8th May, 2022
Data is more portable and sensitive than it has ever been before. The value data holds what makes it susceptible to deletion and leaks.
This necessitates the understanding and implementation of DLP policies and procedures using protocols and tools in such a way that your data is always protected.
Data loss prevention (DLP) is an umbrella term that encompasses tools, methods, and practices that ensure end-users do not send vital or sensitive data outside of an organization and lose it. It keeps sensitive information from being accessed or stolen by anyone without the right authorization.
Additionally, data loss prevention (DLP) refers to data loss prevention software and other data loss prevention technologies that assist network administrators in managing end-user data flows.
There is always a chance of information ending up in the wrong hands, whether shared via texting, email, file transfers, or another way. The term "data loss prevention" refers to systems that monitor, identify, and prevent the unlawful movement of sensitive data for businesses to remain compliant with regulations and maintain consumer trust.
A DLP solution relies on techniques to detect sensitive data and conduct corrective action to prevent incidents of data leaks and loss. Controls for data leakage, data loss, and data exfiltration help reduce the risk of data leakage, data loss, and data exfiltration by ensuring that sensitive information is identified and risk-appropriate controls are implemented, with the goal of having as little impact on business processes as possible.
Data loss prevention tools and techniques can prevent both data breaches (leaks) and data loss. For example, a ransomware attack may result in the loss of critical data.
When sensitive information is transferred across important records systems inside a company, data leakage is more likely. Data loss prevention aims to avert both sorts of illegitimate data movement beyond the business perimeter.
Protecting sensitive information from being accessed, exploited, or destroyed by unauthorized parties is the goal of data loss prevention (DLP). Based on relevant regulations such as the GDPR, HIPPA, or PCI DSS, data loss prevention software classifies data as regulated, confidential, or business-critical.
Then it defines policy violations based on the organization and applicable guidance. DLP data loss prevention software enforces remedies whenever it discovers an infraction, often through protective measures like encryption and alerts.
Network data streams are filtered by DLP software and tools, which also regulate and monitor endpoint operations and keep tabs on cloud-based data. Data in use, data in motion, and data at rest are all protected by a variety of DLP techniques. The reporting function is an important part of data loss prevention tools to meet audit and routine compliance requirements.
Data loss prevention (DLP) technologies are becoming more prevalent. This is primarily due to the variety of ways available for obtaining and maintaining confidential information.
Data can be kept in a handful of environments, including databases, flash drives, file servers, mobile devices, personal computers, physical servers, and the cloud. Due to the fact that data can transit through a variety of network access points, including VPNs and wireless networks, several techniques for dealing with breaches and losses are available.
Data loss prevention (DLP) is essential in any environment where data is kept. One of the most important components of a DLP approach is data in use, data in transit, and data at rest.
Data in use: Some data loss prevention techniques protect data in use, which refers to data that is currently being processed by an endpoint or application at the time of protection. In many cases, these precautions comprise authenticating users and controlling access to resources before giving access.
Data in transit: Data loss prevention technology ensures that confidential data transiting across a network is not routed through unprotected means or outside the organization. Email security, which is the cornerstone of so much commercial communication, as well as encryption, is essential for keeping data safe while in transit.
Data at rest: Data at rest is at risk as well, and data loss prevention solutions safeguard files stored in the cloud and other storage mediums. Data loss prevention software can manage who stores and accesses data, encrypt the disc, and track access to sensitive information.
A comprehensive data loss solution identifies and secures diverse data types while detecting vulnerabilities, allowing you to:
Identify sensitive data that must be protected manually or automatically using metadata and rules.
Control data transfer between external users, users, and groups of users using endpoint-based agents.
Set up tools that detect and alert you of unauthorized activity or unintended violations.
Secure data in motion using network edge technology that analyses traffic to detect critical data infractions.
Encrypt data at rest and enforce data retention policies.
Detects data leaks by monitoring for unusual data transfers.
Comply with Regulations: Secure and comply with personal data, such as that which can be used to identify an individual, as defined by the GDPR, HIPPA, and CCPA. Data loss prevention tools identify, categorize, and tag sensitive data so that context, such as events and actions surrounding the data, may be monitored. Data loss protection tools also report in accordance with regulatory requirements, making compliance audits more manageable if they occur.
Protect your IP: On the internal network, protect the organization's important intellectual property (IP). Data loss prevention tools allow you to classify intellectual property in both organized and unstructured forms based on context. With the proper controls and policies, you can prevent unwanted exfiltration of sensitive data.
Have Data Visibility: Without understanding and the power to act, data is useless. If your company needs more visibility into data flow, a comprehensive enterprise data loss prevention solution can help you monitor and track your data on networks, endpoints, and the cloud. This gives you a better understanding of how individual users and data interact inside your business.
Secure BYOD: Secure environment in which users bring their own devices (BYOD). For personal mobile devices, malware is one of the most critical threats to endpoint security, according to the 2019 McAfee Mobile Threat Report. Malicious exploits frequently use malware as a way to exploit.
Secure the Cloud: On cloud storage systems, ensure that data is protected and that unauthorized parties cannot access it. Data loss prevention techniques for the cloud are used to avoid data breaches and leaks and secure data.
Different tools and techniques ensure data loss prevention.
Data loss and leakage can be prevented using simple data security protocols. For example, a firewall can prevent unauthorized access to important information systems. Computers or endpoint devices can also be protected by intrusion detection systems (IDS), antivirus and anti-malware software.
More advanced data integrity controls, network traffic analyzers, user identity checks, or activity-based verification may assist some companies.
Dedicated data loss prevention tools, on the other hand, maybe suited for larger companies. These solutions are intended to prevent attempts to send or copy sensitive data to unauthorized locations.
We have covered some of the best DLP tools of 2022 here.
Determine your primary data protection objective to determine the most appropriate data loss protection deployment architecture for your organization. It may include increasing data visibility, protecting intellectual property, or meeting regulatory compliance requirements.
Recognize and classify the structured and unstructured data sets so that the data loss prevention strategy can determine which information is sensitive.
Maintain a solid security policy by including frequent audits, security incident recording and remediation, and security incident reporting and tracking.
Clearly define the roles and responsibilities as a part of the organization's data loss prevention program for developing accountability.
Constrain the scope of the data loss prevention strategy to a single category of data or to the automatic identification and classification of sensitive data to keep data transit under strict control.
Documenting how data loss prevention features work in detail will help to guarantee that they are applied consistently. It will also assist employees and the system in producing better records, and it will make the training process for new team members more efficient.
Define key performance indicators (KPIs). Create a list of key KPIs, including KPIs for data loss prevention and other measures of success, and assess their performance on a regular basis. This adds to the enhancement of the data loss prevention strategy over time, as well as the demonstration of the business value of a data loss prevention plan.
Prioritize Data: Prioritize data such that your data loss prevention plan starts with the most sensitive or valuable data.
Classify Data: Classify data depending on contexts, such as the creator, storage location, or source application. Using persistent classification tags allows for data tracking. Regular expression content inspection for PCI, PII, and other regulatory standards is common.
Assess Risk: Risk assessment helps identify which data is vulnerable, when, and where. The riskiest time for data to flow between customers, partners, and endpoints is while it is in use.
Monitor Data: Monitor data in motion to understand how users deploy data and which behaviors put data at risk.
Train Employees: Constantly provide guidance and training to limit the danger of insider data loss. Advanced data loss prevention systems educate employees about dangerous and perhaps illegal data use.
Read our blog post on DLP best practices.