Data Security | 11 mins read

What Is Data Security? Guide to Securing Business Data

what is data security guide to securing business data
Chloe Henderson

By Chloe Henderson

Introduction to Data Security

Businesses continue to transition from traditional data management methods to digital software to expand storage capacity and accessibility. While this significantly improves operational efficiency, it also introduces an entirely new set of internal and external security threats. Companies that do not practice data security often fall victim to harmful cyberattacks, both small and large organizations alike.

In fact, studies found that 43% of cyberattacks target small businesses. This can result in leaked, stolen, and tampered data that damages the company's reputation for customers and partners. To avoid the repercussions of cyberattacks, owners need to invest in multiple data security technologies that actively monitor systems.

What is Data Security?

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Data security is the practice of protecting critical information from internal and external threats. It includes various cybersecurity practices to protect business information from data breaches, unauthorized users, and malware. Without data security, companies can experience stolen, leaked, and tampered data. As a result, the business can undergo a damaged reputation, losing the trust of its partners and customers.

While data security has always been a concern for businesses, owners continuously invest in safety measures for their digital solutions. Automated management tools and databases have their own unique security threats that require additional restrictions and governance practices. Without taking the proper precautions, companies can fall subject to hackers that can identify weaknesses within the firewall.

Most modern companies utilize databases to store their financial, partner, operational, and other critical information. However, businesses have much more than their own data to protect. They have to secure sensitive customer data, such as their personal and billing information. Different organizations may require different forms of security, depending on their size and data, as each industry has unique regulations.

Businesses that do not have robust infrastructure to withhold security tools may need to undergo a digital transformation. Otherwise, implementing sophisticated tools on a weak structure may create system malfunctions. Therefore, owners should analyze their current safety precautions to determine how they can improve their overall security measures.

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Data Security Compliance Regulations

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Each industry has its own set of data security compliance regulations that all businesses must abide by. Otherwise, non-compliant companies can increase risks, accrue fees, and even face legal repercussions. However, some restrictions are difficult for owners to understand, and many end up mistakenly becoming non-compliant. Therefore, owners should take the time to review the regulations applicable to their business.

General Data Protection Regulation

General Data Protection Regulation (GDPR) is the European Union's data privacy law established in 2016. This rule protects customers' data by restricting how domestic and international businesses can manage, store, and process data. The GDPR requires companies that handle sensitive information to implement adequate safety measures, including the customer's consent. After receiving approval, organizations have to encrypt the data to hide the owner's identity in case of a breach.

Health Insurance Portability and Accountability Act

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The Health Insurance Portability and Accountability Act (HIPAA) is the United States' data regulation that protects patients' electronic health information. Originally passed in 1996, HIPAA controls how companies manage health data to prevent fraud and theft. This includes how insurance institutions charge patients for various medical services.

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Sarbanes-Oxley Act

The Sarbanes-Oxley Act (SOX) protects corporate investors from financial fraud and theft. Created in 2002 as a response to corporate accounting scandals, SOX increases the penalty for fraudulent financial reporting. This includes incomplete, inaccurate, and tampered financial information. Public corporations, and some private organizations, must abide by SOX and disclose financial information during external audits.

Federal Information Security Management Act

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The Federal Information Security Management Act (FISMA) standardizes the way American agencies practice data management. Passed in 2002, FISMA requires federal agencies and private subcontractors to follow data security policies. They must also undergo strict auditing procedures to ensure they follow each information regulation.

Data Security Risks

Businesses regularly face several different types of data security risks that they must learn to mitigate.

Accidental Exposure

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Although many people only hear of cybersecurity attacks on corporations, many data leaks are the result of accidental exposure. If an employee loosely grants access, shares, or mishandles critical data, they may be disregarding policies unknowingly. This is often the result of inadequate training, non-compliant systems, and lack of data loss prevention practices. Companies should invest in thorough training workshops, data access controls, and security technology to avoid accidental exposure.

Phishing and Social Engineering Attacks

Phishing and other social engineering attacks are common methods that hackers use to gain access to critical data. Rather than finding weaknesses in the firewall, these target naive employees. The attackers manipulate workers into leaking sensitive information or granting access to private accounts.

While sometimes the phisher is unknown, other times they act like they are a trusted source. After gaining the information or even a private link, sometimes the attacker can take over the employee's device or the company's network. Proper training is the best way to inform workers of these scams and prevent hacks.

Internal Threats

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Internal threats, also known as insider threats, refer to employees that threaten data security, whether they realize it or not. Generally speaking, there are three types of insider threats.

  • Non-malicious insiders are employees that compromise data security by accident because they are unaware or they disregard precautions.
  • Malicious insiders are workers that actively try to steal information and damage the business.
  • Compromised insiders are employees that hackers use, without their knowledge, to hack the data system. This enables the external attacker to compromise the business under the guise of an authorized user.

Ransomware and Malware

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Ransomware and malware infect devices to encrypt data, making it impossible for businesses to retrieve information with the decryption key. Typically, hackers will display a message on the user's screen that requests payment in order to retrieve the data.

However, even if the company decides to pay the attacker, many times, the data is already lost. Sophisticated malware can spread through company devices rapidly and even infect the network. Therefore, businesses need to maintain scheduled backups in a secure database.

Cloud Data Loss

More and more companies are leaving their legacy systems behind for cloud-based software to improve storage capacity and accessibility. However, this technology comes with its own internal and external risks.

Data loss in the cloud is harder to prevent, as the service provider typically stores the information outside of the business. Employees are also able to download data to multiple devices, creating additional vulnerabilities. Owners should speak with their providers to discuss their cloud safety measures and data management practices.

Common Data Security Solutions and Techniques

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There are numerous data security technologies and techniques that organizations can use to protect their sensitive information. However, owners need to remember that not one practice can mitigate all cybersecurity risks. Therefore, owners need to combine multiple techniques to adequately protect their business.

Data Discovery and Classification

Companies that use automated management systems store their data on servers, various endpoints, and cloud software. This can sometimes limit the IT department's visibility into the flow of data and their ability to access risks. Therefore, businesses need data discovery and classification tools to determine how they can adequately protect their information.

Data discovery, or detection, refers to the outline of where the company stores data, how they use it, and when. Data classification categorizes information so developers can create security solutions for the most sensitive data. By combining data discovery and classification, owners can visualize how information can safely travel across the organization.

Data Masking

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Data masking is when companies create a model of their data so they can test different software and training. This way, businesses can find an alternate security measure while protecting data in real-time. While data masking retains the data type, it changes the value. For example, data can undergo encryption, character shuffling, and metric substitution. However, IT managers cannot reverse these changes, so they must carefully consider each option.

Identity Access Management

Identity access management (IAM) is a technical business framework that enables companies to organize and maintain their digital identities. In other words, IAM allows IT managers to regulate user access around sensitive data. Systems that utilize IAM include.

  • Single sign-on systems
  • Two-factor authentication
  • Multi-factor authentication
  • Privileged access management

With these technologies, businesses can safely store user profiles for authentication purposes while remaining compliant with regulations.

Data Encryption

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Data encryption is perhaps the most common tool that businesses use to convert information into an unreadable format. This unreadable format, also known as ciphertext, allows employees to transfer and share data safely. The recipient must have the decryption key to decode and read the information.

However, businesses that use public-key encryption techniques do not need to share the key, as each user already has one. With data encryption, companies can prevent attackers from stealing and using critical data.

Data Loss Prevention

Data loss prevention (DLP) comes in many forms, from software to data recovery systems. Many businesses make multiple digital copies of data in case of natural disasters, system malfunctions, and cyberattacks. IT managers orchestrate this physical redundancy by using local data centers to replicate and store datasets on a remote site.

Owners can also implement DLP software that automates content analysis to define sensitive data and activate protection. By tagging sensitive information, the system detects whenever users read, share, or edit the data. The software can even detect suspicious activity and alert managers when attackers attempt a breach.

Governance, Risk, and Compliance

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Governance, risk, and compliance (GRC) is an extensive methodology that most organizations use to enhance their data compliance and security.

  • Governance refers to the controls and policies that owners enforce throughout the company to remain compliant.
  • Risk refers to cybersecurity threats that businesses must analyze to develop adequate safety precautions.
  • Compliance ensures enterprises follow industry regulation guidelines regarding data management, processing, and accessibility.

Password Hygiene

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Password hygiene is a practice that ensures users' passwords are unique and strong. Without password hygiene, many employees will choose the same password for every account that is easily guessable. Hackers can use password spraying to break into accounts with weak passwords.

To avoid this, many businesses require employees to elongate their passwords and add special characters or numbers. However, as many users tend to use the same numbers and special symbols, some organizations also use multi-factor authentication. This practice requires users to further identify themselves through various measures, including.

  • Answering questions
  • Biometric authentication
  • Sending a code to an additional device

Some companies even have a designated password manager that encrypts and stores each user's code. This way, employees don't have to memorize their passcodes, and the business can store them without the cybersecurity risks.

Authentication

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Authentication and authorization methods verify users attempting to enter databases before granting them access. Although many businesses use multi-factor authentication for external users, they should also practice it internally. IT managers should even restrict employees' accessibility to only data that is relevant to them.

In other words, accountants should only be able to see financial information and not client appointments and personal data. Not only is complete accessibility for all employees useless, but it also increases the company's vulnerabilities to threats. Supervisors should conduct regular audits to reinforce permissions and unnecessary authorizations.

Data Security Audits

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The average company should perform data security audits at least every other month. By regularly performing audits, owners can identify gaps and weaknesses within their security measures. However, it is in a business's best interest to utilize a third-party auditor to ensure analysis is objective and accurate. Owners can perform an in-house audit in addition to the external check, but it shouldn't be the only practice.

Antivirus Protection

The most common cyberattacks that businesses experience come in the form of malware or viruses. This requires IT managers to secure all user endpoints throughout workstations, employee devices, network servers, and cloud systems. In addition to traditional antivirus software, many organizations utilize endpoint protection platforms (EPP) to protect against zero-day malware.

These types of attacks do not require files or other detectable signs, making it harder for companies to mitigate. EDP uses machine-learning technology to identify and quickly respond to malware attacks, preventing larger technical complications.

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