What is Data Security? Data Security Definition and Overview

Enterprises should adhere to well-established data security best practices to effectively reduce risk and address security issues. Formal data risk assessments and routine security audits can assist businesses in identifying their sensitive data and where their existing security controls may be lacking.

What is Data Security?

The process of safeguarding corporate data and avoiding data loss due to unauthorized access is known as data security. This entails protecting the data against assaults that can alter or corrupt it and assaults that can encrypt or destroy it, like ransomware. Data security guarantees that data is accessible to everyone who needs it within the organization.

For some industries to comply with data protection laws, a high level of data security is necessary.

The survival of a modern business depends on data security, which can affect the organization’s critical assets and its clients’ private information, even if an organization is not subject to a regulation or compliance standard.

Data security: Why Is It Important?

Data security is crucial for organizations across all sectors and geographies for various reasons. Businesses must safeguard user and customer information to prevent the loss, theft, and eventual misuse. Data cybersecurity is also essential to avoid the reputational risk associated with a data breach. Customers may lose faith in a company due to a high-profile hack or data loss and choose to do business with a rival. Along with penalties, court costs, and damage repair, if sensitive data is lost, this also carries the risk of substantial financial losses.

Data Privacy vs. Data Security

The difference between data that can be shared with third parties and data that cannot be shared with third parties is known as data privacy (private data). Enforcing data privacy primarily entails two things:

Access control ensures that anyone attempting to access the data is authenticated to verify their identity and is authorized to access only the data to which they have been granted access. Data protection means ensuring that even if unauthorized parties can access the data, they cannot view or harm it. Data loss prevention mechanisms, which stop users from sending sensitive data outside the company, and encryption, which prevents anyone from viewing data if they do not have a private encryption key, are two critical components of data protection methods.

Data privacy and data security frequently intersect. A company’s data security strategy includes the same safeguards to ensure data privacy. The main distinction is that while data security primarily focuses on defending against malicious activity, data privacy mainly focuses on maintaining data confidentiality. Encryption, for instance, might be adequate for privacy protection but insufficient for data security. Attackers could still harm by erasing the data or encrypting it twice to deny access to authorized parties.

Also Read: A CISOs Playbook for Anti-Ransomware Day

Common Data Security Techniques and Solutions

Numerous techniques and technologies exist that can increase data security. While no single approach can completely solve the issue, organizations can significantly enhance their security posture by combining several listed below.

Discovering and Classifying Data

Data is kept on servers, endpoints, and cloud-based platforms in modern IT environments. Understanding what data is susceptible to theft or misuse begins with having visibility over data flows. Knowing the type of data, where it is, and what it is used for will help you protect it effectively. Tools for data discovery and classification may be helpful. By determining which data is sensitive and needs to be secured, data classification enables organizations to develop scalable security solutions. By tagging files on endpoints, file servers, and cloud storage systems, data detection and classification solutions will allow IT teams to visualize data across the enterprise and implement the necessary security policies.

Data obscuring

Using data masking, businesses can produce a fake copy of the organizational data for software testing, training, and other tasks that don’t require the actual information. The objective is to safeguard data while offering a helpful substitute when necessary. Data masking alters the values while preserving the data type. Encryption, character shuffles, and word or character substitution are data-transforming methods. The values must be changed to prevent reverse engineering regardless of the teams’ selection method.

Identification Access Control

Organizations can manage digital identities with the business process, strategy, and technical framework known as identity and access management (IAM). IT managers can manage user access to confidential data within an organization using IAM solutions.

Authentication methods used for IAM include single sign-on, two-factor, multifactor, and privileged access management. With these technologies, the organization can securely store identity and profile data, supporting governance by applying appropriate access policies to every infrastructure component.

Encryption of Data

Data encryption is a technique for converting data from a readable format to an unreadable encoded format. The data cannot be read or processed until the encrypted data has been decrypted using the decryption key. The sender and recipient combine their keys to perform the encryption operation in public-key cryptography techniques. This eliminates the need to share the decryption key as it is more secure. Data encryption may prevent hackers from gaining access to sensitive dataThe majority of security strategies depend on it, and many compliance standards expressly call for it.

Data Loss Avoidance (DLP)

Organizations can use a variety of safeguards, such as backing up data to a different location, to prevent data loss. Data can be protected by physical redundancy from attacks on local servers, power outages, and natural disasters. Data replication to a remote site or cloud environment and redundancy within a local data center are all options for redundancy.

DLP software solutions can assist in protecting organizational data above and beyond simple safeguards like a backup. DLP software automatically scans the content to find sensitive data, enabling centralized control and enforcement of data protection policies. It also alerts in real time when it notices suspicious use of sensitive data, such as much data being copied outside the corporate network.

Most significant risks to data security

The transition of work to cloud-based and remote access models has accelerated the evolution of the data security landscape. There are now some serious risks to data security as a result of these shifting circumstances:

Insider hazard

A person with authorized access to a company’s systems and data poses an insider threat, a cyber-security risk. They may develop due to anyone using a company’s network or applications, including staff members, partners, clients, suppliers, interns, or contractors. For instance, it’s not unusual for employees to take company data when they complete their two weeks of work and prepare to move on to a new opportunity, whether they mean to or not. They might use a thumb drive or their email account to send files.

Insider threats have wreaked havoc on organizations in numerous real-world instances, so it’s critical to have procedures and technology to spot and stop risky data movements before it’s too late.

Unsecured cloud application practices

While tools and technology in the cloud have made it possible to work in new ways, they have also increased the scope and impact of data exfiltration.

The following are some of the most typical non-secure cloud app behaviors:

• Using untrusted personal devices to access business cloud applications
• Exposing private cloud links to the general public
• Using a cloud app to download business data to a personal device
• Using personal clouds, which are typically unauthorized, to share data with co-workers and third parties

When a worker or authorized user carries out one of these tasks, they jeopardize cloud security and endanger the company’s data confidentiality.

Hackers

Hackers are developing new ways to steal, exploit, and extract data from organizations. Phishing and ransomware are two frequent attacks. These threats are particularly difficult to fend off because they frequently employ psychological ploys to elicit information from negligent or inexperienced workers.

Solutions for data security

Organizations can use a range of data security technologies and tactics to reduce these risks:

Identity Access Management (IAM): It is a solution that simplifies the management of electronic identities, typically via single sign-on (SSO) or multifactor authentication.

Security Education and Awareness (SEA): The employees are the first line of defence against data security threats. Organizations can lessen exposure by employing techniques and tools that teach them security best practices.

Zero Trust: Zero trust architecture is a security model requiring continuous user authentication to access internal servers, data, and applications.

Data loss prevention (DLP): DLP programs look for potential data exfiltration and leaks. They necessitate extensive data classification, and if a business fails to do so, a DLP cannot monitor a particular data set.

Insider Risk Management (IRM): A risk-based strategy for data security, IRM solutions. In contrast to traditional DLP techniques, IRM solutions keep track of all data movement, not just that which a business has already labelled. Automatically prioritizing high-risk data exfiltration, they aid security teams in swiftly handling emergencies without hindering worker productivity.

Knowing the potential methods for protecting data can help IT teams decide which option or combination is best for the company.

Also Read: The Importance of Zero Trust Network Access in the BYOD Landscape

Frequently Asked Questions (FAQs)

What types of data require better protection?

Specific categories of personal data are labelled “special categories” under the GDPR because they are deemed particularly sensitive. This data includes but is not limited to, information about genetic and biometric data, health information, and ethnic or racial origin. The use of this data should be carefully considered by those handling it, and they should ensure that it is only used when necessary.

Can employees share data with another organization?

A business may share data with another company or entity if it has a good reason. To comply with the GDPR, companies must have a valid reason for sharing data and maintaining a record. If the data is personal, the data subject must have agreed for the data to be shared with a third party. Additionally, when information is shared, it must be properly secured to prevent access from unauthorized parties.

What is the best method to protect data?

According to cybersecurity experts, encryption software is the best way to keep data secure. When data encryption is used, the contents of a message or file are scrambled, preventing unauthorized readers from accessing them. The owner of a private encryption key that allows them to view, modify, or delete the content is the person who sent the message or created the file. They can then give out a public key, a decryption key, or a decryptor, for short, to those they wish to grant access. Companies can avoid paying hefty fines from data regulators by encrypting the sensitive and confidential data they share and store.

How long should data be stored?

Personal data should only be retained for as long as is necessary for security reasons, even though there are no strict guidelines regarding how long information can be kept. Data must be securely destroyed once it is no longer needed. Data destruction should always be documented, and always keep deletion proof. Physical data files must be destroyed; electronic data can be deleted from computers, servers, and backups.

Why is a strong password necessary?

Passwords are still frequently used credentials for limiting access to data despite their drawbacks. They must be difficult to guess but simple to remember to continue working. While it may be impossible for a threat operator to think of a series of random characters with different cases, numbers, and symbols, they will be equally challenging for a user to remember. In these situations, a user will save the password to their local device or maintain a record of it on file to cut and paste it as needed. In either case, a data security vulnerability results. Instead of users, IT departments should always generate passwords and be changed frequently. Multifactor authentication should be enabled on password-protected areas and accounts, adding a layer of data security.

What should teams do when data security is compromised?

Companies must conduct a risk assessment immediately if the team finds evidence of a data security breach. Learn what kind of data was exposed and how sensitive the data in question is. If the sensitive information belonged to particular data subjects, they must be aware of the breach and advised of any associated risks. Most businesses have 72 hours to evaluate and report a data security breach.