Data security enables organizations to protect digital information across its lifecycle against theft, unauthorized access, and corruption. It covers all components in the data lifecycle, including software, hardware, storage devices, user devices, policies and procedures, access, and administrative controls.
Implementing data security often involves dedicated tools that provide visibility over data usage and activity. Data security tools help protect data using various processes, such as encryption, data masking, and anonymization. They also help organizations streamline auditing and comply with data protection regulations. However, data security cannot be achieved with tools alone and must involve robust organizational practices and a data governance framework.
Creating and implementing a data security management process enables organizations to protect information against critical cyberattacks. Additionally, data security strategies can help organizations minimize risks that occur due to insider threats and human error, two risks that have caused many real-world data breaches.
Data breaches can have catastrophic consequences for a business, so taking measures to secure your data is critical. The average cost of a data breach is millions of dollars. Many data breaches also lead to compliance violations which can lead to fines and additional negative impacts on a business.
Perhaps the most serious impact of a security breach is that it can destroy brand equity and reputation. For large enterprises, the impact can be in the billions of dollars. A study showed that 65% of consumers lose trust in a brand when a data breach occurs, and 27% discontinue their relationship with the organization.
Data privacy and data security may seem similar, but these are two different fields. Data privacy practices focus on governance processes that monitor how the organization collects, uses, and shares personal data. Data privacy regulations and laws vary by country and state, with some stipulating highly stringent requirements that are strictly enforced and others stipulating less stringent rules.
Data security encompasses all measures, technologies, and policies that protect data from internal and external threats. However, data security measures do not guarantee compliance with data privacy requirements. Data privacy requires adherence to specific data collection, usage, and sharing regulations.
To conclude, data security helps protect data from malicious threats, while data privacy addresses governance or use of this data. Data privacy is concerned with ensuring organizations use data while respecting an individual’s privacy, while data security is concerned with protecting personal identification in collected data.
Related content: Read our guide to data privacy (coming soon)
There are many threats facing data security in modern organizations. Here are some of the most severe threats being prioritized by security organizations.
A ransomware attack locks the victim’s computer, typically through encryption, to keep them from using the device or the stored data. The attacker demands a ransom, usually Bitcoin, to allow the victim access to the device or data. Ransomware can spread through malicious email attachments, infected external storage devices, compromised websites, or infected software apps.
Data exfiltration is a security breach that occurs when a threat actor copies, transfers, or retrieves data from a server or computer without authorization. Threat actors can manually conduct data exfiltration by physically accessing a computer or using a malicious automated process conducted over a network.
Cybercriminals usually perform data exfiltration over the public Internet or a network. Threat actors typically launch data exfiltration attacks at specific targets, trying to access a machine or network to find and copy specific data.
Social engineering attacks attempt to trick individuals into revealing private information or providing access to privileged accounts. Threat actors use social engineering attacks to access sensitive data.
Phishing is a form of social engineering commonly used by threat actors. Phishing attacks send legitimate-looking messages but include malicious links or attachments. Once victims comply with the instructions in the message, by clicking a malicious link or providing private information, threat actors can compromise their account or device or even gain unauthorized access to a corporate network.
Security misconfigurations occur due to a lack of security settings, poorly implemented configurations, and insecure default values. It often means your configuration settings do not comply with industry security standards like the OWASP Top 10 and CIS benchmarks. These standards are critical to maintaining security and reducing risks.
A misconfiguration can happen when a developer, database administrator, or system administrator does not properly configure an application’s, website’s, desktop’s, or server’s security framework, opening entry pathways for threat actors.
Misconfigurations can cause a critical data breach, resulting in dire repercussions, like financial losses, temporary loss of business, penalties through litigation, regulatory fines, and lost customers due to lack of trust. When threat actors cause damage to network infrastructure and software, it hinders employee productivity and customer transactions and might even shut down all business operations.
Related content: Read our guide to transaction monitoring (coming soon)
An advanced persistent threat (APT) is a cyberattack directed at a specific target. It occurs when an unauthorized intruder attempts to penetrate a network and remain undetected for a long time. Typically, APTs do not attempt to cause damage to a network or system.
The objective is usually to monitor network activity and then steal information that enables breaching the target, typically using malware and exploit kits. Cybercriminals direct APT attacks at high-value targets, like nation-states and large enterprises.
A data security policy standardizes data usage, monitoring, and management. It works to protect any data the organization consumes, manages, and stores. Organizations leverage data security policies to comply with data protection regulations and standards.
Data protection policies cover all data stored across the organization’s core infrastructure, including offsite locations, cloud services, and on-premise storage equipment. It can help organizations maintain the integrity and security of data at rest and in transit.
Data governance involves managing data availability, integrity, security, and usability in enterprise systems, using internal data policies and standards that also help control data usage. Effective data governance can ensure that data remains trustworthy and consistent and prevents misuse.
As organizations face increasing data privacy regulations, data governance becomes critical to maintaining compliance. Additionally, data governance plays a key role in enabling organizations to leverage data analytics to drive business decision-making and optimize operations.
A data governance program includes:
All roles collaborate to create data governance standards and policies, while data stewards are tasked with implementing and enforcing these procedures. You can also include executives and business operations roles in this program to work alongside IT and data management teams.
Organizations that collect personal data are labeled as data processors, regardless of the volume or type of data. A data processor is responsible for meeting several compliance regulations governing personal data.
The applicable regulations depend on various factors, including the industry and the data type. For example, storing data related to European citizens requires complying with the General Data Protection Regulation (GDPR). Non-compliance violations can result in fines and legal repercussions, depending on the regulatory body.
Now that we have covered the fundamentals of data security let’s review 10 ways you can protect your organization: 5 types of data security tools and 5 best practices that can help improve data security.
Data security management practices protect data by applying various techniques, practices, and processes. Data security management systems protect business-critical intellectual property and sensitive data. Common data security management practices include:
Data encryption processes encode information to ensure it can only be decrypted and accessed by an authorized user with an encryption key. Encrypted data (ciphertext) looks unreadable or scrambled to an entity or person attempting to access it without permission. Data encryption software, also called cipher or encryption algorithm, helps develop an encryption scheme that, ideally, can only be broken using massive computing power.
Organizations use data encryption to prevent negligent or malicious parties from accessing sensitive data. Encryption is a critical line of defense in any cybersecurity architecture. Encryption makes it difficult to use the data when unauthorized parties intercept it. Organizations can apply encryptions to various data protection needs, including classified government intelligence and personal credit card transactions.
Data masking processes create a structurally similar but different version of data. It helps protect the real data version while providing a functional substitute. Organizations use masked data for various purposes, including user training and software testing.
Data masking techniques keep the same data format, changing only the values. It involves altering data using various techniques, such as encryption, word or character substitution, and character shuffling. Regardless of the method, the process must change the values to prevent reverse engineering or detection.
Learn more in our detailed guides to:
Data classification tools scan on-premise and cloud-based repositories for documents containing sensitive information, classifying the identified data. Classifying data makes it easier to remove redundant or duplicate data. It helps assign access controls, increase visibility into data usage, and easily locate the information. Sophisticated solutions allow you to configure data classification according to compliance requirements.
Data loss prevention (DLP) helps prevent unauthorized access to sensitive information, ensuring employees and other parties cannot send sensitive and critical information outside the corporate network.
DLP software solutions use predefined business rules to enforce compliance and classify and protect information to prevent unauthorized users from accidentally or maliciously sharing this data. DLP solutions monitor, detect and prevent sensitive data from leaving the organization. It involves monitoring data attempting to enter or exit the network.
Ensure you have visibility over your data before implementing any security measures. Clearly mark the sensitivity of data using categories like:
This type of classification will allow you to prioritize the information that needs to be protected first and eventually ensure you have appropriate data security measures for all your sensitive data.
An incident response plan establishes actions to identify cybersecurity incidents and mitigate the threat in a timely manner. Several compliance standards, including HIPAA and PCI DSS, have specific incident response requirements.
When planning incident response for data security, keep the following in mind:
It is critical to encrypt data while in a database or other form of storage (at rest), and also encrypt data when shared (in transit). Although encryption does not solve all security problems, it adds a significant layer of protection and is inexpensive to implement.
In the past, encryption slowed down performance on many computer systems, but modern encryption tools only have a marginal impact on performance. Make sure to only use strong encryption algorithms—the Advanced Encryption Standard (AES) is currently considered strong and approved for us by the US government.
In the context of data security, standards and regulations represent a risk because non-compliance can lead to fines and penalties. However, they also present an opportunity because each standard provides a detailed framework for securing your data.
If your organization is subject to compliance standards, run an internal, voluntary audit to see your level of compliance. The detailed feedback from this audit will give you actionable advice on how to improve your security posture. This will not only improve security but make you much better prepared to pass the next external audit.
Employees are typically the weakest link in an organization’s security chain. Almost all security incidents use some form of social engineering. Therefore, employees play a critically important role in the threat mitigation process. Knowledge significantly reduces human factors in data breaches and enables staff to assist and support security efforts.
Educate employees on how to safely handle company assets and how to identify malware and social engineering attempts. Keep them up to date on evolving threats, such as ransomware and new vulnerabilities affecting your industry. Conduct training and security awareness sessions regularly.
Pathlock enables you to capture, assess, and respond to data security, data privacy, and internal/external threats to establish digital trust. Pathlock offers you the ability to secure the leading business systems by implementing layered controls, which help you build and maintain digital trust at the application, data, and transaction levels.
With Pathlock, you can:
Contact us today to see a demonstration of all our capabilities and learn how to secure all applications, transactions, and data with Pathlock.
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