What is Data Security? Threats, Controls, and Solutions
What is Data Security? Threats, Controls, and Solutions
What is Data Security?
Data security is the practice of protecting organizational data from risk. It is common to organize data security according to three dimensions—Confidentiality, Integrity, and Availability—in line with the CIA Triad commonly used in information security.
Data confidentiality involves preventing unauthorized parties, whether internal or external, from accessing sensitive data. Organizations implement a variety of security measures to protect confidentiality, from perimeter network defenses, to permission systems like role based access control (RBAC), data encryption, and multi-factor authentication.
Data integrity involves the prevention of unwanted modification or deletion of data. This might be the result of an accident or disaster, or a malicious act by an attacker seeking to sabotage company operations. An important way to ensure data integrity is the use of digital signatures. Encryption can also help protect data integrity.
Data availability ensures that valuable data can always be accessed by those who need it, both inside and outside the organization. IT operations are primarily responsible for data availability, by making sure infrastructure is working and recovering quickly from failure.
Data Security vs Data Protection vs Data Privacy
Data security is often confused with similar terms such as data protection and data privacy. All of these are different ways to protect an organization’s data:
- Data security means protecting your data from unauthorized access or use where it could be leaked, deleted or corrupted. An example of data security is the use of encryption to prevent hackers from using your data if it is compromised.
- Data protection refers to making backups or copies of data to prevent accidental deletion or loss. An example of data protection is backing up your data, so if data is corrupted or deleted due to a disaster or a cyberattack, it is not lost.
- Data privacy refers to concerns about how data is processed, including data sensitivity, regulatory requirements, consent, and notifications. An example of data privacy is the use of a separate, secure database for personally identifiable information (PII).
Data Security Threats
Here are a few of the most common threats facing organizational data.
Social Engineering Attacks
Social engineering attacks are the primary medium used by attackers to gain access to sensitive data. This includes manipulating or deceiving individuals to provide personal information or access privileged accounts.
Phishing is a common form of social engineering. This includes messages that appear to come from a trusted source but are actually sent by an attacker. If an employee is convinced to provide personal information, click a malicious link, or open a malicious attachment, the attacker can compromise the user’s device or account and gain access to the corporate network.
Security Misconfiguration
If a computing system does not have security settings properly defined, or is kept with the default username and password, a security misconfiguration occurs. This typically means that a system’s configuration does not comply with security standards, such as CIS benchmarks, the OWASP Top 10, or specific compliance requirements.
Shadow IT
Unauthorized use of third-party software, applications, or Internet services in the workplace, known as shadow IT, is difficult for IT departments to track. Shadow IT is very common because employees habitually use applications they know from their personal lives, which are more efficient, lightweight, and easier to use than company-approved alternatives.
Ransomware
Ransomware is a top priority in any organization’s cybersecurity program, and it directly affects data security. In a ransomware attack, the victim’s computer is infected by malware that encrypts valuable files or entire devices, making it impossible for victims to use the equipment and data.
Advanced Persistent Threat Attacks
An Advanced Persistent Threat (APT) is a targeted network attack that goes undetected for a long period of time after attackers penetrate the network. The purpose of APT attacks is not to compromise systems or networks but rather to monitor network activity and steal data over a prolonged period of time.
Types of Data Security Controls
Here are some of the most common security controls organizations can put in place to secure their data.
Access Controls
Access controls are physical and digital mechanisms that limit access to critical systems and data.
Authentication
Authentication is another layer added on top of access controls, which defines how a system verifies user identities before granting access.
Backups & Recovery
Backup and recovery is a critical part of data security, providing a strategy for restoring data in case of a disaster, system failure, or data corruption.
Data Erasure
Erasing data is an important data security control that ensures stored devices do not retain sensitive information.
Data Masking
Data masking hides sensitive information by replacing it with anonymized or randomized data.
Data Resiliency
A key part of data security is ensuring that systems are able to endure failure and rapidly recover.
Encryption
Encryption uses algorithms to transform files into an unreadable format, essential for protecting data from attackers.
Data Security Solutions
Software vendors provide a variety of tools that can help improve data security.
Data Discovery and Classification Tools
Data discovery is the basis of any data security strategy. An organization must understand what data it owns, and which of the data is sensitive and requires protection.
Data and File Integrity Monitoring
Data and File Integrity Monitoring tools provide visibility over file systems and databases and report on the sensitive data being accessed.
Vulnerability Management Tools
These tools can help identify software that needs to be updated or patched and security misconfigurations for data stores.
Automated Compliance Management and Reporting
These tools have the relevant compliance standards built in and can scan an organization’s systems for specific compliance issues.
Data Security Best Practices
Here are a few best practices that can help you secure data more effectively.
Identify and Classify Sensitive Data
Collaborate with your security team to scan data stores and classify them by sensitivity.
Create a Unified Data Security Policy
Create an inventory encompassing all your data and implement a unified security policy for appropriate data protection.
Deploy Identity And Access Management (IAM)
Look for an IAM solution that lets you define and implement access policies based on the least privilege principle.
Carry Out Employee Security Training
Companies must train their employees, explain the policies and their importance, and show them how to manage sensitive data.