Data security

Security is not a new concept. It's been adopted since the early UNIX time-sharing operating system design. In the recent past, security awareness has increased among individuals and organizations on this security front due to the widespread data breaches that led to a lot of revenue loss to organizations.

Security, as a general concept, can be applied to many different things. When it comes to data security, we need to understand the following fundamental questions:

• What types of data exist?
• Who owns the data?
• Who has access to the data?
• When does the data exit the system?
• Is the data physically secured?

Let's have a look at a simple big data system and try to understand these questions in more detail. The scale of the systems makes security a nightmare for everyone. So, we should have proper policies in place to keep everyone on the same page:

In this example, we have the following components:

• Heterogeneous applications running across the globe in multiple geographical regions.
• Large volume and variety of input data is generated by the applications.
• All the data is ingested into a big data system.
• ETL/ELT applications consume the data from a big data system and put the consumable results into RDBMS (this is optional).
• Business intelligence applications read from this storage and further generate insights into the data. These are the ones that power the leadership team's decisions.

You can imagine the scale and volume of data that flows through this system. We can also see that the number of servers, applications, and employees that participate in this whole ecosystem is very large in number. If we do not have proper policies in place, its not a very easy task to secure such a complicated system.

Also, if an attacker uses social engineering to gain access to the system, we should make sure that the data access is limited only to the lowest possible level. When poor security implementations are in place, attackers can have access to virtually all the business secrets, which could be a serious loss to the business.

Just to think of an example, a start-up is building a next-generation computing device to host all its data on the cloud and does not have proper security policies in place. When an attacker compromises the security of the servers that are on the cloud, they can easily figure out what is being built by this start-up and can steal the intelligence. Once the intelligence is stolen, we can imagine how hackers use this for their personal benefit.

With this understanding of security's importance, let's define what needs to be secured.

Application security

Applications are the front line of product-based organizations, since consumers use these applications to interact with the products and services provided by the applications. We have to ensure that proper security standards are followed while programming these application interfaces.

Since these applications generate data to the backend system, we should make sure only proper access mechanisms are allowed in terms of firewalls.

Also, these applications interact with many other backend systems, we have to ensure that the correct data related to the user is shown. This boils down to implementing proper authentication and authorization, not only for the user but also for the application when accessing different types of an organization's resources.

Without proper auditing in place, it is very difficult to analyze the data access patterns by the applications. All the logs should be collected at a central place away from the application servers and can be further ingested into the big data system.

Input data

Once the applications generate several metrics, they can be temporarily stored locally that are further consumed by periodic processes or they are further pushed to streaming systems like Kafka.

In this case, we should carefully think through and design where the data is stores and which uses can have access to this data. If we are further writing this data to systems like Kafka or MQ, we have to make sure that further authentication, authorization, and access controls are in place.

Here we can leverage the operating-system-provided security measures such as process user ID, process group ID, filesystem user ID, group ID, and also advanced systems (such as SELinux) to further restrict access to the input data.

Big data security

Depending on which data warehouse solution is chosen, we have to ensure that authorized applications and users can write to and read from the data warehouse. Proper security policies and auditing should be in place to make sure that this large scale of data is not easily accessible to everyone.

In order to implement all these access policies, we can use the operating system provided mechanisms like file access controls and use access controls. Since we're talking about geographically distributed big data systems, we have to think and design centralized authentication systems to provide a seamless experience for employees when interacting with these big data systems.

RDBMS security

Many RDBMSes are highly secure and can provide the following access levels to users:

• Database
• Table
• Usage pattern

They also have built-in auditing mechanisms to tell which users have accessed what types of data and when. This data is vital to keeping the systems secure, and proper monitoring should be in place to keep a watch on these system's health and safety.

BI security

These can be applications built in-house for specific needs of the company, or external applications that can power the insights that business teams are looking for. These applications should also be properly secured by practicing single sign-on, role-based access control, and network-based access control.

Since the amount of insights these applications provide is very much crucial to the success of the organization, proper security measures should be taken to protect them.

So far, we have seen the different parts of an enterprise system and understood what things can be followed to improve the security of the overall enterprise data design. Let's talk about some of the common things that can be applied everywhere in the data design.

Physical security

This deals with physical device access, data center access, server access, and network access. If an unauthorized person gains access to the equipment owned by an Enterprise, they can gain access to all the data that is present in it.

As we have seen in the previous sections, when an operating system is running, we are able to protect the resources by leveraging the security features of the operating system. When an intruder gains physical access to the devices (or even decommissioned servers), they can connect these devices to another operating system that's in their control and access all the data that is present on our servers.

Care must be taken when we decommission servers, as there are ways in which data that's written to these devices (even after formatting) can be recovered. So we should follow industry-standard device erasing techniques to properly clean all of the data that is owned by enterprises.

In order to prevent those, we should consider encrypting data.

Data encryption

Encrypting data will ensure that even when authorized persons gain access to the devices, they will not be able to recover the data. This is a standard practice that is followed nowadays due to the increase in mobility of data and employees. Many big Enterprises encrypt hard disks on laptops and mobile phones.

Secure key management

If you have worked with any applications that need authentication, you will have used a combination of username and password to access the services. Typically these secrets are stored within the source code itself. This poses a challenge for programs which are non-compiled, as attackers can easily access the username and password to gain access to our resources.

Many enterprises started adopting centralized key management, using which applications can query these services to gain access to the resources that are authentication protected. All these access patterns are properly audited by the KMS

Employees should also access these systems with their own credentials to access the resources. This makes sure that secret keys are protected and accessible only to the authorized applications.