What is Data Security?

Digital data is at the fulcrum of businesses today, with the big data market expected to reach a massive $103 billion by 2027.

Meanwhile, the number of data breaches have increased correspondingly. In the United States, the number of data breaches has gone up from 157 in 2005 to 1244 in 2018 — exposing 446.5 million records and presenting a huge concern for companies trying to protect their data.

With data security assuming center stage like never before, let’s understand what it means, it’s importance, and how to safeguard data from possible attacks.

What is data security?

Data security is the collection of measures taken to prevent data from becoming corrupted. It incorporates the use of systems, processes, and procedures that keep data inaccessible to individuals who may use it in harmful or unintended ways. Breaches in data security may be small and easy to contain, or large and cause significant damage.

Data security applies to both individuals and organizations. For an individual, a possible breach could involve identity theft or stealing personal information such as credit card details. 

At an organization level, there are many ways a breach can happen. Examples include cases of ransomware, in which hackers expect monetary returns, and plain malware, in which hackers aim to disrupt business.  

The challenge today for most companies concerns fragmented data across multiple systems and platforms. Mass migration to cloud and usage of SaaS applications have huge benefits in terms of efficiencies and costs, but it also means relegating control over security to a third-party provider.

This means there are multiple entry points for a hacker, and callous management of confidential data in even a seemingly trivial scenario could risk the company and its customers’ data.

The importance of data security

The numerous gateways to data breaches can result in substantial losses to companies in the form of customers, reputation, and money. It’s reported that almost 60% of small and medium businesses will shut down within six months if their data is lost. 

This was evident in the case of Ma.gnolia, a bookmark sharing website, which lost all user data in a crash that took down the company’s database servers. Even though Ma.gnolia had backups, the corrupted files synchronized with the backup too, rendering them unusable. With just one terrible incident, the company went from an engaging and user-friendly website to a non-existent one.

Large companies have had their share of breaches too. Yahoo, for example, encountered a data theft in 2013. Although the impact was initially estimated to be much less severe, by 2017 it became apparent that all of Yahoo’s three billion user accounts had actually been compromised. This had its repercussions in that Verizon, which was poised to buy Yahoo at that time, lowered the offering price significantly from its initial offer. 

Reputation and financial impact aside, data security is critical to ensure compliance against regulations such as the GDPR (for data related to users in European Union), HIPAA (for healthcare data), The Sarbanes Oxley Act (for the financial industry), and PCI-DSS (for credit card and payments data). Non-compliance can result in huge penalties to be paid to the government and also loss of business.

5 types of data security

Now that we have established the ‘why’ aspect of security, let’s look at the ‘how’. The scope of how to go about implementing data security is wide and hence, one single approach cannot plug all possible loopholes. 

That’s why we rely on multiple techniques to address this issue. Let’s look at a few common types of data security. 

1. Network layer: As the first level of protection, organizations need to secure their TCP/IP layer to guarantee that only the right set of people gain access into their network. Protection of email gateways, wireless networks, mobile devices, and VPN layers come under the purview of network security.Firewalls, access control layers, network segmentation, and anti-virus programs are some of the methods that help achieve this. Encryption of data packets using IPSec protocol with underlying cryptographic algorithms is another example of shielding networks.
2. Application security: An non-secure application installed on your mobile device can expose all private details stored on the device. Similarly, an application with a vulnerability could become the entry point for an attacker to access the rest of the company’s data. For example, hardcoded passwords in source repositories are more common than one might suspect. Many companies use open-source code and a large number of third-party applications. It’s critical to evaluate if these tools and apps are devoid of any risks before bringing them into the company’s umbrella. 
3. Data masking: It’s essential to focus on how data is persisted or passed around between systems. Confidential data always needs to be obfuscated or encrypted so that a person with bad intent may not misuse it. Masking and storing the data in parts ensure that while the data makes sense internally, it remains anonymous to a hacker.
4. Data deletion: There is a lot of stray and unnecessary data lying around in systems that make their maintenance challenging. For smooth data governance, data needs to be frequently cleaned up, ensuring its integrity. For example, if a banking customer discontinues his account, a cleanup job should remove access to all services that the customer may have. Regulations such as the GDPR make it mandatory for companies and their vendors to implement this.
5. Recovery of lost data: Preventing data loss during disasters and thefts is critical for business continuity. Diversifying data centers across the globe helps to change the primary location in the event of an incident. Even if there is data loss, backup and recovery mechanisms need to be in place to bring the business back on its feet. 

In the case of cyber attacks that result in data loss, such data retrieval methods can significantly help reduce the exposure of the company involved.

Data security solutions: crucial capabilities and features

The traditional approach to secure data has been to work with diverse tools that address isolated problems. However, a cloud-native solution with data integration features is the need of the hour in today’s complex data landscape. 

The objective is to have a single platform or tool that consolidates data from multiple sources and enforces validation and governance policies in place. This approach avoids data quality issues such as redundant and orphaned data that could eventually put the company at risk. Also, the measures to ensure data integrity help customers gain complete trust over their data.

In addition, such a tool should be able to scale to growing volumes and promote compatibility with various cloud-based applications that most organizations leverage to run their day-to-day business.

Most importantly, it should be a state-of-the-art security solution that automatically provides compliance with various regulations such as the GDPR or HIPAA. For example, check whether PII fields are encrypted.

The cloud and the future of data security

Most organizations have moved or are in the process of moving a major share of their data to the cloud. Some have even opted for a multi-cloud environment. Applications, hardware, and databases are residing on cloud leveraging a combination of IaaS, PaaS, and SaaS solutions. To add to the complexity, these are being used in conjunction with on-premises systems. This has made securing data and its infrastructure more challenging in recent years.

It seems that people are oscillating between handing over complete control to cloud solutions or placing extreme suspicions on cloud security. Rather, implementing security in the cloud era requires a more balanced perspective.

Cloud integration is inevitable but it calls for adapting to the new environment and making appropriate changes to data security solutions.

First, companies need to perform a thorough evaluation of the cloud solution before placing their trust. Asking questions such as the ones below help assure that the cloud solution isn’t just a black box:

• How much data availability or downtime does the vendor promise?
• What kind of backup solutions are provided?
• What are the privacy policies? Is sensitive data encrypted? Is data shared with third-parties or are there stringent restrictions instead?
• How is the solution’s adherence to compliance regulations?
• In what locations do the data centers reside? What sort of regulations apply to those regions?

Second, companies need a solution that monitors the integrity of their data. Data integrity (that encompasses data security and quality) is critical to ensure accuracy and consistency of data. Moreover, data integrity helps protect data from external threats. It confirms that only the right people or systems get to manipulate data and that no hardware or data is compromised because of any vulnerabilities.

The continued growth of cloud-based technologies will require data security solutions to strategize accordingly. They will need to build connectors that can extract data from each source, merge, cleanse, and govern them so that it empowers organizations to shield their data as well as make key decisions.

Getting started with data security

Data security may be an age-old problem. But, the multiple points of data origin along with an increasing number of external and internal attacks warrant a modern, cloud-based approach. 

Talend Data Fabric offers a single suite of self-service apps for data integration and integrity. Users can collect data across systems, govern it for proper use, transform it into new formats and improve quality, and share it with internal and external stakeholders. 

By doing so, Talend Data Fabric shortens the time to trusted data by solving some of the most complex aspects of the data value chain. In essence, it resolves the fundamental problems that could jeopardize data security. Get started with Talend Data Fabric today.