Types Of Data Security Controls & Best Practices to Implement Them

What Are Data Security Controls?

Data security controls are measures implemented by organizations to protect their data from loss, theft, or misuse. These controls are typically divided into three categories, known as the CIA triad: Confidentiality, Integrity, and Availability.

• Confidentiality controls focus on limiting access to data. This is achieved through mechanisms such as Access Control Lists (ACLs), encryption, OAuth systems, and two-factor authentication.
• Integrity controls ensure the accuracy and completeness of data. They involve controlling access to data, tracking changes made to it, and implementing measures like hashing and signatures to verify data integrity.
• Availability controls ensure that data is accessible when needed. This includes creating archives, storing data on high availability file systems, and using reliable databases.

Types of Data Security Controls

In addition to the above categories, data security controls can be divided into two inter-related categories, namely: internal and incident response controls. These controls are explained in more detail below:

1. Internal Controls

Internal controls are measures that protect data within a company’s internal workflows and operations. This includes administrative controls, which are policies and procedures for handling sensitive data, as well as technical controls, which involve tools and software like access controls and encryption. Architectural controls also fall under this category and focus on how the business handles data on its own servers and in the cloud. These controls aim to identify and address any weaknesses in the network. Below is a more detailed explanation of these internal controls:

• Technical controls are data security controls that use software tools and hardware equipment to enhance data security. Examples include firewalls, encryption, directory services, and intrusion detection systems. Data masking, another form of encryption, helps to control access to data by obscuring the data with proxy characters that render the data useless in the event of a breach. Data erasure also helps by permanently removing unnecessary data, eliminating any potential risks.
• Architectural controls are data security controls that focus on the design and configuration of systems and networks to prevent cyber attacks. Examples include Zero Trust, network segmentation and zoning, server replication, and secure coding practices.
• Operational controls are data security controls that involve implementing operational procedures, rules, and mechanisms to protect data. Examples include security training, incident response plans, data backup and recovery processes, and security testing and monitoring.
• Administrative and physical controls are data security controls that involve establishing policies, procedures, and standards for data security and using physical barriers and safeguards. Examples include security policies, risk assessments, security awareness programs, access control systems, surveillance cameras, and secure server rooms and storage facilities.

2. Incident Response Controls

Incident response controls are measures taken in response to a cyberattack or security breach. This includes preventative measures such as implementing the principle of least privilege and network security enforcement technologies. Solutions are used to detect unauthorized access or anomalous activity, restoring lost data and applying security patches. Incident response requires preventive, detective and corrective controls, which are explained below:

• Preventive controls aim to prevent data breaches by implementing measures such as system and software hardening, least privilege, multi-factor authentication, and anti-network sniffing.
• Detective controls focus on detecting and identifying threats in the IT environment before they become major attack vectors. Continuous monitoring and intrusion detection systems are used to scan for potential threats.
• Corrective controls come into play after a data breach has occurred. They include disaster recovery procedures such as patching vulnerabilities, data restoration, and applying antivirus software.

Best Practices for Implementing Data Security Controls

It is important to adhere to industry best practices and standards when selecting security controls. Before moving on to more complex controls, it is recommended to start with the following basic controls:

1. Keep an inventory of all hardware and software: Regular inventories play a significant role in identifying security vulnerabilities and weaknesses within systems. By conducting inventories, organizations can ensure that the operating systems and antivirus protection on their servers are up to date and that no unnecessary applications are installed on any devices or systems.
2. Establish baselines for hardware and software: Establishing standardized settings for hardware and software helps to speed-up the provisioning process while enhancing data security. This practice ensures consistency and uniformity throughout the organization.
3. Use a real-time activity monitoring solution: Consistently monitoring activity within the environment allows security teams to detect any suspicious behavior in real-time, enabling them to respond before any significant damage occurs. Additionally, auditing provides valuable insights for improving security policies.
4. Use vulnerability management solutions: Vulnerability scanning tools help assess network elements that may jeopardize data security, such as open ports. Furthermore, conducting penetration testing allows organizations to evaluate the effectiveness of their data security policies, network architecture, and other security measures.
5. Secure remote access: Secure access to internal data for employees working remotely is vital. Strong authentication measures should be implemented, and IT teams should evaluate the devices used to access sensitive data. Detailed remote access usage logs are essential for investigations and accountability.
6. Discover and classify your sensitive data: Understanding the types and locations of data within the network is a crucial part of data security. Implementing a data discovery and classification solution allows organizations to map their data and categorize it based on sensitivity and compliance mandates, providing better risk management and improving accessibility.
7. Use endpoint protection solutions: Endpoints are often the entry point for malware and virus infections. Security teams can combat these threats by using anti-virus software, anti-spyware, anti-adware, and other malware protection solutions.
8. Establish a robust backup and recovery plan: Prompt restoration of data and operations is crucial for organizations. Whether it’s an accidental file deletion, server failure, or a targeted attack, having a well-defined disaster recovery plan that outlines the necessary steps for data retrieval and incident response is essential.

How Lepide Helps Protect Sensitive Data

The Lepide Data Security Platform helps protect sensitive data by detecting and responding to anomalous activity in real-time. It uses advanced machine learning algorithms to establish a baseline of normal activity, and monitors user behavior to identify deviations from this baseline. It identifies users with excessive permissions, helping security teams apply appropriate access controls. The Lepide platform comes with a built-in data discovery and classification feature, allowing you to easily locate and safeguard your most valuable assets. The platform also simplifies Active Directory cleanup by automating the removal of inactive or obsolete accounts. In the event of a security incident, Lepide provides valuable insights and aids in forensic analysis.

If you’d like to see how the Lepide Data Security Platform can help to protect your data from loss, theft, or misuse, schedule a demo with one of our engineers.