Data Security Management Fundamentals

Originally published by New Context.

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Data is a dynamic, living part of an organization. With it, companies can predict customer behavior, prepare for and better meet industry trends, and improve overall revenue. However, with those benefits comes the risk of a data breach. In 2019 alone, data breaches increased by 54%, and that number will only grow due to the rapid digital transformation of 2020. These issues wreak havoc on a company’s bottom line, with the average data breach costing an organization $3.86 million. This is why data security management is such a vital part of any company today. 

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Data protection is more challenging now than it’s ever been. Organizations see the value of it for a wide range of applications, both internal and external. But bad actors also see its potential and are only doubling their efforts to break past company protections. A holistic, dynamic approach to data security is the best way to prepare for the threats that emerge in the new environment. 

The What, Where, Why, and Who of Data Security Management 

A data audit is the first step to data security management. Completing one helps leaders organize their digital asset strategies. Specifically, the audit should cover four key components: what, where, how, and who.  

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With a complete understanding of existing data and its management, it’s much easier for business leaders to create solutions for controlling it. A lot of this is accomplished through a holistic approach that combines observability with security. 

5 Fundamentals in Data Identification and Protection 

Today’s data is decentralized. That makes it very challenging to manage. However, an integrated approach to security helps build in protocols that grow as data does. This integration becomes scalable and flexible by adding in visibility, security as code, automation, monitoring, and assessment. 

#1: Visibility

Data should be accessible for those who need it and protected from those who don’t. Encryption is a vital part of this as it acts as a second layer of protection. In the event of physical theft of company equipment, like a stolen server or lost employee laptop, encryption ensures that data is not usable. 

Data tagging also falls under visibility. Through this, organizations can better prioritize their data by marking it based on its needs. This also feeds into automation, as policies can be established around specific tags to ensure it is treated based on required compliance standards or company protocols. 

#2: Security as Code 

Security as code takes DevSecOps a step further by making protection a layer of any program development process. Gates, checks, and tests are part of the overall code from the very start. This ties in closely with infrastructure as code, another method of making security and programs scalable and manageable even in a decentralized space.

Security as code can also integrate required compliance measures in various industries. Business rules based on these requirements are established and then built into the framework. This strategy ensures that the program is always up to date even as compliance needs change.

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#3: Automation

Automation is where Security as Code policies get executed and enforced. In its simplest form, you examine your current infrastructure, looking for opportunities to harden it against potential exploits by making changes via programmatic code. Hence the name, “Security as code.” That code lives in the automation pipeline, which will enforce the changes consistently with every release.

Automated policy enforcement is also crucial in data management. The security configuration should be based on preset policies that are unchangeable without administrator approval. With this, the company can take an exceptions-based reporting approach, where only anomalies require attention rather than everyday events. 

#4: Monitoring

Monitoring is about managing both internal and external threats through observation. Immutable logs ensure system administrators understand how users access their system and can help to find trends indicative of problematic behavior. In all cases, it is imperative that monitors run on systems adjacent and independent of the systems under observation, to avoid attacks compromising both the target and observers in one swoop.

Cyber threat intelligence allows companies to share information about emerging threats. As these threats typically occur within the same industry, an open-source platform where their issues are communicated and resolved is beneficial. In support of cyber threat intelligence delivery, New Context has contributed to the STIX and TAXII standards, and is an OASIS sponsor.

#5: Assessment 

A third-party assessment can help firms better understand their data needs and create more accurate, reliable protocols in governance. As it can be difficult for internal workers to see gaps, a third party provides a new perspective. Due to their heavy industry focus, third party assessors tend to stay on top of the most recent innovations in security, enabling clients to leverage their expertise to the benefit of their own applications.

Data security management fundamentals must center around integration, automation, and observability. This is an approach that New Context takes with our secure compliant data platform. A scalable, flexible strategy for data management provides continuous improvements as threats evolve and needs change.