At its core, data security incorporates different tools, technologies, and processes to provide visibility into where sensitive data is located, how it’s being used by authorized end users, and who is trying to access it. Advanced data security tools provide solutions like data encryption, data masking, sensitive file redaction, hashing, tokenization, and key access management practices, as well as automated reporting and assistance with meeting regulatory compliance requirements.
Below we will detail the importance of data security, common data security risks, and security solutions you can use to protect your data.
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According to IBM’s Cost of a Data Breach Report, data breach costs rose from $3.86 million to $4.24 million in 2021—the highest average total cost in the 17-year history of their report.
Organizations around the globe are investing heavily in information technology (IT) cyber security capabilities to protect their critical assets. Whether an enterprise needs to protect a brand, intellectual capital, and customer information or provide controls for critical infrastructure, the means for incident detection and response to protecting organizational interests have three common elements: people, processes, and technology. To help both public and private sector organizations reduce their chance of experiencing a costly data breach, effective data security solutions must be implemented to safeguard enterprise assets and sensitive business information (e.g., trade secrets, intellectual property (IP), etc.) from cybercriminals. In addition, robust data security tools must also mitigate insider threats and human error—which are two of today’s leading causes of data breaches.
Data privacy regulations
But data security solutions aren’t just about protecting the enterprise; they are also about the legal and moral obligation that organizations must protect personally identifiable information (PII) of their employees, contractors, vendors, partners, and customers. With multiple enacted data privacy regulations, organizations in many major sectors must comply with stringent data security policies to avoid compromised PII and costly fines. Some of the most prominent privacy regulations include:
Organizations that do not implement the proper data security measures and fall victim to a data breach also run the risk of tarnishing their brand reputation. This is especially true in the event of a highly publicized or high-profile breach, as many customers will lose trust in an organization's ability to keep their PII protected.
IT modernization and acceleration to the cloud
On top of meeting data privacy regulations, implementing robust data security solutions is becoming increasingly complex—especially as more businesses undergo digital transformation and IT modernization. With an increase in data that organizations create, utilize, and store, IT environments accelerating to the cloud, and more remote workers than ever before, attack surfaces are growing larger. This means that IT and information security teams must adapt and modernize their current data security measures to accommodate new attack vectors and network architecture vulnerabilities in the cloud.
Some of the most common data security risks include:
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.
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 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 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.
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.
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.
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.
Ensuring your organization has the proper data security measures can feel overwhelming, especially if your IT department is attempting to piecemeal a security strategy together through disjointed security vendors or solutions. However, with a single-vendor data security solution like OpenText, you can easily safeguard your organization's sensitive data and your employees’ PII.
At OpenText, we are a leader in modern data security solutions with over 80 patents and 51 years of expertise. With advanced data encryption, tokenization, and key management to protect data across applications, transactions, storage, and big data platforms, OpenText Voltage simplifies data privacy and protection—even in the most complex use cases.
Voltage data privacy solutions include: