What is Data Security?

Some of the most common data security risks include:

• Human Error: Many data breaches are caused by non-malicious human error that results in the exposure of sensitive data or information. From sharing or granting access to valuable data to losing or mishandling sensitive information, employees can trigger a data breach either by accident or because they are not fully briefed on enterprise security policies.
• Social Engineering Attacks: As a primary attack vector for cybercriminals, social engineering attacks manipulate employees into providing PII or access to private accounts. One of the most common forms of social engineering attacks is phishing.
• Internal Threats: Malicious or compromised insiders are employees, contractors, vendors, or partners who intentionally or inadvertently put your organization's data at risk. Malicious insiders actively try to steal data or harm your organization for personal gain, while compromised insiders go about their daily routine unaware that their account has been hacked.
• Ransomware: Ransomware is malware used by criminals to take over corporate devices and encrypt sensitive data. This data is only accessible with a decryption key that the cybercriminal owns, and they commonly only release this key if a ransom has been paid. Oftentimes, even when organizations pay the ransom, their data ends up being lost. Ransomware: The Good, The Bad, and The Ugly
• Data Loss During Cloud Migration: As organizations migrate their IT environments to the cloud, IT teams who aren’t familiar with cloud architecture can easily mishandle cloud security configurations or data—resulting in an exposed attack surface or compromised information.

Comprehensive data privacy solutions require several techniques to effectively protect your organization from cyber-attacks that target sensitive data. Below, we will break down a few of the most important data security techniques your organization should be utilizing to protect your assets and your employees’ PII.

Identity and Access Management

Identity and access management (IAM) represents the process of managing digital identities within your organization. Through strategies like zero trust network access (ZTNA), single sign-on (SSO), and multi-factor authentication (MFA), you can establish the principle of least privilege (PoLP) and ensure that only end users with pre-established privileges can access data based on their job titles or roles. With a ZTNA framework, you can provide conditional end user access based on things like identity, time, and continuous device posture assessments.

Encryption

Data encryption uses cipher (an encryption algorithm) and an encryption key to encode plaintext (human-readable text) into ciphertext (a string of unreadable characters). Only an authorized user with a decryption key can successfully convert this ciphertext back into plaintext. Organizations can use encryption to safeguard things like files, databases, and email communications. In addition, many data privacy regulations require data encryption to meet compliance standards.

Tokenization

Tokenization substitutes sensitive data for a non-sensitive, unreadable version of the same data—also known as token. This token is a string of random data that represents the sensitive data stored in a secure token vault. Tokenization of data is completely indecipherable, and the process cannot be reversed by a cybercriminal due to there being no mathematical connection between the token and that data it represents. This data security solution is often used by organizations that handle PII like Social Security numbers or payment information.

Data Masking

Data masking allows organizations to “mask” or hide key information by substituting human-readable text for proxy characters. When an authorized end user receives information that has been masked, only they will be able to view that information in its original, human-readable form. This data security strategy can be utilized for things like software testing or training, as these types of events don’t require the real data. Also, if an unauthorized user or bad actor gained access to masked information, they would not be able to view any sensitive data or PII.

Data Discovery and Analysis

Data discovery and analysis solutions allow organizations to quickly uncover what types of data they have, where data is located, and how data is being used. This provides data visibility from a single pane of glass, which allows organizations to quickly identify which data is confidential and needs to be secured. These solutions also allow identification across multiple IT environments, including internal data centers, cloud providers, and network endpoints.

Data Loss Prevention (DLP)

DLP solutions use artificial intelligence (AI) to automatically review and analyze an organization's confidential data, as well as provide real-time alerts when they detect abnormal use of this data. In addition, they provide centralized control of data security policies for sensitive data. Another way organizations can prevent data loss is through data backups. These are especially important for organizations storing their data in internal data centers, as uncontrollable or unexpected events like power outages or natural disasters can destroy physical servers and that data that’s stored on them. Typically, data backups should be done at remote sites or cloud environments.

Data and Application Retirement

Disposing of data and applications may seem straightforward, but standard data wiping isn’t a 100% effective solution. With robust data retirement software, an organization can properly dispose of data or expired applications at any time. These solutions completely overwrite data on any device and ensure that data cannot be recovered by anyone—especially malicious actors.

Security Audits

To ensure their data security strategies are effective, an organization must perform data security audits on a regular basis. These audits detect any weaknesses or vulnerabilities across an organization's entire attack surface. Comprehensive security audits can be performed by professional third-party vendors (e.g., network penetration testing) or in house. But no matter how security audits are performed, any detected data security issues must be addressed quickly.

Endpoint Protection

With IT environments shifting to the cloud as remote work increases, employee endpoints must be properly protected from threats like malware, especially if an organization has allowed bring your own device (BYOD) programs. Unlike sanctioned or IT-managed devices, servers, or cloud systems, unsanctioned endpoints likely do not feature the same security protocols or threat prevention architecture to shield against modern-day attacks like zero-day malware. With the proper endpoint protection solutions in place, an organization can better detect unknown attacks on endpoints as they happen, as well as lock down any affected endpoint to prevent larger breaches.

Employee Education

An organization's employees or affiliates must have the proper education on data security best practices. This includes understanding how to create strong passwords for their individual accounts, as well as understanding what social engineering attacks like phishing schemes look like. In addition to educating your employees about these security strategies, be sure to require more complex passwords for users creating accounts, and enforce password updates on a regular basis.