The definition of data security is simple and convoluted at the same time. At a very basic level, it means the means and measures taken to protect information. However, in the broader sense, data security encompasses a wide range of aspects like data governance, risk analysis, encryption, vulnerability assessment, compliance, and whatnot. In this post, we will talk about data security, its types, features, best practices, and importance.
The definition of data security
“Data security is the practice of protecting digital information from unauthorized access, corruption, or theft throughout its entire lifecycle”
This definition is given to us by IBM and it does a good job to accommodate the entire scope of data security in very few loaded words. Let’s see if we can break this definition down for better comprehension.
What do we mean by digital information?
Digital information is data that is created by and for electronic devices like computers, mobile devices, etc. For instance, if you take a photo of a house with a digital camera and store it on the hard drive of a computer, it becomes digital information. The information here is not limited to the visual representation of the house but also the time and date when the photo was taken, and its resolution.
Every pixel in that image represents digital information. Not kidding! Hadn’t it been so, it wouldn’t be possible to use machine learning to recognize that image. But that’s a story for a different time.
From banks to healthcare facilities, every institution creates digital information – personal records of people. It is important to protect this information from unauthorized access.
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Now, what is unauthorized access?
Let’s say you provide your email ID to a website in the hopes of receiving a newsletter from them which is relevant to you. So, you authorize the website to use your email ID to send material to you. Now, if the website falls prey to an attack and ends up exposing customer email IDs, the hacker will have access to your email ID. That is unauthorized access. To prevent unauthorized access like this, implementing email verification can significantly reduce the risk by ensuring that only legitimate and verified email addresses are used for communication, adding an extra layer of security to protect your information.
Data security is an umbrella term that covers all the processes and practices involved in protecting digital information from unauthorized access.
Types of data security
Here, we will discuss some common measures for securing data from unauthorized access.
Encryption
Encryption is the process of transforming textual data into an unreadable, encrypted format that is readable only using keys available to authorized users. In the event of a data breach, encryption works as a final line of defense for sensitive data. Encryption is intertwined with security key management – the process of making the security keys available to authorized users through authentication.
Data Erasure
Data erasure is the process of using software to completely overwrite data on a disc. It removes any possibility of recovering the data.
Data Masking
Data masking is the process of hiding personally identifiable information (PII) while working with real-life data. It is necessary to ensure that data-driven development is possible without violating data privacy norms.
Data Resiliency
Data resiliency defines an organization’s capability of resisting or recovering from a data breach or a similar security failure. It also defines how exploitable the data is within their systems.
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Tools involved in data security
From malware scanners to data governance tools, from compliance automation to penetration testing, a lot of physical and automated processes contribute to the successful implementation of data security. We will talk about some of those tools here.
Data discovery and classification tools
In order to protect sensitive data, you need to know where it resides. It can be in a structured form in spreadsheets or in an unstructured form like media files, audio recordings, or videos. It can be in on-premise databases or in a public cloud. The tools for data discovery and classification help you discover sensitive data and assess the risk it may be exposed to.
Alongside these, implementing database change management tools is essential for maintaining the integrity and security of your data across all environments. These tools ensure that any modifications to your database structures are tracked and managed effectively, reducing the risk of data breaches and enhancing compliance.
Data and file activity monitoring
It’s easier for a security team to protect data if they can identify anomalous activity early. That is what file activity monitoring helps you with. It analyzes data usage patterns and helps security people know who is accessing data. These tools can also be used for creating alerts when an anomaly is spotted and even to block an IP.
Vulnerability scanner
Vulnerabilities are like bugs in software, only instead of affecting the performance of an application or website, they affect its security. A vulnerability can exist in the form of a software misconfiguration, an outdated app that’s missing a patch, or a user input field that lacks input validation. It is important to identify these vulnerabilities and remove them. A vulnerability scanner helps you automatically detect a bunch of such security loopholes.
Automated compliance reporting
Every industry is governed by a set of digital security regulations like GDPR, HIPAA, SOC, PCI DSS, etc. It is important that an organization complies with the regulations relevant to it. There are tools that can help you automate the process of getting compliance-ready.
Conclusion
Data security has come to the forefront after the Covid-19 pandemic more than ever. With so many people working from home, login into company assets with personal devices, and using innumerable applications and then forgetting about them without logging out, data security is a paramount concern for businesses. The more aware we are the safer.
