A Guide to SaaS Data Loss Prevention (DLP)

In the past, all of a company’s data was stored on physical storage systems — punch cards, magnetic tapes, hard drives, floppy disks, compact discs, and USB flash drives. The job of protecting the data was relatively straightforward. Limit access to these physical devices, and things were good. 

Data protection became far more challenging as data migrated to the cloud and then to decentralized storage systems. Not only has the number of data storage systems increased, but each adds another data pipe that must also be secured. With 60% of all corporate data being stored in the cloud, the attack surface that security and IT teams have to manage and protect from internal and external threats is mind-boggling. When the area that you have to protect grows exponentially, how do you protect it? The solution is a data loss prevention (DLP) system.

This guide was developed to help you understand the importance of DLP, factors to consider when planning a SaaS DLP initiative, and share best practices for implementing one.

Why is DLP for SaaS important?

There are numerous reasons why companies should pay attention to SaaS DLP. It helps organizations protect their most sensitive data and ensure that personal data, financial records, intellectual property, and other proprietary information remain secure and confidential. DLP policies also help ensure that sensitive data only ends up where it’s supposed to. An example? Imagine a scenario where customer financial data can be restricted only to Salesforce, and prevented from finding its way into Google Docs. This would allow security teams to breathe more comfortably because they know there are controls in place to prevent someone from stealing that data and that regulated data is stored in the proper location to comply with compliance standards such as PCI DSS. These policies also help to prevent data leakage and prevent employees from putting vital company information into a questionable AI tool, which may actually be a veiled attempt to steal data.

DLP for SaaS ensures data in SaaS applications is properly stored and protected, lowering the risk of data breaches and the associated costs. With the average cost of a data breach hovering around the $4.5M mark, organizations are naturally concerned about the severe financial and reputational threats posed by data breaches, and DLP provides the protection they need. 

This protection extends to insider threats, which cost companies an average of $15.4M, more than three times as much as the average data breach. Not all insider threats are malicious, of course. Employee-related risks can be intentional or accidental. The latter makes it more difficult for companies to secure their data. Still, a DLP solution can prevent both by monitoring user activity and enforcing policies to prevent data exfiltration - maliciously or mistakenly.

For companies bound to strict data protection regulations such as GDPR or HIPAA, DLP offers automated assurance that they comply. Implementing DLP helps organizations automatically ensure that proper data handling practices are always observed, preventing costly mistakes that could result in greater scrutiny from regulators, and hefty fines. 

One of the biggest costs associated with data breaches is the loss of business continuity. Data breaches cause an average disruption in business operations of 22 days. This translates to downtime, loss of productivity, and loss of revenue. Implementing a DLP solution helps to lower the chances of a disruption happening as a result of a data breach by helping businesses to maintain continuity and recover quickly in the event of a security incident. 

Businesses that commit to protecting their customers’ data help engender trust with those customers. Beyond the obvious security implications of implementing DLP measures, a commitment to DLP can also be viewed as a brand-building effort, in the same way that Apple uses its commitment to privacy as a business differentiator.   

Factors to Consider When Implementing SaaS Data Loss Prevention

Implementing a DLP measure successfully within your organization involves far more than finding, vetting, and selecting a tool that claims to help you solve your DLP woes. It requires support from every corner of the organization and a commitment to ongoing improvements to the initiative. The main factors you should consider when rolling out a DLP initiative are listed below.

Policy development

Policy development is the first step any organization should focus on before rolling out a company-wide initiative, as it helps to provide the framework and guardrails that help maximize its chances of success. The benefits of developing a policy framework for your SaaS DLP initiative are:

Clear objectives and definitions. By developing a DLP policy, your organization sets clear objectives for the DLP initiative and articulates its commitment to protecting sensitive data. The policy also defines what constitutes ‘sensitive data’ so that everyone clearly understands its meaning and what sort of data to prioritize protection for. This provides the clarity necessary to enable a successful rollout of the initiative throughout the organization.

Risk assessment and classification. Policies guide the process of identifying and classifying sensitive data based on its level of sensitivity and regulatory requirements. This classification helps prioritize data protection efforts, ensuring that resources are allocated effectively to safeguard the most critical information assets. 

Compliance with regulations. DLP policies align organizational practices with legal requirements, outlining data handling, retention, and disposal procedures to ensure adherence to applicable regulations. 

Consistency across the organization. Policies promote uniformity in your company’s data protection practices across your organization. Whether spanning departments or geographies, they ensure a consistent approach to every data handling, encryption, access control, and incident response scenario. Removing inconsistencies helps reduce the risks of vulnerabilities or breaches by ensuring that the response has been identified as your organization's best course of action.

Implementation of technical controls. Policies guide the selection and deployment of technical controls and DLP solutions tailored to the organization’s risk profile and operational needs. They provide a framework for integrating security measures such as encryption, access controls, and data masking into existing IT systems and workflows.

Continuous monitoring and improvement.  DLP policies include provisions for ongoing monitoring, evaluation, and improvement of data protection measures. Regular audits and assessments ensure that policies remain current and effective against evolving threats, enabling proactive adjustments to security strategies as needed.

Data discovery and classification

Data discovery and classification form the basis for effectively identifying, categorizing, and protecting sensitive data within an organization. These processes help with a host of different efforts, which include:

Comprehensive data identification.  Data discovery is the first step in data protection, and it involves the systematic scanning and analysis of all data repositories within an organization, including databases, file servers, cloud storage, and endpoints. Once the data is collected, automated tools and techniques are used to identify sensitive information in this data.

Locating data across networks. Data is typically scattered across different systems and locations in modern enterprises, and to perform a comprehensive data inventory, data discovery tools must locate data that’s on-premises, stored in the cloud, and on mobile devices. 

Classification based on sensitivity. After the data has been identified, it is classified based on its sensitivity and importance to the organization. Labels or tags are applied to the datasets to indicate the level of confidentiality, integrity, and availability that they are required to adhere to. These labels allow organizations to prioritize protection efforts and allocate resources accordingly when handling the data.

Granular access control. Proper classification enables organizations to implement granular access controls, which help ensure that only authorized personnel can access sensitive data. Each employee’s level of access is pre-determined and dictated by the organization’s security policies and the type of data they need to access to perform their job. Role-based access controls (RBAC) are often integrated with data classification schemes to enforce least privilege principles and minimize the risk of unauthorized access.

Facilitating audits and assessments.  Data classification provides a structured framework for conducting internal audits and external assessments of data protection practices. It simplifies auditors’ jobs by making it easier to verify that security controls are appropriately aligned with the sensitivity of classified data, identify areas for improvement in DLP strategies, and ensure compliance with organizational policies and regulatory requirements.

Access control and encryption

Access control and encryption are critical safeguards that protect sensitive data from being accessed, misused, and exposed. They function by implementing the following:

Principle of least privilege. Through the use of RBAC, users are only granted access to the data and resources necessary to conduct their jobs, based on their specific role and responsibility within the organization. Limiting privileges based on operational requirements and job functions minimizes the chances of inadvertent or malicious data breaches that result from unauthorized access. 

Granular permissions management. Access control policies are set at the organizational level, and they define who can access sensitive data, from where, and under what circumstances. Granular permissions management allows administrators to enforce these data access policies. This helps to ensure that only authorized individuals or systems can view, modify, or delete sensitive information–reducing the attack surface and enhancing overall data security.

Data-at-rest encryption. Data-at-rest refers to data stored on physical and virtual devices, such as servers, databases, and endpoint devices. Data-at-rest encryption protects this type of data against unauthorized access and data theft in the event of device loss or theft using encryption. Encryption transforms sensitive data into ciphertext using cryptographic algorithms. This ciphertext cannot be read by anyone who doesn’t have the decryption key.

Data-in-transit encryption. Data-in-transit refers to data as it moves between endpoints, networks, and cloud environments. Like the method of protecting data-at-rest, encryption is used to encrypt data packets during transmission using secure communication protocols such as TLS/SSL. Encrypting data packets that are being transmitted deters malicious actors from attempting to eavesdrop or manipulate sensitive information during transit since they cannot extract anything useful from it without the decryption key.

Enhanced data confidentiality. Combining access control and encryption enhances data confidentiality by restricting access to authorized users and ensuring that sensitive information remains protected from unauthorized disclosure or exposure.

Monitoring and incident response

Organizations perform monitoring and incident response to proactively detect, mitigate, and respond to potential data breaches and security incidents. Monitoring and incident response help with:

Real-time data monitoring. Continuous monitoring involves the real-time surveillance of data access, usage patterns, and security events across networks, systems, and endpoints. Monitoring should cover both in-line traffic, which monitors traffic as it leaves an endpoint, and out-of-band monitoring, which involves monitoring your corporate SaaS apps via API. The former monitors for policy violations, while the latter looks for non-compliant data that shouldn’t be in a particular app or system. Organizations can detect anomalies, unauthorized access attempts, and suspicious activities that may indicate potential data breaches or policy violations using advanced monitoring tools and technologies.

Alert and notification mechanisms. A vital function of monitoring systems is promptly alerting and notifying security teams when they detect anomalous behavior that deviates from established baseline behaviors or indicates security incidents. These alerts can be triggered based on predefined thresholds and anomaly detection algorithms to mitigate potential threats before they escalate.

Establishing incident response plans. An incident response plan outlines a set of procedures and protocols that must be initiated in response to a security incident. Whether it’s a data breach, unauthorized access, malware infection, or insider threat, these plans establish clear roles, responsibilities, and escalation paths for incident handlers. This helps ensure a coordinated and effective response to minimize the impact of incidents and restore operations back to normal quickly.  

Early threat detection and mitigation. Proactive monitoring allows organizations to detect security incidents early, which helps them mitigate threats, minimize potential loss of sensitive data, and prevent disruptions to business operations. Rapid detection and response to incidents help companies to contain breaches, prevent data exfiltration, and mitigate the financial, legal, and reputational consequences of data loss.

Compliance and regulatory considerations

Organizations that comply with regulatory requirements and have effective incident protocols ensure that they protect their sensitive data, meet legal obligations, and mitigate the impact of security incidents. Compliance and regulatory considerations help protect data by providing guidelines and standards for data protection measures, including data encryption, access controls, data minimization, and privacy-by-design principles. 

User education and awareness

68% of data breaches involve a non-malicious human element, which underscores the importance of user education and awareness in helping to combat data loss. These efforts help your employees to: 

Understand data risks. User education programs empower employees at all levels of the organization to recognize the importance of data security and understand potential risks associated with mishandling sensitive information. Educated users are more likely to adopt security best practices and adhere to organizational policies to protect data confidentiality, integrity, and availability.

Recognize social engineering threats. User education can help organizations reduce the chances that employees fall victim to social engineering attacks. These initiatives raise awareness about common social engineering tactics such as phishing scams, pretexting, and baiting, which malicious actors use to manipulate individuals into divulging sensitive information or compromising organizational systems. Educating users about these threats reduces the likelihood that they’ll fall victim to these attacks, safeguarding your data. 

Best practices for implementing SaaS data loss prevention

Now that you’re familiar with the things you need to consider when rolling out a SaaS DLP initiative, here are some best practices that can help guide your choices for the implementation.

Discover and classify sensitive data

Understanding and identifying sensitive data within your organization is the basis for selecting the appropriate security controls to protect that data. Leverage automated data discovery tools to scan networks, databases, file systems, and endpoints to identify and catalog sensitive data. Classify data with the appropriate labels—public, internal, confidential, and restricted–and develop policies to apply these classifications. Consistent data labeling and metadata tagging help ensure proper data handling, so make this a core part of your process.

Use data encryption

Encryption is critical to any DLP strategy since it converts plain text data into an unreadable format unless you have the correct decryption key. It protects data stored on devices and storage media and data transmitted over networks.

Control access to sensitive data

Organizations can significantly reduce the risk of data breaches and unauthorized disclosures by ensuring that only authorized individuals can access sensitive information. You can do this by implementing role-based access control (RBAC), which helps to define roles, assign permissions, assign time-based access, and provide access requests. Regular audits of access logs and real-time monitoring of access requests should be a core part of your approach.

Keep systems up-to-date

Maintaining up-to-date software, systems, and security measures is a top priority as security threats evolve. Staying current on updates helps ensure that vulnerabilities are promptly patched, security features are enhanced, and your organization remains resilient against evolving threats. Some best practices include setting up patch management tools to schedule and deploy updates across the network and systems, regularly updating operating systems and software, and monitoring end-of-life and end-of-support dates to avoid security risks associated with unsupported products.

Use automation when and where possible

You should automate your DLP processes as much as possible. This improves efficiency, enhances the effectiveness of data protection measures, and helps minimize errors. Automation can be leveraged in numerous aspects of DLP, from data discovery and classification to policy enforcement to incident detection and response. Automation should also be applied in areas that can really get bogged down if performed manually, including patch management, reporting and compliance monitoring, and employee awareness and training.

Educate your teams

Employees are your first line of defense when it comes to data protection. Educating them about data loss prevention helps create a strong defense against data breaches, insider threats, and human errors that could compromise sensitive information. As part of their education, develop a comprehensive training program that addresses your organization’s specific risk profile and security needs. The customized training materials should cover key topics in data loss prevention, including phishing awareness, password security, data handling, and device security.

Continuously monitor and refine policies

Ongoing monitoring and policy refinement are critical to ensuring security policies remain relevant to changes in the threat landscape and organizational goals. Steps to ensure the latter include establishing a policy review schedule, staying abreast of regulatory changes, implementing version control and documentation, and testing and validating policies before broad implementation. Build these into your annual planning process to make sure that they’re not overlooked.

Data loss prevention with an enterprise browser

A lot of today’s work happens outside the office, often from unmanaged devices and networks. Organizations use a growing list of SaaS and web applications to enable work, a scenario legacy DLP platforms were not designed to handle.

Island’s Enterprise Browser builds data loss protection capabilities into the browser itself, delivering a more effective and efficient way to protect data, regardless of whether the work is performed within the perimeter of the company’s network or over an unmanaged network. These DLP controls protect sensitive data before it leaves or enters the browser and offers several core capabilities. They provide application and data boundaries, which keep sensitive data within the confines of predefined enterprise applications and prevent leakage across all means of egress. They mask sensitive data from view on a page until the data is actually needed. DLP detectors flag sensitive data to stop leakage, regardless of which application it originates from. 

Island also incorporates features that double as both productivity features and provide DLP capabilities. These features include built-in productivity tools such as an AI Assistant, Password Manager, and Clipboard Manager, which enhance efficiency and user satisfaction. Your employees also don’t have to download other tools with questionable origins to perform these functions, helping safeguard your data even more.

If you want to preview a future where all data interactions inside SaaS and web apps remain fundamentally secure, drop us a note. We’re excited to share what the future of work looks like and the opportunities it will unlock for your team.