75% of organizations have migrated some or all of their data to the cloud.
As the world is moving to digital infrastructure, businesses have been opting for cloud technology to become more flexible. However, organizations’ wide cloud adaptation has increased the risk of data breaches and thus urgently necessitates robust security measures. Security is a key issue for enterprises because data stored in the cloud faces numerous threats, such as access by unauthorized users and accidental exposure or deletion of sensitive information.
That is where Data Loss Prevention (DLP) solutions step in.
DLP is a security strategy for making sure that end users do not send sensitive or critical information outside the corporate network. Organizations are continuing to store and process massive amounts of data in the cloud, making protecting that information crucial. A solid data loss prevention solution reduces the risks of sensitive data from being exposed, ensures compliance with regulations and legislation related to information security, significantly improves the overall protection level for companies working in cloud environments, and aids in identifying sensitive data.
Understanding Cloud Security Challenges
When businesses transition their data and operations to the cloud, they face many security challenges. Identifying sensitive data is crucial in overcoming these cloud security challenges, as it helps in classifying and monitoring sensitive information within an organization’s digital environment.
1. Data Privacy and Compliance
Challenge: Cloud environments often save personal and financial sensitive data, which attracts more stringent compliance regulations such as GDPR, HIPAA or CCPA.
Why it matters: Violations of sensitive information can result in hefty legal penalties, loss of business, and reputational damage.
Solution: Set up restrictive data governance and implement security controls (DLP) to abide these regulations. Identifying sensitive data is a crucial step in setting up data governance and security controls.
2. Data Breaches and Unauthorized Access
Challenge: As Cloud platforms are shared and distributed in nature; hackers have an easy way to intrude your private data.
Why it matters: Data breaches can cost you millions of dollars or even cost you your business with intellectual property theft and business disruption.
Solution: Use multi-factor authentication (MFA), encryption, and DLP to detect and prevent unauthorized access attempts. Identifying sensitive data within your organization’s digital environment is crucial for understanding what data is present and how it is used, facilitating the detection of unauthorized access and ensuring an effective data security strategy.
3. Insider Threats
Challenge: Not just external attackers pose a threat but employees with sensitive data might cause data breach inadvertently or because of malice.
Why it matters: Insider threats are more difficult to identify than outside hacks, but the consequences can be equally damaging.
Solution: Enforce robust controls on access and use cloud data loss prevention solutions to monitor and detect malicious activity from within the company. Identifying sensitive data is crucial to classify and monitor information, facilitating the detection of unauthorized access and ensuring an effective data security strategy.
4. Data Visibility and Control
Challenge: When data is moved to the cloud, it can be more challenging track — where and how the data is stored and who has access to that information.
Why it matters: A lack of visibility increases the risk of breach and makes it more difficult to detect potential threat.
Solution: Cloud data loss prevention solutions offer centralized visibility and control over sensitive data to administer protection over all the cloud storage. Identifying sensitive data is a key step in achieving centralized visibility and control.
What is Cloud Data Loss Prevention (DLP)?
Definition and Importance
Cloud Data Loss Prevention (DLP) is a proactive data security strategy designed to monitor, detect, and prevent the exposure or exfiltration of sensitive data within cloud environments.
As organizations increasingly rely on cloud services, the need to protect sensitive data from unauthorized access, data breaches, and data leaks becomes paramount. Cloud DLP solutions employ advanced techniques such as data classification, pattern matching, and machine learning to accurately identify and safeguard critical information. By enforcing context-aware policies, cloud DLP ensures compliance with regulatory standards, such as the General Data Protection Regulation (GDPR), and mitigates the risk of data breaches in complex cloud-based infrastructures. Implementing a robust cloud DLP solution is essential for maintaining data security and protecting sensitive data in today’s digital landscape.
What is a DLP Solution?
Data loss prevention is a collection of different tools and platforms that ensures that sensitive data is not accessed and misused by anyone. DLP solutions play a very important role in protecting data at multiple levels, including when it is being transmitted from one location to another (data-in-transit), stored on a storage device (data-at-rest) and when the data are active or processed by an application, user, etc. Identifying sensitive data is crucial for the effectiveness of DLP solutions, as it helps in classifying and monitoring sensitive information within an organization’s digital environment.
How DLP Solutions Work
Data loss prevention solutions focus on protecting data in three key states:
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Role of DLP in Cloud Security
The covid-19 changed the way we worked as most of the world is either working from home or working in a hybrid model. That being said, now more and more organizations rely on cloud environments as their data storehouse. With the sensitive data lying over the cloud, one of the key security controls these organizations can add is Cloud Data Loss Prevention (DLP) — to identify, monitor, and protect cloud data across your cloud infrastructure. Identifying sensitive data is crucial in cloud DLP solutions to ensure effective data security and detect unauthorized access.
1. Identifying and Protecting Sensitive Data
Identifying sensitive data is crucial for Data Loss Prevention solutions to detect sensitive data within cloud environments. Cloud data loss prevention tools scan and classify data based on predetermined policies that recognize sensitive information (PII, financial records or intellectual property). It is designed to protect cloud data by knowing where data is stored. This categorization process is also critical to ensure data security and prevent unintended exposure or unauthorized access to the storage.
2. Monitoring and Enforcing Security Policies
After data is classified, cloud DLP solutions implement security policies dictating the ways in which this information can be accessed and shared. Identifying sensitive data is a crucial step in implementing these security policies. Sensitive information can easily be mishandled in cloud environment due to multiple users and shared nature of the data. DLP tools constantly track the movement of data and user activities against security policies configured in them. Whenever any suspicious activity and policy violation is the cloud data loss prevention systems can automatically raise alerts or even block actions to avoid data spills.
3. Preventing Unauthorized Access
One of the key aspects for DLP in cloud security is stopping unauthorized access to private data. Identifying sensitive data is crucial in preventing unauthorized access by understanding what data is present and how it is used. However, cloud environments are more vulnerable to external and insider threats. Cloud data loss prevention solutions can detect abnormal access patterns such as unauthorized users, or suspicious behavior. DLP helps in and controlling data manipulation activities so that the risk of falling prey to such attacks can be reduced.
4. Ensuring Compliance
Organizations using cloud services need to be compliant with various data protection regulations like — GDPR, HIPAA and CCPA etc. Identifying sensitive data is crucial in ensuring compliance with these regulations. Cloud based DLP solutions are instrumental in making sure sensitive data is used within these regulatory lines. This is why DLP helps to keep companies compliant by enforcing policies around how data should be handled and documented, as the risk of leaks or loss increase without it.
To sum up, Cloud data loss prevention solutions play a critical role in cloud security by providing strong capabilities to discover and classify sensitive data along with monitoring its movement.
Traditional DLP vs. Cloud DLP
Key Differences
Traditional DLP solutions and cloud DLP solutions serve the same fundamental purpose of protecting sensitive data, but they differ significantly in their deployment and functionality. Traditional DLP solutions are typically deployed on-premises, focusing on safeguarding an organization’s endpoints and internal network infrastructure. These solutions are well-suited for environments where data primarily resides within the organization’s physical boundaries.
In contrast, cloud DLP solutions are specifically designed to protect sensitive data stored in cloud environments. They offer advanced features such as data classification and policy enforcement to address the unique security challenges posed by cloud storage and applications. Cloud DLP solutions are inherently more scalable and flexible, making them ideal for modern organizations that operate in dynamic and distributed cloud environments. By leveraging cloud DLP, organizations can ensure comprehensive protection of their sensitive data, regardless of where it resides or how it is accessed.
Wondering what sets the best DLP solution apart?
Find out in our network DLP buying guide! This guide discusses:
- Key Features & Requirements
- Robust Architecture of DLP
- Accurate Inspection of Data
Key Features to Look for in Effective Cloud DLP Solutions
When selecting a Cloud Data Loss Prevention (DLP) solution, you should make sure it has features that protect cloud data across IT infrastructure. Below are the features to look out for in cloud Data Loss Prevention and how Fidelis Network® Data Loss Prevention incorporates them:
Identifying sensitive data is crucial for effective cloud DLP solutions as it helps in classifying and monitoring sensitive information within an organization’s digital environment.
Comprehensive Data Discovery and Classification
Identifying sensitive data is crucial for an efficient DLP solution, which should be capable of automatically identifying and categorizing sensitive data (e.g., Personally Identifiable Information (PII), financial records & intellectual property) in both structured and unstructured formats.
Fidelis Network® DLP provides the automated discovery and deep classification of sensitive data across network traffic.
Real-time Monitoring and Threat Detection
The solution needs to monitor each data in motion, at rest, and in use so that it can detect any suspicious activity. Identifying sensitive data is a crucial step in real-time monitoring and threat detection. It should also include real-time alerts to stop breaches before they happen.
Fidelis Network® DLP supports long-term metadata capture, offering up to 360 days of data retention for in-depth real-time and retrospective security analysis.
Prevention of Data Leaks Across All Ports
An advanced Cloud data loss prevention solution should be able to monitor all traffic across 65,535 ports of network and not even missing any non-standard port. Identifying sensitive data plays a crucial role in preventing data leaks by ensuring that all sensitive information is classified and monitored effectively. This ensures complete cloud data protection is provided for all communication paths and ports.
Fidelis Network® DLP blocks any unauthorized data movement across all network ports, safeguarding sensitive information.
Advanced Content Analysis Technologies
Many different types of sophisticated content analysis must be used for any cloud based DLP to accurately identify the sensitive or protected information. Identifying sensitive data is crucial in advanced content analysis to understand what data is present and how it is used, facilitating the detection of unauthorized access and ensuring an effective data security strategy. This ensures the strict identification of data requiring protection and reduces the risk of false positives or negatives.
Fidelis Network® DLP includes sophisticated content analysis technologies that deliver accurate detection of sensitive data over the network.
Protect Cloud Data with Fidelis Network DLP
In this cloud driven world, protecting sensitive data is more difficult than ever. As organizations are moving to multi-cloud environments like Google DLP, AWS DLP, and Azure DLP, the attackers are constantly finding and exploiting vulnerabilities with their sophisticated attacks.
In the hour of need, Fidelis Security came up with Fidelis Network® Data Loss Prevention solution that provides comprehensive cloud data protection for data stored on a single platform or across multiple cloud platforms. Identifying sensitive data is a key feature of Fidelis Network DLP, ensuring that organizations can classify and monitor sensitive information within their digital environment. By offering all-encompassing cloud native DLP, Fidelis ensures sensitive data is protected from unauthorized access and kept safe from leaks as well as insider threats. It is a combination of the most effective next-gen defenses into a single integrated security solution for comprehensive email and cloud data loss prevention.
Selecting the correct cloud data loss prevention solution is as important as your cloud assets security. Fidelis Network DLP provides a single integrated solution that surveils, protects and adjusts to threats in the ever-evolving security environments of all major cloud providers.
Best Practices for Implementing Cloud DLP
Implementing a cloud DLP solution requires careful planning and execution to ensure effective protection of sensitive data. Here are some best practices to consider:
- Classify Sensitive Data: Begin by identifying and classifying sensitive data, such as personally identifiable information (PII), financial records, or intellectual property. This classification helps determine the level of protection required for different types of data.
- Monitor Data Flow: Continuously monitor data flowing into, out of, and within the cloud environment. This helps detect potential security threats and ensures that sensitive data is not being mishandled or exposed.
- Enforce Context-Aware Policies: Implement policies that consider the context in which data is accessed or shared, such as user identity, location, and device type. Context-aware policies help prevent unauthorized access and data leaks.
- Use Data Encryption: Protect sensitive data both in transit and at rest by using strong encryption methods. Data encryption ensures that even if data is intercepted, it remains unreadable to unauthorized users.
- Implement Data Access Controls: Use role-based access control (RBAC) to ensure that only authorized users have access to sensitive data. This minimizes the risk of data breaches caused by unauthorized access.
- Continuously Monitor and Detect: Regularly monitor the cloud environment for potential security threats, such as data breaches or data leaks. Implementing real-time detection mechanisms allows for quick response to incidents.
- Provide User Education and Training: Educate users about the importance of data security and how to handle sensitive data responsibly. Regular training sessions can help prevent accidental data leaks and reinforce security best practices.
By following these best practices, organizations can effectively implement a cloud DLP solution and protect their sensitive data from unauthorized access, data breaches, and data leaks.
- Increased data visibility
- Sophisticated content analysis
- Robust and adaptable architecture
