Data loss or data leak prevention (DLP) is a well-known approach for detecting and preventing the loss, leakage, or misuse of data through unauthorized access, breaches, and exfiltration. Traditional DLP solutions use a reactive approach to ensure that sensitive enterprise information like IP, customer data, and financial records are protected from exposure.
But what if an organization requires a more proactive way to protect itself against insider risk, accidental disclosure, and external attackers? In this scenario, it may be time to start thinking about data loss protection.
A data loss protection initiative requires advanced technologies to keep data safe. It’s more proactive and reduces false positives, while ensuring strong access controls and encryption.
Below, we’ll break down what’s involved in data loss protection, how it’s different from traditional DLP approaches, and what technologies can help implement an effective data loss protection strategy.
What are the downsides of traditional DLP?
By reacting to incidents in real-time, DLP solutions can help organizations respond quickly to data breaches, minimize their impact, and prevent further data loss and liability. But it’s important to note that data loss prevention should be just one part of a comprehensive data protection strategy — particularly because DLP approaches have some notable weaknesses.
Below, we’ll explain several drawbacks and challenges posed by traditional DLP tools.
Reactive controls. DLP is typically considered a reactive control because it focuses on detecting and mitigating attempted data breaches and leaks that have already occurred or are already in progress. By monitoring and analyzing data in motion, a traditional DLP solution can identify and prevent unauthorized transfers or access — but only when data is already on its way out. To achieve a strong defense-in-depth framework, DLP must be complemented by proactive measures like access controls and encryption.
False positives. Because of inaccuracies in data detection and a lack of context around incidents, data loss prevention systems often issue erroneous or inaccurate alerts. These alerts indicate the presence of a data breach when no actual security incident has occurred. Such false positives can generate a large number of unnecessary alerts and create additional workloads. They can also overwhelm security teams and lead to alert fatigue, where genuine security incidents may go undiscovered or unnoticed due to the constant noise of false positives.
Monitoring-only mode. One report by CompTIA suggests that over 90% of active DLP installations are running in “monitoring-only” mode. This means that the DLP tool will notify an organization when data has been leaked — but it won’t take automatic measures to stop the leak, and it will require manual actions for a proper investigation. In these cases, security teams can quickly be overwhelmed by false positives and the “needle in the haystack” element as they manually search for the source of the leak.
Business processes. DLP tools often require business processes and data workflows to be adjusted to the DLP strategy. If DLP is implemented without a strategy on how to align it with existing business processes and data workflows, the effectiveness of both the DLP program and the overall business itself is negatively impacted
Complex and evolving data environments. Organizations increasingly operate in highly dynamic data environments with numerous communication channels, collaboration tools, and cloud services at play. DLP tools may struggle to keep pace with the changes in these complex environments, particularly in the cloud. That leaves them ultimately providing inadequate coverage and missing serious threats across different data repositories within the enterprise.
Attacks that evade detection. Cyber attackers are constantly evolving their techniques to bypass security solutions, including data loss prevention tools. For instance, sophisticated attackers may compress or split data into smaller files to evade DLP detection, or they may modify the format of data to render it unrecognizable.
Data loss protection: a proactive alternative to DLP
Organizations seeking a more proactive stance — one that protects data before it ever leaves the enterprise environment — should consider data loss protection. It’s conceptually simple: protect data in the environment where it resides, before exfiltration is even attempted. Rather than implementing data security controls only at the egress points where data is leaving the organization, data loss protection involves applying security measures to data as soon as it’s written to storage.
This approach offers several obvious benefits. Most importantly, it prevents unauthorized users from reading data, even if they manage to gain access to the storage location. That applies not only to malicious hackers but also to potential internal threats like infrastructure providers and local storage administrators who shouldn’t have access to data for compliance and regulatory reasons.
A data loss protection approach also does not rely on monitoring tools alone as the first line of defense to detect every single data breach or leak. It ensures that sensitive data remains protected at all times, while allowing traditional DLP solutions to focus on detection and monitoring. Since the DLP solution is no longer the first line of defense, the negative side effects of false positives and the need for fine-grain tuning of the system are mitigated.
Data loss protection with ShardSecure
The ShardSecure platform offers a proactive approach to data loss protection. Our technology offers advanced file-level protection for unstructured data the moment it’s written to storage — whether that’s on-premises, in the cloud, or hybrid- and multi-cloud storage. Even if an unauthorized user like a cyberattacker or a cloud storage admin accesses data, our technology renders it unintelligible and unexploitable.
Unlike traditional, reactive data loss prevention tools, ShardSecure’s data loss protection solution is able to maintain strong data confidentiality, integrity, and availability. It also transparently reconstructs damaged data in the face of ransomware attacks, cloud provider outages, and other disruptions.